On time-dependent symmetries and formal symmetries of evolution equations
量子力学英文课件格里菲斯Charter10
In molecular physics, this technique is known as the Born-Oppenheimer (玻恩-奥本海默)approximation.
In quantum mechanics, the essential content of the adiabatic approximation can be cast in the form of a theorem.
Here we assume that the spectrum is discrete and nondegenerate throughout the transition from Hi to Hf , so there is no ambiguity(歧义) about the
ordering of the states; these conditions can be relaxed, given a suitable procedure for “tracking” (跟踪)the eigenfunctions, but we’re not going to pursue that
A case in point is our discussion of the hydrogen molecule ion.
We began by assuming that the nuclei were at rest, a fixed distance R apart, and we solved for the motion of the electron.
and they are complete, so the general solution to the time-dependent Schrödinger equation
Beyond Undecidable
a rX iv:mat h /66713v1[mat h.GM ]28J un206BEYOND UNDECIDABLEPAOLA CATTABRIGA Abstract.The predicate complementary to the well-known G¨o del’s provabil-ity predicate is defined.From its recursiveness new consequences concerning the incompleteness argumentation are drawn and extended to new results of consistency,completeness and decidability with regard to Peano Arithmetic and the first order predicate calculus.Keywords:decision problem,provability predicate,G¨o del numbering.Introduction Of all the remarkable logical achievements of the twentieth century perhaps the most outstanding is the celebrated G¨o del incompleteness argumentation of 1931[1,2].In contrast to Hilbert’s program called for embodying classical mathematics in a formal system and proving that system consistent by finitary methods [4],G¨o del paper showed that not even the first step could be carried out fully,any formal system suitable for the arithmetic of integers was incomplete.The present article,in the most absolute respect for the extraordinary contribu-tion given by G¨o del to the logical inquiry,brings G¨o del’s achievement into question by the definition of the refutability predicate.As it is well-known self-reference plays a crucial role in G¨o del’s incompleteness argumentation and the methods of achiev-ing self-referential statements is the so-called “diagonalization”.The refutability predicate,defined by arithmetization as a number-theoretic statement,gives rise to new consequences properly regarding G¨o del’s incompleteness argumentation and the method of diagonalization.This article proposes a revision based on the logical investigation of the interactive links between provability and refutability predicates.Originally devised by G¨o del in order to arithmetize metamathematical notions,G¨o del numbering turns out to be the key of the problem in defining refutability with the same recursive status as provability.The inquiry comes up with a final solution for finitary methods and the related decision problem [3].The paper is organized as follows.Firstly,in the following of this section,we introduce diagonalization and the famous incompleteness argumentation of G¨o del.Section 1presents two new primitive recursive predicates for refutability and the enucleation of some of their consequences,which represent the first main result of this paper:G¨o del’s incompleteness argumentation is not a theorem in Peano Arithmetic.Section 2shows that any formula of Peano Arithmetic is proved if andonly if it is not refuted,and extends this result to the accomplishment of consistency and completeness for Peano Arithmetic and then to the achievement of decidability forfirst order predicate calculus.Basic Setup.We shall assume afirst order theory which adequately formalizes Peano Arithmetic(see for example the system S,with all the necessary assumptions, in[5]116-175).Let us call it PA.As is well known by means of the G¨o del numbering, each expression in PA can refer to itself.Numerals,as usual,are defined recursively,n+1is(n,and this name can be substituted back intoφ(v).This self-reference procedure is admitted by the so-called diagonalization lemma as follows.Diagonalization.For any formulaφwith only the variable v free there is a sen-tenceδsuch that⊢PAδ⇐⇒φ(n)= φ(m).We shall show thatδis the sentence we were looking for.To this purpose we notice that in PA they hold the following equivalences⊢δ⇐⇒β(m,β(v) ,β(δ )by definition.G¨o del’s Incompleteness.We present the version of the so-called G¨o del’sfirst incompleteness Theorem as it is given in([5]161-162),to which the reader can refers for the definition of the concepts which are involved.Letφ(v)be the formula∀x¬P f(x,v),hence by diagonalization lemma we attain⊢P Aδ⇐⇒∀x¬P f(x,r,r,δ ).By Biconditional Elimination,⊢P A∀x¬P f(x,r,δ ), Biconditional Elimination yields⊢P A¬∀x¬P f(x,δ ).On the other hand,since PA isω-consistent,PA is consistent.But,⊢P A¬δ.Hence,not⊢P Aδ;that is,there is no proofin PA ofδ.So Pf(n,q)is false for every natural number n and,therefore,⊢P A¬P f( δ )for every natural number n.(Remember that q.)Byω-consistency,not⊢P A∃x P f(x,1We shall not reproduce entirely this long list of definitions which is already well-known(see also[1]162-176).∃u u<x∃v v<x∃z z<x∃w w<x([x=2w∧Ax(w)]∨[Prf(u)∧Fml((u)w)∧x=u∗2v∧Gen((u)w,v)]∨[Prf(u)∧Fml((u)z)∧Fml((u)w)∧x=u∗2v∧MP((u)z,(u)w,v)]∨[Prf(u)∧x=u∗2v∧Ax(v)].Pf(x,v):x is the G¨o del number of a proof in PA of the formula with G¨o del number v:Prf(x)∧v=(x)lh(x) –1.By means of such definitions,we shall define two new predicates,Rf and Ref.Rf(x,v):x is the G¨o del number of a proof in PA of the negation of the formula with G¨o del number v:Pf(x,z)∧z=Neg(v).In other terms Rf(x,v)states x is the G¨o del number of a refutation in PA of the formula with G¨o del number v2.Rf is primitive recursive,as the relations obtained from primitive recursive rela-tions by means of propositional connectives are also primitive recursive([5]137). For its recursiveness Rf(x,v)is expressible in PA by a formula Rf(x,v).Ref(x):x is the G¨o del number of a refutation in PA:Prf(v)∧v=Neg(x)In other terms Ref(x)states x is the G¨o del number of a proof in PA of its negation.Ref(x)is primitive recursive,as the relations obtained from primitive re-cursive relations by means of propositional connectives are also primitive recursive. For its recursiveness Ref(x)is expressible in PA by a formula Ref(x).Lemma1.For any natural number n and for any formulaαnot both Rf(n, α ) and Pf(n, α ).Proof.Let us suppose to have both Rf(n, α )and Pf(n, α ).We should have thenPrf(n)∧ α =(n)lh(n) –1and Pf(n,z)∧z=Neg( α ),i.e.Prf(n)∧ α =(n)lh(n) –1and Prf(n)∧Neg( α )=(n)lh(n) –1.By the definition of Prf(x)this would mean to have∃u u<n∃v v<n∃z z<n∃w w<n([n=2w∧Ax(w)]∨[Prf(u)∧Fml((u)w)∧n=u∗2v∧Gen((u)w,v)]∨[Prf(u)∧Fml((u)z)∧Fml((u)w)∧n=u∗2v∧MP((u)z,(u)w,v)]∨[Prf(u)∧n=u∗2v∧Ax(v)]and bothα =(n)lh(n) –1and Neg( α )=(n)lh(n) –1and hence the four cases(1)[n=2 α ∧Ax( α )]and[n=2Neg( α )∧Ax(Neg( α ))](2)[Prf(u)∧Fml((u)w)∧n=u∗2 α ∧Gen((u)w, α )]and[Prf(u)∧Fml((u)w)∧n=u∗2Neg( α )∧Gen((u)w,Neg( α ))](3)[Prf(u)∧Fml((u)z)∧Fml((u)w)∧n=u∗2 α ∧MP((u)z,(u)w, α )]and[Prf(u)∧Fml((u)z)∧Fml((u)w)∧n=u∗2Neg( α )∧MP((u)z,(u)w,Neg( α ))](4)[Prf(u)∧n=u∗2 α ∧Ax( α )]and[Prf(u)∧n=u∗2Neg( α )∧Ax(Neg( α ))]which are all immediately impossible by the definitions of Ax(y),Gen(x,y)and MP(x,y,z)and thence by the definitions of the axioms of PA,the Generalization Rule and Modus Ponens,because no axiom belongs to PA together with its negation and the two inference rules preserve logical validity.We now recall the definition of characteristic function.If R is a relation of n arguments,then the characteristic function C R is defined as followsC R(x1,...,x n)= 0if R(x1,...,x n)is true,1if R(x1,...,x n)is false.Let us call the characteristic functions of Pf(x,v),Prf(x),Rf(x,v)and Ref(x) respectively C Pf,C Prf,C Rf,and C Ref.A relation R(x1,...,x n)is said to be primitive recursive(recursive)if and only if its characteristic function C R(x1,...,x n)is primitive recursive(recursive)([5] 137).As Pf(x,v),Prf(x),Rf(x,v)and Ref(x)are primitive recursive then also C Pf,C Prf,C Rf and C Ref are primitive recursive.Every recursive function is representable in PA([5]143),thence C Pf,C Prf,C Rf and C Ref,are representable in PA.We shall assume C P f,C P rf,C Rf and C Ref to represent respectively C Pf,C Prf,C Rf and C Ref in PA.Lemma2.For any formulaα,and n as the G¨o del number of a proof in PA ofα⊢P A C P f( α )=n,1Proof.One can easily see that the two conjuncts are true:as n is the G¨o del number of a proof in PA ofαC P f( α )=n,0∧C P f( α )=n,0is true.By Lemma(1)Pf(n, α )does not hold,therefore it is true that n is not the G¨o del number of a proof in PA of α. Lemma4.For any formulaα(i)not both⊢P A P f( α )⊢P A Rf( α ),(ii)for n as the G¨o del number of a refutation in PA ofα⊢P A Rf( α )⇐⇒¬P f( α ),(iii)for n as the G¨o del number of a proof in PA ofα⊢P A P f( α )⇐⇒¬Rf( α ).Proof.(i)Immediately by Lemma(1)and the definition of being expressible which holds for both Pf(x,v)and Rf(x,v)([5]130).(ii)Let us assume⊢P A Rf( α ),then Lemma(3)yields⊢P A C P f( α )=n,n,n,n,n,n,n,1.Hence by definition Rf( α )is false,consequently⊢P A¬Rf( α ).Con-versely let us assume⊢P A¬Rf( α )then Rf( α )is false and by Lemma(2) we attain⊢P A P f( α ).All preceding lemmas were carried out constructively,needlessly to assume con-sistency.We are now able to consider the consequences yielded by such lemmas to the G¨o del’s argumentation.(a′)Assume⊢P Aδ.Let r be the G¨o del number of a proof in PA ofδ.Then Pf(r,q).Hence,⊢P A P f(q),that is⊢P A P f( δ ).Hence by Lemma(4)(i)⊢P A Rf( δ )is not admitted,which means that r cannot be the G¨o delnumber of a refutation ofδ(indeed Lemma(2)yields⊢P A C Rf( δ )=r,r,r,0).(b′)Assume⊢P A¬δ.Let r be the G¨o del number of a proof in PA of¬δ.Then Rf(r,q).Hence⊢P A Rf(q)that is⊢P A Rf( δ ).Hence by Lemma(4)(i)⊢P A P f( δ )is not admitted.This means that r cannot be theG¨o del number of a proof ofδ(in fact,r is the G¨o del number of a refutation ofδ,Lemma(3)yields⊢P A C P f( δ )=r,r,r,0).We have thus shown that previous Lemmas prevent any accomplishment of(a) and(b)within G¨o del’s argumentation3.We have then established the following theorem.Theorem5.By the arithmetization of the refutability predicate G¨o del’s incom-pleteness does not hold as a theorem of PA.2.Consistency,Completeness and DecidabilityA recursive predicate defines a decidable set,by reason that its characteristic function is considered to be effectively computable([5]165,249).Let us call T P A the set of G¨o del numbers of theorems of PA and R P A the set of G¨o del numbers of refutations of PA.By the recursiveness of Pf(x,v),C Pf(x,v)=0if v∈T P A and C Pf(x,v)=1if v/∈T P A.By the recursiveness of Rf(x,v),C Rf(x,v)=0if v∈R P A and C Rf(x,v)= 1if v/∈R P A.We can than state the following theorem.Theorem6.T P A and R P A are decidable sets.r,It is furthermore well-known that if we have a computable function f(x1,...,x n) such thatf(x1,...,x n)= 0if<x1,...,x n>∈S1if<x1,...,x n>/∈S(where S is a set of natural number which turns out to be decidable just by this definition),then the function g(x1,...,x n)defined byg(x1,...,x n)= 1if f(x1,...,x n)=00if f(x1,...,x n)=1is effectively computable too.Accordingly the complement of S is decidable.One can easily see that for f(x1,...,x n)primitive recursive,g(x1,...,x n)is primitive recursive too.Consequently we haveC¬Prf(x)= 1if C Prf(x)=00if C Prf(x)=1C¬Ref(x)= 1if C Ref(x)=00if C Ref(x)=1C¬Pf(x,v)= 1if C Pf(x,v)=00if C Pf(x,v)=1C¬Rf(x,v)= 1if C Rf(x,v)=00if C Rf(x,v)=1where¬Prf,¬Pf,¬Ref and¬Rf are respectively complementary of Prf,Pf,Ref and Rf.Let us summarize,Prf,Pf,Ref and Rf are primitive recursive,then C Prf,C Pf, C Ref and C Rf are primitive recursive too.But C¬Prf(x)=1−C Prf(x),C¬Pf(x,v)= 1−C Prf(x,v),C¬Ref(x)=1−C Ref(x),and C¬Rf(x,v)=1−C Rf(x,v),thence¬Prf,¬Pf,¬Ref and¬Rf are primitive recursive too.We have then the following statements.Lemma7.For every xPrf(x)if and only if¬Ref(x).Proof.Let us assume Prf(x).C Prf(x)=0.Hence C Prf(Neg(x))=1,by the effective computability of C Prf.Prf(Neg(x))is false,then Ref(x)is false.Accordingly, C Ref(x)=1.Thus C¬Ref(x)=0and¬Ref(x).Conversely,let us assume¬Ref(x).Then C¬Ref(x)=0and C Ref(x)=1.If Ref(x)is false by its definition Prf(Neg(x))is false.Thus C Prf(Neg(x))=1and C¬Prf(Neg(x))=0.Consequently C¬Prf(x)=1,and C Prf(x)=0.Hence Prf(x).If we convent to formalize“a proof in PA ofθ”withθ1...θr⊢P Aθthen we have ⊢P A(θ1⇒(θ2⇒...(θr⇒θ)...))(Herbrand,1930).Indeed Lemma(7)could be read as follows:forθ1,...,θr,θformulas in PA Prf( (θ1⇒(θ2⇒...(θr⇒θ)...)) )if and only if¬Ref( (θ1⇒(θ2⇒...(θr⇒θ)...)) ).Furthermore,by the recursiveness of Prf(x),C Prf(x)=0if x∈T P A and C Prf(x)=1if x/∈T P A.By the recursiveness of Ref(x)C Ref(x)=0if x∈R P A and C Ref(x)=1if x/∈R P A.Lemma8.For every<x,v>Pf(x,v)if and only if¬Rf(x,v).Proof.Let us assume Pf(x,v).C Pf(x,v)=0.Hence C Pf(x,Neg(v))=1.Accord-ingly C¬Pf(x,Neg(v))=0.Thence C¬Rf(x,v)=0and¬Rf(x,v).Conversely,let us assume¬Rf(x,v).We have then¬Pf(x,Neg(v))and C¬Pf(x,Neg(v))=0.Therefore C¬Pf(x,v)=1,by the effective computability of C¬Pf.Accordingly C Pf(x,v)=0 and Pf(x,v).Indeed Lemma(8)could be read as follows:forθ1,...,θr,αformulas in PA Pf( (θ1⇒(θ2⇒...(θr⇒α)...) , α )if and only if¬Rf( (θ1⇒(θ2⇒...(θr⇒α)...) , α ).Lemma9.For m= α and n= (θ1⇒(θ2⇒...(θr⇒θ)...))(i)m∈T P A iffm/∈R P A,(ii)n∈T P A iffn/∈R P A.Proof.Immediately(i)by Lemma(8),(ii)by Lemma(7). Theorem10.PA is consistent;that is,there is no formulaαsuch that bothαand ¬αare theorems of PA.Proof.Let us assume m to be the G¨o del number of a proof of a formulaαof PA and n to be the G¨o del number of a proof of¬α.Then n,m∈T P A.But since n is the G¨o del number of a proof of¬αwe have also n∈R P A,accordingly n belongs to both T P A and R P A,which is impossible by Lemma(9). Theorem11.PA is complete;that is for any well formed formulaαof PA either ⊢P Aαor⊢P A¬α.Proof.Letαbe a well formed formula of PA,we can then yield by G¨o del numbering m= α .By Lemma(9)either m∈T P A or m∈R P A.Therefore either⊢P Aαor ⊢P A¬α.Let us call PF the fullfirst-order predicate calculus([5]172).Let T P F be then the set of G¨o del number of theorems of PF.Theorem12.T P F is decidable.Proof.By G¨o del Completeness Theorem,a formulaαof PA is provable in PA if and only ifαis logically valid,andαis provable in PF if and only ifαis logically valid.Hence⊢P Aαif and only if⊢P Fα.Accordingly,for n as the G¨o del number of a proof ofαin PA,n∈T P A iffn∈T P F.Hence,by theorem(6),T P F is decidable.Calling our attention to the diagonalization lemma we note that it holds for any formulaφwith only the variable v free.In other termsφcan be replaced by any formula with only one free variable.Let us suppose now that a sentenceδis a theorem of PA,i.e.⊢P Aδ.For n as the G¨o del number of a proof in PA ofδwe have⊢P A P f( δ ).But forφ(v)as∀x Rf(x,v)diagonalization lemma could have already yielded⊢PAδ⇐⇒∀x Rf(x,we have⊢PA∀x Rf(x,n,n,n,n,n,n,n,。
Time-dependent Density Functional Theory
Time-dependent Density Functional Theory Miguel A.L.Marques and E.K.U.Gross1IntroductionTime-dependent density-functional theory(TDDFT)extends the basic ideas of ground-state density-functional theory(DFT)to the treatment of excita-tions or more general time-dependent phenomena.TDDFT can be viewed an alternative formulation of time-dependent quantum mechanics but,in contrast to the normal approach that relies on wave-functions and on the many-body Schr¨o dinger equation,its basic variable is the one-body electron density,n(r,t).The advantages are clear:The many-body wave-function,a function in a3N-dimensional space(where N is the number of electrons in the system),is a very complex mathematical object,while the density is a simple function that depends solely on3variables,x,y and z.The standard way to obtain n(r,t)is with the help of afictitious system of non-interacting electrons,the Kohn-Sham system.Thefinal equations are simple to tackle nu-merically,and are routinely solved for systems with a large number of atoms. These electrons feel an effective potential,the time-dependent Kohn-Sham potential.The exact form of this potential is unknown,and has therefore to be approximated.The scheme is perfectly general,and can be applied to essentially any time-dependent situation.Two regimes can however be observed:If the time-dependent potential is weak,it is sufficient to resort to linear-response theory to study the system.In this way it is possible to calculate,e.g.optical absorp-tion spectra.It turns out that,even with the simplest approximation to the Kohn-Sham potential,spectra calculated within this framework are in very good agreement with experimental results.On the other hand,if the time-dependent potential is strong,a full solution of the Kohn-Sham equations is required.A canonical example of this regime is the treatment of atoms or molecules in strong laserfields.In this case,TDDFT is able to describe non-linear phenomena like high-harmonic generation,or multi-photon ionization.Our purpose,while writing this chapter,is to provide a pedagogical in-troduction to TDDFT1.With that in mind,we present,in section2,a quite detailed proof of the Runge-Gross theorem[5],i.e.the time-dependent generalization of the Hohenberg-Kohn theorem[6],and the corresponding2Miguel A.L.Marques and E.K.U.GrossKohn-Sham construction[7].These constitute the mathematical foundations of TDDFT.Several approximate exchange-correlation(xc)functionals are then reviewed.In section3we are concerned with linear-response theory, and with its main ingredient,the xc kernel.The calculation of excitation en-ergies is treated in the following section.After giving a brief overlook of the competing density-functional methods to calculate excitations,we present some results obtained from the full solution of the Kohn-Sham scheme,and from linear-response theory.Section5is devoted to the problem of atoms and molecules in strong laserfields.Both high-harmonic generation and ion-ization are discussed.Finally,the last section is reserved to some concluding remarks.For simplicity,we will write all formulae for spin-saturated systems.Ob-viously,spin can be easily included in all expressions when necessary.Hartree atomic units(e=¯h=m=1)will be used throughout this chapter.2Time-dependent DFT2.1PreliminariesA system of N electrons with coordinates r∂tΨ(r,t)Ψ(r,t)|2, is interpreted as the probability offinding the electrons in positions r)+ˆW(r,t).(2) Thefirst term is the kinetic energy of the electronsˆT(r2Ni=1∇2i,(3)whileˆW accounts for the Coulomb repulsion between the electronsˆW(r2N i,j=1i=j1,t).The Hamiltonian(2)is completely general and describesTime-dependent Density Functional Theory3 a wealth of physical and chemical situations,including atoms,molecules,and solids,in arbitrary time-dependent electric or magneticfields,scattering ex-periments,etc.In most of the situations dealt with in this article we will be concerned with the interaction between a laser and matter.In that case,we can write the time-dependent potential as the sum of the nuclear potential and a laserfield,ˆV TD=ˆU en+ˆV laser.The termˆU en accounts for the Coulomb attraction between the electrons and the nuclei,ˆU en (r|r i−Rν(t)|,(5)where Zνand Rνdenote the charge and position of the nucleusν,and N n stands for the total number of nuclei in the system.Note that by allowing the Rνto depend on time we can treat situations where the nuclei move along a classical path.This may be useful when studying,e.g.,scattering experiments, chemical reactions,etc.The laserfield,ˆV laser,reads,in the length gauge,ˆVlaser(r4Miguel A.L.Marques and E.K.U.Grossthe calculation of a“simple”two electron system(the Helium atom)in a laser field takes several months in a modern computer[8](see also the work on theH+2[9]molecule and the H++3molecule[10]).The effort to solve Eq.(1)growsexponentially with the number of particles,therefore rapid developments re-garding the exact solution of the Schr¨o dinger equation are not expected.In these circumstances,the natural approach of the theorist is to trans-form and approximate the basic equations to a manageable level that still retains the qualitative and(hopefully)quantitative information about the system.Several techniques have been developed throughout the years in the quantum chemistry and physics world.One such technique is TDDFT.Its goal,like always in density-functional theories,is to replace the solution of the complicated many-body Schr¨o dinger equation by the solution of the much simpler one-body Kohn-Sham equations,thereby relieving the computational burden.Thefirst step of any DFT is the proof of a Hohenberg-Kohn type theo-rem[6].In its traditional form,this theorem demonstrates that there exists a one-to-one correspondence between the external potential and the(one-body)density.With the external potential it is always possible(in princi-ple)to solve the many-body Schr¨o dinger equation to obtain the many-body wave-function.From the wave-function we can trivially obtain the density. The second implication,i.e.that the knowledge of the density is sufficient to obtain the external potential,is much harder to prove.In their seminal paper,Hohenberg and Kohn used the variational principle to obtain a proof by reductio ad absurdum.Unfortunately,their method cannot be easily gen-eralized to arbitrary DFTs.The Hohenberg-Kohn theorem is a very strong statement:From the density,a simple property of the quantum mechani-cal system,it is possible to obtain the external potential and therefore the many-body wave-function.The wave-function,by its turn,determines every observable of the system.This implies that every observable can be written as a functional of the density.Unfortunately,it is very hard to obtain the density of an interacting sys-tem.To circumvent this problem,Kohn and Sham introduced an auxiliary system of non-interacting particles[7].The dynamics of these particles are governed by a potential chosen such that the density of the Kohn-Sham system equals the density of the interacting system.This potential is local (multiplicative)in real space,but it has a highly non-local functional de-pendence on the density.In non-mathematical terms this means that the potential at the point r can depend on the density of all other points(e.g. through gradients,or through integral operators like the Hartree potential). As we are now dealing with non-interacting particles,the Kohn-Sham equa-tions are quite simple to solve numerically.However,the complexities of the many-body system are still present in the so-called exchange-correlation(xc) functional that needs to be approximated in any application of the theory.Time-dependent Density Functional Theory5 2.2The Runge-Gross theoremIn this section,we will present a detailed proof of the Runge-Gross theorem[5], the time-dependent extension of the ordinary Hohenberg-Kohn theorem[6]. There are several“technical”differences between a time-dependent and a static quantum-mechanical problem that one should keep in mind while try-ing to prove the Runge-Gross theorem.In static quantum mechanics,the ground-state of the system can be determined through the minimization of the total energy functionalE[Φ]= Φ|ˆH|Φ .(7) In time-dependent systems,there is no variational principle on the basis of the total energy for it is not a conserved quantity.There exists,however,a quantity analogous to the energy,the quantum mechanical actionA[Φ]= t1t0dt Φ(t)|i∂2If the two potentials differ solely by a time-dependent function,they will produce wave-functions which are equal up to a purely time-dependent phase.This phase6Miguel A.L.Marques and E.K.U.Grossdensity,n(r,t),i.e.v(r,t)=v (r,t)+c(t)⇒ρ(r,t)=ρ (r,t).(9) This statement immediately implies the one-to-one correspondence between the potential and the density.In the following we will utilize primes to dis-tinguish the quantities of the systems with external potentials v and v .Due to technical reasons that will become evident during the course of the proof, we will have to restrict ourselves to external potentials that are Taylor ex-pandable with respect to the time coordinate around the initial time t0v(r,t)=∞k=0c k(r)(t−t0)k,(10)with the expansion coefficientsc k(r)=1dt kv(r,t) t=t0.(11)We furthermore define the functionu k(r)=∂k2i ∇ˆψ†(r) ˆψ(r)−ˆψ†(r) ∇ˆψ(r) .(15) We now use the quantum-mechanical equation of motion,which is valid for any operator,ˆO(t),i d∂tˆO(t)+ ˆO(t),ˆH(t) |Ψ(t) ,(16)Time-dependent Density Functional Theory7 to write the equation of motion for the current density in the primed and unprimed systemsdij (r,t)= Ψ (t)| ˆj(r),ˆH (t) |Ψ (t) .(18)dtAs we start from afixed initial many-body state,at t0the wave-functions, the densities,and the current densities have to be equal in the primed and unprimed systems|Ψ(t0) =|Ψ (t0) ≡|Ψ0 (19)n(r,t0)=n (r,t0)≡n0(r)(20)j(r,t0)=j (r,t0)≡j0(r).(21) If we now take the difference between the equations of motion(17)and(18) we obtain,when t=t0,didt k+1 j(r,t)−j (r,t) t=t0=n0(r)∇u k(r).(23) The right-hand side of Eq.(23)differs from zero,which again implies that j(r,t)=j (r,t)for t>t0.In a second step we prove that j=j implies n=n .To achieve that purpose we will make use of the continuity equation∂[n(r,t)−n (r,t)]=−∇· j(r,t)−j (r,t) .(25)∂t8Miguel A.L.Marques and E.K.U.GrossAs before,we would like an expression involving the k th time derivative of the external potential.We therefore take the(k+1)st time-derivative of the previous equation to obtain(at t=t0)∂k+2∂t k+1 j(r,t)−j (r,t) t=t0=−∇·[n0(r)∇u k(r)].(26) In the last step we made use of Eq.(23).By the hypothesis(13)we have u k(r)=const.hence it is clear that if∇·[n0(r)∇u k(r)]=0,(27) then n=n ,from which follows the Runge-Gross theorem.To show that Eq.(27)is indeed fulfilled,we will use the versatile technique of demonstra-tion by reductio ad absurdum.Let us assume that∇·[n0(r)∇u k(r)]=0with u k(r)=const.,and look at the integrald3r n0(r)[∇u k(r)]2=− d3r u k(r)∇·[n0(r)∇u k(r)](28)+ S n0(r)u k(r)∇u k(r)·d S.This equality was obtained with the help of Green’s theorem.Thefirst term on the right-hand side is zero by assumption,while the second term vanishes if the density and the function u k(r)decay in a“reasonable”manner when r→∞.This situation is always true forfinite systems.We further notice that the integrand n0(r)[∇u k(r)]2is always positive.These diverse conditions can only be satisfied if either the density n0or∇u k(r)vanish identically. Thefirst possibility is obviously ruled out,while the second contradicts our initial assumption that u k(r)is not a constant.This concludes the proof of the Runge-Gross theorem.2.3Time-dependent Kohn-Sham equationsAs mentioned in section2.1,the Runge-Gross theorem asserts that all observ-ables can be calculated with the knowledge of the one-body density.Nothing is however stated on how to calculate that valuable quantity.To circumvent the cumbersome task of solving the interacting Schr¨o dinger equation,Kohn and Sham had the idea of utilizing an auxiliary system of non-interacting (Kohn-Sham)electrons,subject to an external local potential,v KS[7].This potential is unique,by virtue of the Runge-Gross theorem applied to the non-interacting system,and is chosen such that the density of the Kohn-Sham electrons is the same as the density of the original interacting system.In the time-dependent case,these Kohn-Sham electrons obey the time-dependentTime-dependent Density Functional Theory9 Schr¨o dinger equationi ∂2+v KS(r,t) ϕi(r,t).(29)The density of the interacting system can be obtained from the time-dependentKohn-Sham orbitalsn(r,t)=occi|ϕi(r,t)|2.(30)Eq.(29),having the form of a one-particle equation,is fairly easy to solve numerically.We stress,however,that the Kohn-Sham equation is not a mean-field approximation:If we knew the exact Kohn-Sham potential,v KS,we would obtain from Eq.(29)the exact Kohn-Sham orbitals,and from these the correct density of the system.The Kohn-Sham potential is conventionally separated in the following wayv KS(r,t)=v ext(r,t)+v Hartree(r,t)+v xc(r,t).(31) Thefirst term is again the external potential.The Hartree potential accounts for the classical electrostatic interaction between the electronsv Hartree(r,t)= d3r n(r,t)δn(r,τ) n(r,t),(33) whereτstands for the Keldish pseudo-time.Inevitably,the exact expression of v xc as a functional of the density is unknown.At this point we are obliged to perform an approximation.It is im-portant to stress that this is the only fundamental approximation in TDDFT. In contrast to stationary-state DFT,where very good xc functionals exist, approximations to v xc(r,t)are still in their infancy.Thefirst and simplest of these is the adiabatic local density approximation(ALDA),reminiscent of the ubiquitous LDA.More recently,several other functionals were proposed,from which we mention the time-dependent exact-exchange(EXX)functional[13], and the attempt by Dobson,B¨u nner,and Gross[14]to construct an xc func-tional with memory.In the following section we will introduce the above mentioned functionals.10Miguel A.L.Marques and E.K.U.Gross2.4xc functionalsAdiabatic approximations There is a very simple procedure that allows the use of the plethora of existing xc functionals for ground-state DFT in the time-dependent theory.Let us assume that˜v xc[n]is an approximation to the ground-state xc density functional.We can write an adiabatic time-dependent xc potential asv adiabatic xc (r,t)=˜v xc[n](r)|n=n(t).(34)I.e.we employ the same functional form but evaluated at each time with the density n(r,t).The functional thus constructed is obviously local in time. This is,of course,a quite dramatic approximation.The functional˜v xc[n]is a ground-state property,so we expect the adiabatic approximation to work only in cases where the temporal dependence is small,i.e.,when our time-dependent system is locally close to equilibrium.Certainly this is not the case if we are studying the interaction of strong laser pulses with matter.By inserting the LDA functional in Eq.(34)we obtain the so-called adi-abatic local density approximation(ALDA)v ALDA xc (r,t)=v HEGxc(n) n=n(r,t).(35)The ALDA assumes that the xc potential at the point r,and time t is equal to the xc potential of a(static)homogeneous-electron gas(HEG)of density n(r,t).Naturally,the ALDA retains all problems already present in the LDA. Of these,we would like to emphasize the erroneous asymptotic behavior of the LDA xc potential:For neutralfinite systems,the exact xc potential decays as−1/r,whereas the LDA xc potential falls offexponentially.Note that most of the generalized-gradient approximations(GGAs),or even the newest meta-GGAs have asymptotic behaviors similar to the LDA.This problem gains particular relevance when calculating ionization yields(the ionization potential calculated with the ALDA is always too small),or in situations where the electrons are pushed to regions far away from the nuclei(e.g.,by a strong laser)and feel the incorrect tail of the potential.Despite this problem,the ALDA yields remarkably good excitation ener-gies(see sections4.2and4.3)and is probably the most used xc functional in TDDFT.Time-dependent optimized effective potential Unfortunately,when one is trying to write v xc as explicit functionals of the density,one encoun-ters some difficulties.As an alternative,the so-called orbital-dependent xc functionals were introduced several years ago.These functionals are written explicitly in terms of the Kohn-Sham orbitals,albeit remaining implicit den-sity functionals by virtue of the Runge-Gross theorem.A typical member of this family is the exact-exchange(EXX)functional.The EXX action is ob-tained by expanding A xc in powers of e2(where e is the electronic charge),Time-dependent Density Functional Theory11 and retaining the lowest order term,the exchange term.It is given by the Fock integralA EXX x=−1|r−r |.(36) From such an action functional,one seeks to determine the local Kohn-Sham potential through a series of chain rules for functional derivatives.The pro-cedure is called the optimized effective potential(OEP)or the optimized potential method(OPM)for historical reasons[15,16].The derivation of the time-dependent version of the OEP equations is very similar to the ground-state case.Due to space limitations we will not present the derivation in this article.The interested reader is advised to consult the original paper[13],one of the more recent publications[17,18],or the chapter by E.Engel contained in this volume.Thefinal form of the OEP equation that determines the EXX potential is0=occj t1−∞dt d3r [v x(r ,t )−u x j(r ,t )](37)×ϕj(r,t)ϕ∗j(r ,t )G R(r t,r t )+c.c.The kernel,G R,is defined byi G R(r t,r t )=∞k=1ϕ∗k(r,t)ϕk(r ,t )θ(t−t ),(38)and can be identified with the retarded Green’s function of the system.More-over,the expression for u x is essentially the functional derivative of the xc action in relation to the Kohn-Sham wave-functionsu x j(r,t)=1δϕj(r,t).(39)Note that the xc potential is still a local potential,albeit being obtained through the solution of an extremely non-local and non-linear integral equa-tion.In reality,the solution of Eq.(37)poses a very difficult numerical prob-lem.Fortunately,by performing an approximationfirst proposed by Krieger, Li,and Iafrate(KLI)it is possible to simplify the whole procedure,and ob-tain an semi-analytic solution of Eq.(37)[19].The KLI approximation turns out to be a very good approximation to the EXX potential.Note that both the EXX and the KLI potential have the correct−1/r asymptotic behavior for neutralfinite systems.A functional with memory There is a very common procedure for the construction of approximate xc functionals in ordinary DFT.It starts with12Miguel A.L.Marques and E.K.U.Grossthe derivation of exact properties of v xc,deemed important by physical ar-guments.Then an analytical expression for the functional is proposed,such that it satisfies those rigorous constraints.We will use this recipe to generate a time-dependent xc potential which is non-local in time,i.e.that includes the“memory”from previous times[14].A very important condition comes from Galilean invariance.Let us look at a system from the point of view of a moving reference frame whose origin is given by x(t).The density seen from this moving frame is simply the density of the reference frame,but shifted by x(t)n (r,t)=n(r−x(t),t).(40) Galilean invariance then implies[20]v xc[n ](r,t)=v xc[n](r−x(t),t).(41) It is obvious that potentials that are both local in space and in time,like the ALDA,trivially fulfill this requirement.However,when one tries to deduce an xc potential which is non-local in time,onefinds condition(41)quite difficult to satisfy.Another rigorous constraint follows from Ehrenfest’s theorem which re-lates the acceleration to the gradient of the external potentiald2dt2 d3r r n(r,t)=− d3r n(r,t)∇v ext(r).(43)In the same way we can write Ehrenfest’s theorem for the Kohn-Sham system d2Time-dependent Density Functional Theory13 i.e.the total xc force of the system is zero.This condition reflects Newton’s third law:The xc effects are only due to internal forces,the Coulomb inter-action among the electrons,and should not give rise to any net force on the system.A functional that takes into account these exact constraints can be con-structed[14].The condition(46)is simply ensured by the expression1F xc(r,t)=R(t |r,t)=j(R,t )∂tdt Πxc(n(R,t ),t−t ).(50)n(r,t)∇Finally,an expression for v xc can be obtained by direct integration of F xc (see[14]for details).2.5Numerical considerationsAs mentioned before,the solution of the time-dependent Kohn-Sham equa-tions is an initial value problem.At t=t0the system is in some initial state described by the Kohn-Sham orbitalsϕi(r,t0).In most cases the initial state will be the ground state of the system(i.e.,ϕi(r,t0)will be the solution of the ground-state Kohn-Sham equations).The main task of the computational physicist is then to propagate this initial state until somefinal time,t f.14Miguel A.L.Marques and E.K.U.GrossThe time-dependent Kohn-Sham equations can be rewritten in the inte-gral formϕi(r,t f)=ˆU(t f,t0)ϕi(r,t0),(51) where the time-evolution operator,ˆU,is defined byˆU(t ,t)=ˆT exp −i t t dτˆH KS(τ) .(52)Note thatˆH KS is explicitly time-dependent due to the Hartree and xc po-tentials.It is therefore important to retain the time-ordering propagator,ˆT, in the definition of the operatorˆU.The exponential in expression(52)is clearly too complex to be applied directly,and needs to be approximated in some suitable manner.To reduce the error in the propagation from t0 to t f,this large interval is usually split into smaller sub-intervals of length ∆t.The wave-functions are then propagated from t0→t0+∆t,then from t0+∆t→t0+2∆t and so on.The simplest approximation to(56)is a direct expansion of the exponen-tial in a power series of∆tˆU(t+∆t,t)≈kl=0 −iˆH(t+∆t/2)∆t lTime-dependent Density Functional Theory15 i)Obtain an estimate of the Kohn-Sham wave-functions at time t+∆t by propagating from time t using a“low quality”formula forˆU(t+∆t,t).The expression(53)expanded to third or forth order is well suited for this purpose. ii)With these wave-functions construct an approximation toˆH(t+∆t)and toˆU(t+∆t/2,t+∆t).iii)Apply Eq.(55).This procedure leads to a very stable propagation.The split-operator method In afirst step we neglect the time-ordering in Eq.(52),and approximate the integral in the exponent by a trapezoidal rule ˆU(t+∆t,t)≈exp −iˆH KS(t)∆t =exp −i(ˆT+ˆV KS)∆t .(56) We note that the operators exp −iˆV KS∆t and exp −iˆT∆t are diagonal respectively in real and Fourier spaces,and therefore trivial to apply in those spaces.It is possible to decompose the exponential(56)into a form involving only these two operators.The two lowest order decompositions are exp −i(ˆT+ˆV KS)∆t =exp −iˆT∆t exp −iˆV KS∆t +O(∆t2)(57) andexp −i(ˆT+ˆV KS)∆t =exp −iˆT∆t2+O(∆t3).(58) For example,to apply the splitting(58)toϕ(r,t)we start by Fourier trans-forming the wave-function to Fourier space.We then apply exp −iˆT∆t16Miguel A.L.Marques and E.K.U.GrossInstead perturbation theory may prove sufficient to determine the behavior of the system.We will focus on the linear change of the density,that allows us to calculate,e.g.,the optical absorption spectrum.Let us assume that for t<t0the time-dependent potential v TD is zero–i.e.the system is subject only to the nuclear potential,v(0)–and furthermore that the system is in its ground-state with ground-state density n(0).At t0 we turn on the perturbation,v(1),so that the total external potential now consists of v ext=v(0)+v(1).Clearly v(1)will induce a change in the density. If the perturbing potential is sufficiently well-behaved(like almost always in physics),we can expand the density in a perturbative seriesn(r,t)=n(0)(r)+n(1)(r,t)+n(2)(r,t)+ (60)where n(1)is the component of n(r,t)that depends linearly on v(1),n(2) depends quadratically,etc.As the perturbation is weak,we will only be con-cerned with the linear term,n(1).In frequency space it readsn(1)(r,ω)= d3r χ(r,r ,ω)v(1)(r ,ω).(61)The quantityχis the linear density-density response function of the sys-tem.In other branches of physics it has other names,e.g.,in the context of many-body perturbation theory it is called the reducible polarization func-tion.Unfortunately,the evaluation ofχthrough perturbation theory is a very demanding task.We can,however,make use of TDDFT to simplify this process.We recall that in the time-dependent Kohn-Sham framework,the density of the interacting system of electrons is obtained from afictitious system of non-interacting electrons.Clearly,we can also calculate the linear change of density using the Kohn-Sham systemn(1)(r,ω)= d3r χKS(r,r ,ω)v(1)KS(r ,ω).(62)Note that the response function that enters Eq.(62),χKS,is the density re-sponse function of a system of non-interacting electrons and is,consequently, much easier to calculate than the full interactingχ.In terms of the unper-turbed stationary Kohn-Sham orbitals it readsχKS(r,r ,ω)=limη→0+∞jk(f k−f j)ϕj(r)ϕ∗j(r )ϕk(r )ϕ∗k(r)Time-dependent Density Functional Theory17 v(1)KS.This latter quantity can be calculated explicitly from the definition of the Kohn-Sham potentialv(1)KS(r,t)=v(1)(r,t)+v(1)Hartree(r,t)+v(1)xc(r,t).(64) The variation of the external potential is simply v(1),while the change in the Hartree potential isv(1)(r,t)= d3r n(1)(r ,t)Hartreen(1)(r ,t ).(66)δn(r ,t )It is useful to introduce the exchange-correlation kernel,f xc,defined byδv xc(r,t)f xc(r t,r t )=n(1)(r ,ω).|x−r |+f xc(x,r ,ω)From Eq.(61)and Eq.(68)trivially follows the relationχ(r,r ,ω)=χKS(r,r ,ω)+(69) d3x d3x χ(r,x,ω) 118Miguel A.L.Marques and E.K.U.Gross3.2The xc kernelAs we have seen in the previous section,the main ingredient in linear response theory is the xc kernel.f xc,as expected,is a very complex quantity that includes–or,in other words,hides–all non-trivial many-body effects.Many approximate xc kernels have been proposed in the literature over the past years.The most ancient,and certainly the simplest is the ALDA kernelf ALDA xc (r t,r t )=δ(r−r )δ(t−t )f HEGxc(n) n=n(r,t),(70)wheref HEG xc (n)=dn(r,t)[u x k(r,t)+c.c].(72)Using the definition(67)and after some algebra we arrive at thefinal form of the PGG kernelf PGG x (r t,r t )=−δ(t−t )1|r−r || occ kϕk(r)ϕ∗k(r )|2dn2 n HEG xc(n) ≡f0(n),(74)Time-dependent Density Functional Theory19where HEGxc ,the xc energy per particle of the homogeneous electron gas,isknown exactly from Monte-Carlo calculations[23].Also the infinite frequency limit can be written as a simple expressionlim q→0f HEGxc(q,ω=∞)=−43dn2/3 +6n1dnHEG xc(n)πf HEGxc(q,ω)πf HEGxc(q,ω)−f HEGxc(q,∞)15ω3/2.(79)The real part can be obtained with the help of the Kramers-Kronig relationslim ω→∞ f HEGxc(q=0,ω)=f∞(n)+23π(1+β(n)ω2)520Miguel A.L.Marques and E.K.U.GrossFig.1.Real and imaginary part of the parametrization for f HEGxc.Figure reproduced from Ref.[25].The coefficientsαandβare functions of the density,and can be determined uniquely by the zero and high frequency limits.A simple calculation yieldsα(n)=−A[f∞(n)−f0(n)]53,(83) where A,B>0and independent of n.Once again,by applying the Kramers-Kronig relations we can obtain the corresponding real part of f HEGxcf HEGxc (q=0,ω)=f∞+2√π√√2Π 1−r√2Π 1+r√1+βω2and E andΠare the elliptic integrals of second andthird kind.In Fig.1we plot the real and imaginary part of f HEGxc for twodifferent densities(r s=2and r s=4,where r s is the Wigner-Seitz radius, 1/n=4πr3s/3).The ALDA corresponds to approximating these curves by their zero frequency value.For very low frequencies,the ALDA is naturally a good approximation,but at higher frequencies it completely fails to reproducethe behavior of f HEGxc .To understand how the ALDA can yield such good excitation energies, albeit exhibiting such a mediocre frequency dependence,we will look at a spe-cific example,the process of photo-absorption by an atom.At low excitation frequencies,we expect the ALDA to work.As we increase the laser frequency, we start exciting deeper levels,promoting electrons from the inner shells of the atom to unoccupied states.The atomic density increases monotonically as we approach the nucleus.f xc corresponding to that larger density(lower。
The chords' problem
The chords’problemAlain Daurat∗,Yan G´e rard†&Maurice Nivat‡January26,2000AbstractThe chords’problem is a variant of an old problem of computa-tional geometry:given a set of points of n,one can easily build themultiset of the distances between the points of the set but the con-verse construction is known for a longtime as difficult.The problemthat we are going to investigate is also a converse construction withthe difference that it no more the one of the distances multisets butthe one of the chords’multisets.In dimension1,the old distances’problem and the chords’problem coincide with each other whereasin other dimensions,the chords’multisets contain more informationson the sets than their distances’multisets.This paper provides,indimension1,two different algorithms to reconstruct the set of pointsaccording to their chords’multiset.Thefirst one is given for its effec-tiveness in spite of an uncertain complexity whereas the second one isthefirst polynomial algorithm solving the chords’problem.At least,we will explain how to transform a chords’problem in dimension ninto an equivalent chords’problem in dimension1.∗daurat@llaic.u-clermont1.fr,Laboratoire de Logique et d’Informatique de Cler-mont1(LLAIC1),IUT,D´e partement d’Informatique,Ensemble Universitaire des C´e zeaux, B.P.86,F-63172Aubi`e re Cedex†gerard@llaic.u-clermont1.fr,Laboratoire de Logique et d’Informatique de Cler-mont1(LLAIC1),IUT,D´e partement d’Informatique,Ensemble Universitaire des C´e zeaux, B.P.86,F-63172Aubi`e re Cedex‡Maurice.Nivat@liafa.jussieu.fr,Laboratoire d’Informatique,Algorithmique, Fondements et Applications.(LIAFA),Universit´e Denis Diderot,Case7014-2,place Jussieu F-75251Paris Cedex0512 Keywords:chords’multiset,symmetrical polynomials,Minkowski’s sum1IntroductionThe chords’problem is close to the old problem of computational geometry which among others has aroused the curiosity of Paul Erd¨o s and which consists in recog-nizing the distances’multisets.The variant which interests us does not necessitate any distance and could be formulated in any group.We have not the ambition to solve the question in a so larger framework and then,we will content ourself with working withfinite subsets of n.A rigorous formulation of the chords’problem will necessitate the introduction of some classical tools used in particular in the domain of convex geometry.After the complete presentation of the chords’prob-lem and of its relations with the polynomials,we provide two algorithms to solve it in dimension1.These are both new versions of algorithms previously presented in [1]and whose we have improved the complexity.After the resolution of the chords’problem in dimension1,we will explain how a chords’problems in dimension n can be projected in dimension1so that it could be solved by one or the other of the previous algorithms.This kind of reduction is quite unusual because generally speaking,the problems in dimension n are more as complicated as in dimension1. It is however not the case for the chords’problem and we will see by using the same tools that it is neither the one of the factorization of polynomials in[X i]1≤i≤n. 2The chordsBefore giving a sense to the notion of”chord”,let us introduce a few classical definitions of mathematics.We begin with the term multiset.Definition2.1.−A multiset is a set where some elements can occur many times.Example.−M={−4,−4,−4,3,6,6,9}is a multiset of.Definition2.2.−The multiplicity of an element in a multiset is its number of occurences.Example.−The multiplicity of−4in M is3because−4occurs3times in this multiset.The multiplicity of−2in M is0because−2does not occur in M and the multiplicity of9is1.Now,we are going to introduce several operators which act on the sets or the multisets but before doing it,let us recall that we will only work withfinite sets3 andfinite multisets.It is also essential to notice that these operators can be defined in the two frameworks,the one of the sets and the one of the multisets.In both of them,the definitions are the same and then,each time,we will give only one which will be valuable in both frameworks.Thefirst operator that we can define is the symmetry:Definition2.3.−Let A be a set or a multiset,its symmetric−A is defined by−A={−a|a∈A}.Example.−The symmetric set of S={−3,5,9}is−S={3,−5,−9}and the symmetric multiset of M is−M={4,4,4,−3,−6,−6,−9}.Now,let us introduce the Minkowski’s sum:Definition2.4.−Let A and B be two sets or two multisets of n,the Minkowski’s sum of A and B is defined by A+B={a+b|a∈A and b∈B}.Remark.−In the framework of the sets,the Minkowski’s sum of two sets provides a set while in the framework of the multisets,the Minkowski’s sum of two multisets provides a multiset.It is important to see that one can also sum two sets in the framework of the multisets.Example.−In the framework of the sets,{1,3,5}+{7,9}={8,10,12,14}whereas in the framework of the multisets,we have{1,3,5}+{7,9}={8,10,10,12,12,14} and{1,1,2}+{−3,−3}={−2,−2,−2,−2,−1,−1}.Properties.−The Minkowski’s sum is associative and commutative.−The symmetry and the union are distributive with the Minkowski’s sum:we have(A∪B)+C=(A+C)∪(B+C)and−(A+B)=(−A)+(−B).−We can also notice that a translation of a set or a multiset is nothing else than its Minkowski’s sum with a singleset.The operator that we are going to use most often in this paper is the following:Definition2.5.−Let A and B be two set or multisets of n,an element of the form b−a where a∈A and b∈B is called a chord from A to B.Then,the set or multiset of the chords from A to B is defined byC(A,B)={b−a|a∈A and b∈B}.4 Examples.−We have in the framework of the sets C({0,4},{−3,2,6})={−3,2,6,−7,2}and in the framework of the multisets C({1,1,2},{1,4})={0,0,3,3,−1,2}. Remark.−The difference between b and a has a geometric sens:the chords’set or multiset C(A,B)is the set or the multiset of the vectors going from A to B.In this paper,it is not exactly the operator C(.,.)which interests us but the one which takes a set A(and no multiset)and provides the multiset C(A,A)where C(.,.)is the operator acting in the framework of the multisets.In order to reduce the number of notations,we will call it the chord’s multiset of A and denote it C(A).Example.−let A be the subset{−1,0,2,4}of,its chord’s multiset C(A)is {−1+1,−1−0,−1−2,−1−4,0+1,0−0,0−2,0−4,2+1,2−0,2−2,2−4,4+1,4−0,4−2,4−4}={−5,−4,−3,−2,−2,−1,0,0,0,0,1,2,2,3,4,5}.The operator C(.)takes a set and provides a multiset.Given a multiset,the chord’s problem consists is knowing wether it is an image of C(.)and if it is,in computing one of its antecedant.In other words,is it a chords’multiset?and if it is one,of which set of points?Properties.−Translating a set or taking its symmetric does not modify its chords’multiset.−The chords’multisets are symmetric with respect to the origin and the square of the multiplicity of0is always equal to the sum of all the multiplicities.−With the previous notations of the symmetry and of Minkowski’s sum,the chords’multiset can be defined by C(A)=A+(−A)in the framework of the multisets.Remarks.−The chords’multiset C(A)is the multiset of the vectors going from A to A.−The chords’problem has also a sense withfinite susbsets of n but in this framework,it can always be reduced to a problem in p(by using an isomorphism between the additive group generated by the chords and p).−By using convolution products,the chords’multiset and Minkowski’s sum can also be defined for infinite subsets of n.In this framework,these are some classical tools of convex geometry:the chords’multiset is also known as the difference body, the chords’problem is called the covariogram problem and for the convex sets apart from symmetry and translations,the operator which provides the difference5 body is injective.This let us think that apart from symmetry and translations, the operator C(.)could be injective for the convex sets of n.In fact,several counter-examples prove that it is false.3A new pyramid algorithmIn this part,we provide an efficient algorithm in order to solve the chord’s problem in dimension n=1.Then let B be a multiset of which verifies the two simple properties of the chords’multisets(it is symmetric with respect to the origin and the square of the multiplicity of0is equal to the sum of all the multiplicities). The question is to know whether or not it is a chords’multiset and if it is,then we would like to know a set of points solution.Two sets translated one from the other have the same chords’multiset and then we can assume that the smallest positive element of each solution is0.By denoting l the largest element of B,we can even assume that each solution is a subset of {0,...,l}.Now,let A be any subset of{0,...,l}.For all i∈{0,...,l},we can code the existence of the point i in the set A with a variable a i equal to1if i belongs to A and to0otherwise.The multiplicity of the chord i(where i∈{0,...,l})and of the chord−i in the multiset C(A)is equal to the sum a0a i+a1a i+1+......+ a j a i+j+......+a l−i a l.By denoting b i the multiplicity of i and−i in the symmetric multiset B,we have C(A)=B if and only ifa0a l=b la0a l−1+a1a l=b l−1a0a l−2+a1a l−1+a2a l=b l−2 ............................................a0a i+a1a i+1+......+a j a i+j+......+a l−i a l=b i .......................................................................................a0a1+a1a2+...................+a j a j+1+....................+a l−1a l=b1a0a0+a1a1+.................................+a j.a j+..........................+a l.a l=b0Then we can transform the chords’problems in dimension1in systems of equa-tions,where(b0,b1,···,b j,···,b l)is the given and where(a0,a1,···,a i,···a l),sup-posed in{0,1}l+1,is unknown.A classical pyramidal algorithm can be used to solve these systems:you solve the first equation,then the second one,then the third.....Sometimes,you have more than one solution for solving an equation.In that case you need to make a choice, which will sometimes lead to a general solution and sometimes not(then you have6 to make a different choice and start again).Zhang proved that this algorithm is exponential[2].Our algorithm follows the same main principle,but with some improvements.We use an idea of Elias Tahhan Bittar which consists in postponing some choices until we have better exploited the system.Performing this algorithm,we transform the initial system.The general form of the equations during the process isk∈K a k+ (m,m )∈M a m.a m =dwhere K is a multiset of indices(an index can not occur more than two times),M a subset of{0,···,l}2and d a possibly negative integer.Among all the equations of the system,we distinguishe three special types:•I.Case d<0or d>card(K)+card(M).Those equations have no solution, and as soon as we detect such one,we can be sure that the choices we have done were bad.•II.(a)case d>card(K)+card(M).This equation imposes a k=1,a m=1,a m =1for all k∈K and(m,m )∈M.(b)case d=0.This equation imposes a k=0for all k∈K.•III.Case card(K)=2,card(M)=0,d=1.The form of these equations is a k+a k =1.This last type of equation is quite simple and some other equations where the sum a k+a k appears can become simplified.A new pyramid algorithm can be the following:As in the classical algorithm,we solve thefirst equation,then the second one,then the third....and sometimes,we have to make some choices.The new idea is that between the solvation of two following equations,we use a recursive process:•We read all the system.•If we meet an equation of the form I,then the system has no solution.•If we meet an equation of the form II,then we have some new informations about the solutions,we substitute in the system the new values that we know and we obtain a new system.•If we meet an equation of the form III,then we try to simplify the other equations.7•If we have transformed the system then we restart the process.So we obtain a new pyramid algorithm,which differs from the old classical one by a more complete analysis of the equations.The examples of Zhang,which prove that the classical pyramid algorithm is exponential do not run anymore.Is this new algorithm still exponential?Probably(even if it is not proved for the moment),but we can observe in practical that it is efficient.4Relations between multisets and polynomials Now,we are going to consider the relations between the multisets and the poly-nomials in order to interpret the chords’problem in terms of polynomials.The fundamental relation which interests us concerns the multisets of n and the poly-nomials of n variables with coefficients in.One can even say that these poly-nomials and these multisets are a lonely thing,seen in two different ways.Letfor instance P(X)= d i=1a i X i be any polynomial of one variable with all its coefficients a i in.We can also write it P(X)= i∈P X i where P is the mul-tiset,where for all i∈,the multiplicity of i is exactly a i.We have,in this way,a natural one to one map between the polynomials P(X)with coefficients in and thefinite multisets P of.There exists also the same correspondance between the polynomials P(X i)1≤i≤n of n variables with coefficients in and the finite multisets P of n.We can also notice that the sets of n correspond to the polynomials of n variables whose coefficients belong to{0,1}.By going from one way of thinking to the other,the addition of the polynomials corresponds to the union of the multisets and the product of the polynomials corresponds,in the framework of multisets,to the Minkowski’s sum.Let us explain shortly this last point:LetP(X1,X2,···X n)= (α1,α2,···αn)∈P Xα11.Xα22.···.Xαn nandQ(X1,X2,···X n)= (β1,β2,···βn)∈Q Xβ11.Xβ22.···.Xβn nbe two polynomials of n variables X1,X2,...X n with coefficients in and re-spectively associated with the multisets P and Q of n.The product of the polynomials P(X1,X2,···X n).Q(X1,X2,···X n)is equal to(α1,α2,···αn)∈P and(β1,β2,···βn)∈Q Xα1+β11.Xα2+β22.···.Xαn+βnn8 namelyXγ11.Xγ22.···.Xγn n.(γ1,γ2,···γn)∈P+QRemark.−The product of the two polynomials corresponds to the Minkowski’s sum of the two associated multisets because these are both some convolutions’products.Now we are going to use this correspondance in order to give a formulation of the chords’problem in dimension1in terms of polynomials:Let B be a multiset of which is symmetric with respect to the origin and for which the square of the multiplicity of0is equal to the sum of all the multiplicities.The chord’s problem is the following:Is B a chords’multiset?and if it is,of which set of points?As we have already explained for the pyramid algorithm,by denoting l the largest element of B,we can assume that each solution is included in{0,...,l}.The points0and l necessarily belong to each solution because otherwise,l could not be one of their chord.We remind that C(A)=A+(−A)and then,we can say that the solutions are the subsets A of{0,...,l},containing0and l and verifyingA+(−A)=B.(1) Now,we are going to translate the sets and the multisets of this equality so that they would be all included in.We have noticed that the Minkowski’s sum of a set with a singleset is nothing else than a translation.Then by adding{l}to each side of the previous equality,we obtain the equivalent equality A+(−A)+{l}=B+{l}. The Minkowski’s sum is commutative and associative and it follows thatA+({l}+(−A))=B+{l}.(2) The sets A,{l}+(−A)and the multiset B+{l}are all included in and then one can associate them respectively with the polynomials A(X),SA(X)which have no other coefficients than some0and1,and with the polynomial B(X).By using the correspondance that we have described previously,the equality(2)is equivalent toA(X).SA(X)=B(X).(3) We have chosen the notation SA(X)for the polynomial associated with{l}+(−A) because by construction,this polynomial is the symmetric of the polynomial A(X). Let us remind to the reader with two exemples how is defined this symmetry S of polynomials:if for instance,P(X)=2+3X+5X3then SP(X)=5+3X2+2X39 and if P(X)=4X+5X2then SP(X)=5X+4X2.The symmetry of the polynomials has several properties,for instance towards irreducibility,but we will recall and use them later.At this step,we have showed the following theorem that one can attribute to Rosenblatt-Seymour:Theorem4.1.−The multiset B of whose smallest element is denoted−l is a chords’multiset if and only if there exists a polynomial A(X)whose coefficients belong to{0,1}and which verifiesA(X).SA(X)=B(X)(3) where B(X)is the polynomial associated with the multiset B+{l}of and where S denotes the symmetry of polynomials.Everything is not told in the theorem and it is better to add some details:the multiset B can be supposed symmetric because otherwise,there can not exist any solution and it has the consequence that the polynomial B(X)is also symmetric. The degree of B(X)is2l,the degree of A(X)and of its symmetric is l.The coefficients of degree0and l in A(X)are1and it follows that the coefficients of degree0and2l in B(X)should also be1because otherwise there can neither exist any solution.The theorem4.1provides a formulation of the chords’problem in terms of poly-nomials and now,we are going to make the most of it in order to provide a new algorithm to solve the chords’problem in dimension1.5A new version of the Rosenblatt-Seymour algo-rithmThe chords’problem can be formulated in terms of polynomials:given a sym-metric multiset B,one constructs the symmetric polynomial B(X)of degree2l with a constant coefficient different from0and the problem is to compute the set of the polynomials A(X)whose coefficients belong to{0,1}and which verify A(X).SA(X)=B(X).According to the theorem4.1,the polynomials A(X)solu-tions correspond to the sets of points A⊂{0,...,l}whose chords’multiset is B. Notations.−S still represents the symmetry of the polynomials.We introduce the set E of the polynomials P(X)of[X]which verify P(X).SP(X)=B(X).We denote also E{0,1}the subset of E containing the polynomials whose coefficients belong to{0,1}and E{0,−1}the subset of E containing the polynomials whose coefficients belong to{0,1}.10 Remark.−We can notice that if a polynomial P(X)belongs to E,then it is also the case for−P(X).It follows that P(X)∈E{0,1}if and only if−P(X)∈E{0,−1}.With these notations,the chords’problem consits in computing E{0,1}and ac-cording to the previous remarks,one can consider that it is equivalent to compute E{0,1}∪E{0,−1}.In fact,we have introduced the sets E and E{0,1}∪E{0,−1}for two main reasons:-Thefirst one is that E is not difficult to compute,and that will be the subject of the part5.1.-The second reason is that according to the lemma5.1coming in part5.2,the set E{0,1}∪E{0,−1}that we consider as the solutions of the chords’problem,is either equal to E or wether empty.It is then possible to know this subset of E without having to examine all the polynomials of E.-As conclusion,we will see in part5.3,that it provides an algorithm to compute E{0,1}∪E{0,−1}and then solve the chords’problem.5.1Computation of EThe computation of E uses the properties of the symmetry of the polynomials. Properties of the symmetry of the polynomials.−The main property is that the symmetry is distributive towards the polynomials’product:for all polynomials P and Q in[X],we have SP.SQ=S(P.Q).The distributivity of the symme-try is also true in the other rings of polynomials but we do not need it there. Now,let Q(X)be any polynomial of[X].A consequence of the distributivity is that a polynomial Q is irreducible if and only if its symmetric SQ is irreducible. It follows thatΠi∈I Qαi i is the factorization in the lowest terms of Q in[X]if and only ifΠi∈I SQαi i is the one of SQ.One can deduce from it that if Q is symmetric(Q=SQ)then its factorization in its lowest terms is of the form Q=(Πi∈I Qαi i.SQαi i).(Πj∈J Qβj j)where the indices i∈I are used for the non-symmetric irreducible factors and the indices j∈J for the symmetric factors. This last property provides a characterization of the polynomials in E: Theorem5.2.−We denote B=(Πi∈I Bαi i.SBαi i).(Πj∈J Bβj j)the factorization of the symmetric polynomial B in its lowest terms in[X],where the indices i∈I are used for the non-symmetric irreducible factors and the indices j∈J for the symmetric factors.If there exists an odd exponentβj then E is empty andotherwise E is composed of the polynomials P=(Πi∈I Bγi i.SBδi i).(Πj∈J Bβj/2j )withsome exponentsγi∈andδi∈verifyingγi+δi=αi.11 This theorem gives a description of E according to the factorization of B(X)in its lowest terms.5.2Relations between E and its subset E{O,1}∪E{O,−1}This part contains a lemma that we have already mentionned by saying that E{0,1}∪E{0,−1}is either equal to E or wether empty.This lemma comes from [1]where it is given under a different form and used differently.On the other hand,the proof that we provide is exactly the one which is given by Skiena, Smith and Lemke in[1].Lemma5.1.−Only two cases are possible:E0,1=∅or E=E0,1∪E0,−1. Proof.Let us remind that the degree of the polynomial B(X)is2l and then that all the polynomials P in E are of degree l.The constant coefficient of the polynomials in E can not be null because they verify P(0).SP(0)=B(0)which is by construction different from0.We suppose that the set E0,1is not empty and we take anyone of its elements A(X)= l i=1a i X i.For all i∈{0,...,l},the coefficient a i is either1wether0.In other words,all the coefficients verify a2i=a i and we will use it in the following. Now,we take any element P(X)= l i=1p i X i of E and we are going to prove that it belongs to E0,1∪E0,−1.As a0and p0are not null,we have SA(X)= l i=1a l−i X i and SP(X)= l i=1p l−i X i. Since A(X)and P(X)belong to E,we have A(X).SA(X)=P(X).SP(X)=B(X) and it implies two equalities:for x=1,we obtain( l i=0a i)2=( l i=0p i)2or namelyl i=0a i=±l i=0p i.(4) and by equality of the two coefficients of degree n,we obtainl i=0(a2i)=l i=0(p2i).(5)First case.−We suppose l i=0a i=+ l i=0p i.(4+) The coefficients a i are only some0and some1and then we have l i=0a i= l i=0(a2i).By combining this last equality with(4+)and(5),we obtain that l i=0p i= l i=0(p2i)namely li=0(p2i−p i)=0.(6+)12 As for all i the numbers p i are integer,the values p2i−p i are all positive and according to(6+),their sum is null.It implies that p2i−p i=0for all i∈[0,l]. The two solutions of the equation x2−x=0are0and1,and we conclude that all the coefficients p i are in{0,1}or in other words that P(X)belongs to E0,1. Second case.−We suppose l i=0a i=− l i=0p i.(4−) Then the coefficients p i=−p i verify(4+)and(5).According to thefirst case,it follows that for all i in[0,l]we have p i∈{0,1}and that proves that P(X)belongs to E0,−1.2 5.3Description of an algorithm computing E{0,1}∪E{0,−1}Given a symmetric multiset B,we construct the symmetric polynomial B(X)of degree2l with a constant coefficient different from0and which is associated with B+{l}.Now,we are going to give an algorithm in polynomial time in order to compute E{0,1}∪E{0,−1}.The polynomials A(X)of this set correspond to the sets of points A included in{0,...,l}and whose chords’multiset is B.Remark.−In the algorithm,we can assume that the constant coefficient of B(X) is1because otherwise we know that there does not exist any solution.This will allow us to have a better theoritical complexity.First step.−We factorize the symmetric polynomial B(X)in its lowest terms in [X]by using the LLL-algorithm.In the general case,this factorization takes a pseudo-polynomial time but as we have assumed that the constant coefficient is1, it takes a polynomial time[3].According to the part5.1,the factorization of the symmetric polynomial B in[X]is of the form B=(Πi∈I Bαi i.SBαi i).(Πj∈J Bβj j), where the indices i∈I are used for the non-symmetric irreducible factors and the indices j∈J for the symmetric factors.Second step.−If there exists an odd exponentβj then E{0,1}∪E{0,−1}is empty. There does not exist any solution and we stop.Last step.−The exponentsβj are all even and then,we compute the polynomialP=(Πi∈I Bαi i).(Πj∈J Bβj/2j )which belongs to E.If all the coefficients of P are in{0,1}or if they are all in{0,−1}then E{0,1}∪E{0,−1}is not empty and according to the lemma5.1,it implies E=E{0,1}∪E{0,−1}.Otherwise the lemma ensures that E{0,1}∪E{0,−1}is empty and then that there does not exist any solution. At the end of the algorithm,wether we know that there are not any solution either we know a polynomial of E{0,1}∪E{0,−1}and in that case,we can obtain13all the solutions with the formula of the elements of E given in theorem 5.1.The compexity of this algorithm is polynomial.It is proved in [1]that the number of solutions of a chords’problem is less than a polynomial boundary.This property is important to increase the complexity of the algorithm which consists in computing all the elements of E before seeing if one of them belongs to E 0,1,because it shows that this classical version of the Rosenblatt-Seymour algorithm is pseudo-polynomial (the new version that we have exposed is polynomial).Now that we have an efficient algorithm and a polynomial one in order to solve the chords’problem in dimension 1,let us investigate the problem in any dimension.6Transformation of the chords’problem by a mor-phismAlthough we have not given any example in another dimension than 1,the def-initions of the operators acting on the sets or multisets were in any dimension.Example .−Let A be the set {(0,3);(1,1);(2,1);(3,1)}drawn fig 1.s s s s --01234Figure 1.−The subset A of 2.The chords’multiset of A is C (A )={(0,3)−(0,3);(1,1)−(0,3);(2,1)−(0,3);(3,1)−(0,3);(0,3)−(1,1);(1,1)−(1,1);(2,1)−(1,1)...........}and we obtain C (A )={(−3,2);(−2,2);(−1,2);(−2,0);(−1,0);(−1,0);(0,0);(0,0);(0,0);(0,0);(1,0);(1,0);(2,0);(1,−2);(2,−2);(3,−2)}(fig 2)14s 4s 2s 2s 1s 1s 1s 1s 1s 1s 1s 1-----4-3-2-101234Figure 2.−The chords’multiset C (A )with the multiplicity of each one of its points.The general aim of this part is to develop a technical in order to transform a chords’problem in dimension n into an equivalent chords’problem in dimension1.This technical exceeds the single framework of the chords and we are going to present it for any operator K defined by symmetries and Minkowski’s sums.6.1Introduction of a general operator KLet K be an operator acting on the sets or multisets and defined by combining some symmetries with some Minkowski’s sums.As with the Minkowski’s sum or the symmetry,we do not precise if we are in the framework of the sets or in the one of the multisets because in each one of both,the properties are the same.The operator K could be the Minkowski’s sum itself,the symmetry itself,the chords’operator or almost any other operator of this kind.We just suppose that each set or multiset given as argument appears exactly one time in the expression of K .It leaves out for instance the operators DONALD (A,B,D,E )=A −D −E or C (A )=A −A .Example .−The operator K could be the one which takes four sets or multisets A ,B ,D ,E ,and associates with them K (A,B,D,E )=A +B −D +E .From now until the end,we suppose that K is an operator of this kind and we denote k the number of its arguments.Remarks .−We can also define the action of the operator K on the points of n .For the example which is above,we have K ({a },{b },{d },{e })={a +b −d +e }where a ,b ,d and e are supposed in n and then it is natural to define the action of K on the points by K (a,b,d,e )=a +b −d +e .−For any indice i ∈[1,k ],we have K (A 1,A 2,···,A i ∪A i ,···A k )=K (A 1,A 2,···。
$N=2$ and $N=4$ SUSY Yang-Mills action on $M^4times (Z_2oplus Z_2)$ non-commutative geometr
a rXiv:h ep-th/9411158v122N ov1994ASITP-94-61November,1994.N =2and N =4SUSY Yang-Mills action on M 4×(Z 2⊕Z 2)non-commutative geometry Bin Chen 1Hong-Bo Teng 2Ke Wu 3Institute of Theoretical Physics,Academia Sinica,P.O.Box 2735,Beijing 100080,China.Abstract We show that the N =2and N =4SUSY Yang-Mills action can be reformulated in the sense of non-commutative geometry on M 4×(Z 2⊕Z 2)in a rather simple way.In this way thescalars or pseudoscalars are viewed as gauge fields along two directions in the space of one-forms on Z 2⊕Z 2.1IntroductionSince A.Connes introduced his non-commutative geometry into particle physics[1,2],a successful geometrical interpretation of the Higgs mechanism and Yukawa coupling has been acquired.In this interpretation,the Higgsfields are regarded as gaugefields on the discrete gauge group. The bosonic part of the action is just the pure YM action containing the gaugefields on both continuous and discrete gauge group,and the Yukawa coupling is viewed as a kind of gauge interactions of fermions.At the same time,applying non-commutative geometry to SUSY theories has encountered many difficulties.A natural way is to introduce a non-commutative space which is the product of the superspace and a set of discrete points,similar to those which have been done in non-SUSY theories.However,it proved that such an extension of superspace is rather difficult to accomplish.In[3],A.H.Chamseddine gave an alternative way in which the supersymmetry theories in their component forms were considered.He showed that N=2and N=4SUSY Yang-Mills actions could be derived as action functionals for non-commutative spaces,and in some cases the coupling of N=1and N=2super Yang-Mills to N=1and N=2matter could also be reformulated.This paper is thefirst one in which the non-commutative geometry is successfully applied to SUSY theories.Intrigued by A.H.Chamseddine’s work,we show the N=2and N=4SUSY Yang-Mills actions can be derived with non-commutative geometry on M4×(Z2⊕Z2)in a rather simple way.We use the differential calculus on discrete group developed by A.Sitarz[4].With a specific case of differential algebra on Z2⊕Z2,we take the scalar components of the super Yang-Mills field as gaugefields on discrete symmetry group.In N=2case,the scalar and pseudoscalar fields are set to two directions of the space of one-forms.In case of N=4,the complex scalar fields which belong to6of SU(4)are regarded as components of the connection one-form.First in section2we show the specific case of the differential algebra on Z2⊕Z2.Then in section3we derive the N=2and N=4super Yang-Mills Lagrangian with this algebra.Finally we end with conclusions.2Differential Calculus on Z2⊕Z2In this section,we briefly describe the differential calculus on Z2⊕Z2and introduce a specific case of this algebra.For a detailed description of differential calculus on discrete group,we refer to[4].Let’s write the four elements of Z2⊕Z2as(e1,e2),(r1,e2),(e1,r2),(r1,r2).And the group multiplication is(g1,g2)(h1,h2)=(g1h1,g2h2).(1)Let A be the algebra of complex valued functions on Z2⊕Z2.The derivative on A is defined as∂g f=f−R g f g∈Z2⊕Z2,f∈A(2)with R g f(h)=f(hg).We will write∂i and R i for convenience where i=1,2,3refers to (r1,e2),(e1,r2),(r1,r2)respectively.{∂i,i=1,2,3}forms the basis of F,the space of left invariant vectorfields over A.One canfind that the following relations hold∂1∂2=∂1+∂2−∂3∂2∂3=∂2+∂3−∂1(3)∂3∂1=∂3+∂1−∂2∂1∂1=2∂1∂2∂2=2∂2(4)∂3∂3=2∂3∂1∂2=∂2∂1∂1∂3=∂3∂1(5)∂2∂3=∂3∂2.The Haar integral on Z2⊕Z2is defined asZ2⊕Z2f=1Next we introduce the space of one-forms,Ω1,which is the dual space of F.Haven chosen the basis of F,we automatically have the dual basis ofΩ1,{χi,i=1,2,3}.It is defined withχi(∂j)=δi j i,j=1,2,3.(7) The definition of higher forms is natural,Ωn is taken to be tensor product of n copies ofΩ1,,Ωn=Ω1⊗···⊗Ω1n copiesandΩ0=A.AndΩ= ⊕Ωn is the tensor algebra on Z2⊕Z2.As usual,the external derivative satisfies the graded Leibniz rule and is nilpotentd(ab)=d(a)b+(−1)dega a(db)a,b∈Ω(8)d2=0and for f∈Ω0=Ad f=∂1fχ1+∂2fχ2+∂3fχ3.(9)From(8),(9),onefindsχi f=(R i f)χi i=1,2,3f∈A(10)anddχ1=−χ1⊗χ2−χ1⊗χ3+χ2⊗χ3−2χ1⊗χ1−χ2⊗χ1−χ3⊗χ1+χ3⊗χ2dχ2=−χ2⊗χ3−χ2⊗χ1+χ3⊗χ1−2χ2⊗χ2−χ3⊗χ2−χ1⊗χ2+χ1⊗χ3(11)dχ3=−χ3⊗χ1−χ3⊗χ2+χ1⊗χ2−2χ3⊗χ3−χ1⊗χ3−χ2⊗χ3+χ2⊗χ1We also need the involution¯on our differential algebra,which agrees with the complex conjugation on A and(graded)commutes with d,i.e.d(da.For one-forms,then we getdχi=0i=1,2,3.(14) It is a specific case of the above algebra.Obviously the postulation induces an antisymmetric tensor algebraΛwhich is a subalgebra ofΩ.In this subalgebra,we denote the product of forms with∧.And we will use this subalgebra to derive the N=2and N=4SUSY Yang-Mills action in next section.3N=2and N=4super Yang-Mills actionLet’sfirst consider the N=2case.The N=2super Yang-Mills Lagrangian is given byL=T r(−12DµSDµS+12[S,P]2)(15)whereψis the Dirac4−spinor which is the combination of two2−spinors,S is the scalar and P is the pseudoscalar.Allfields are valued in the adjoint representation of the gauge group,i.e.,f=f a T a f=Aµ,S,P,ψ(16)where T a is the generator of gauge group.AndFµν=∂µAν−∂νAµ+i[Aµ,Aν]DµS=∂µS+i[Aµ,S]DµP=∂µP+i[Aµ,P]Dµψ=∂µψ+i[Aµ,ψ].(17)From a simple observation,we see that it is possible to choose the generalized connection one-form on M4×(Z2⊕Z2)A(x,g)=iAµ(x,g)dxµ−iS(x,g)χ1−iγ5P(x,g)χ2g∈Z2⊕Z2.(18)And we setAµ(x,g)=Aµ(x);S(x,g)=S(x);P(x,g)=P(x);g∈Z2⊕Z2.(19)And later in fermionic sector we will also letψ(x,g)=ψ(x).Since all quantities take the same values on different points of Z2⊕Z2,we will ignore the variable g.Please note in this assignment the scalar and pseudoscalar are assigned to two directions of the connection one-form,and we have manifestly set the component inχ3direction of A to zero.We will see it is sufficient for our construction.With(13),(14),(18),(19)the curvature two form is easily foundF=dA(x)+A(x)∧A(x)=i(∂µAν+iAµAν)dxµ∧dxν−i(∂µS+i[Aµ,S])dxµ∧χ1−iγ5(∂µP+i[Aµ,P])dxµ∧χ2−γ5[S,P]χ1∧χ2=iF(h)>(21) we get exactly the bosonic sector of the LagrangianL B=T r(1dxρ∧dxσ>+DµS(DνS)∗<dxµ∧χ1,dxν∧χ2>+[S,P][S,P]∗<χ1∧χ2,4FµνFµν+12DµP DµP+1dxρ∧dxσ>=<dxµ∧dxν,dxσ∧dxρ>=gµσgνρ<dxµ∧χ1,2gµν<dxµ∧χ2,2gµν<χ1∧χ2,2.(23)As to the fermionic sector of the Lagrangian,we haveL F= Z2⊕Z2T r(i¯ψ[γµDµ+D1+D2+D3,ψ])=T r(i¯ψγµDµψ+¯ψ[S+γ5P,ψ])(24)where[D1,ψ]=∂1ψ−i[SR1,ψ]=−i[S,ψ][D2,ψ]=∂2ψ−i[γ5P R2,ψ]=−i[γ5P,ψ][D3,ψ]=∂3ψ=0.(25) So the N=2super Yang-Mills Lagrangian is reformulated.We next consider N=4case,the Lagrangian isL=T r[−12DµM ij DµM ij+iλi[M ij,λj]+i¯λi[M ij,¯λj]+12ǫijkl M kl=M ij,and transforms as6of SU(4), andλi is the2−spinor transforming as4of SU(4)whereas¯λi transforming as¯4.So L is SU(4) invariant.In order to write the spinor in four component form,we introduce Majorana spinorsλi= λαi¯λ˙αi ;¯λi= λαi,¯λi˙α (27) andφij= M ij M ijI ij= δj iδi j (28)α=1,2and˙α=˙1,˙2are spinor indices.So the Lagrangian can be written asL=T r[−12¯λiγµDµλi+18[φij,φkl][φ†ij,φ†kl]].(29)here the trace also takes on the2×2matrix in whichfields in two2−component form are arranged into4−component form.We set the connection one-form on M4×(Z2⊕Z2)A(x,g)=iAµ(x,g)I ij dxµ+φij(x,g)χ1+φij(x,g)χ2g∈Z2⊕Z2.(30)Again we will let allfields take the same values on different points of Z2⊕Z2,so we will ignore the variable g,and as in the N=2case,we let the component inχ3direction be zero.Then we haveF=dA(x)+A(x)∧A(x)=i2 Z2⊕Z2T r<F(h),2T r(1dxρ∧dxσ>+Dµφij(Dνφij)∗<dxµ∧χ1,dxν∧χ2>+[φij,φkl][φij,φkl]∗<χ1∧χ2,8FµνFµνI2+18[φij,φkl][φ†ij,φ†kl])(32)here again in order to give appropriate normalization constants,we have chosen the metric <dxµ∧dxν,dxν∧χ1>=<dxµ∧χ1,−χ1∧dxν>=1dxν∧χ2>=<dxµ∧χ2,−χ2∧dxν>=1χ1∧χ2>=<χ1∧χ2,χ2∧χ1>=12 Z2⊕Z2T r(i¯λi[γµ(Dµ)I ij+(D1)ij+(D2)ij+(D3)ij,λj])=T r(i4ConclusionsWe show that the N=2and N=4super Yang-Mills Lagrangian can be reformulated on M4×(Z2⊕Z2)non-commutative geometry.We use the differential calculus on discrete group developed by A.Sitarz and regard the scalar or pseudoscalarfields as connection one-forms on the discrete symmetry group.This reformulation is different from that of A.H.Chamseddine and seems much simpler and clearer.References[1]A.Connes:Non-commutative Geometry English translation ofGeometrie Non-commutative,IHES Paris,Interedition.[2]A.Connes and J.Lott:Nucl.Phys.(Proc.Suppl.)B18,44(1990).[3]A.H.Chamseddine:Phys.Lett.B332,(1994)349-357.[4]A.Sitarz:To appear in J.Geo.Phys.[5]A.H Chamseddine,G Felder and J.Frohlich:Phys.Lett.296B(1993)109.[6]R.Coquereaux,G.Esposito-Farese and G.V aillant:Nucl.Phys.B353689(1991).。
Threshold Perspectives on Meson Production
a rXiv:n ucl-e x /31111v112N ov23Threshold Perspectives on Meson Production M.Wolke 1The Svedberg Laboratory,Uppsala University,Box 533,75121Uppsala,Sweden ∗Abstract.Studies of meson production in nucleon–nucleon collisions at threshold are characterised by few degrees of freedom in a configuration of well defined initial and final states with a transition governed by short range dynamics.Effects from low–energy scattering in the exit channel are inherent to the data and probe the interaction in baryon–meson and meson–meson systems otherwise difficult to access.From dedicated experiments at the present generation of cooler rings precise data are becoming available on differential and eventually spin observables allowing detailed comparisons between complementary final states.To discuss physics implications of generic and specific properties,recent experimental results on meson production in proton–proton scattering obtained at CELSIUS and COSY serve as a guideline.INTRODUCTION High precision data from the present generation of cooler rings,IUCF,CELSIUS,and COSY ,have contributed significantly over the last decade to our present knowledge and understanding of threshold meson production (for a recent review see [1]).Due to the high momentum transfers required to create a meson or mesonic system in production experiments close to threshold the short range part of the interaction is probed.In nucleon–nucleon scattering,for mesons in the mass range up to 1GeV /c 2distances from 0.53fm (π0)down to less than 0.2fm (φ)are involved.At such short distances it is a priori not clear,whether the relevant degrees of freedom are still baryons and mesons,or rather quarks and gluons.As there is no well defined boundary,one goalof the threshold production approach is to explore the limits in momentum transfer for a consistent description using hadronic meson exchange models.Within this framework,questions concerning both the underlying meson exchange contributions and especially the role of intermediate baryon resonances have to be answered.Another aspect which enriches the field of study arises from the low relative centre–of–mass velocities of the ejectiles:Effects of low energy scattering are inherent to the observables due to strong final state interactions (FSI)within the baryon–baryon,baryon–meson,and meson–meson subsystems.In case of short–lived particles,low energy scattering potentials are otherwise difficult or impossible to study directly.DYNAMICS OF THE TWO PION SYSTEMInγandπinduced double pion production on the nucleon the excitation of the N∗(1440) P11resonance followed by its decay to the Nσchannel,i.e.N∗(1440)→p(ππ)I=l=0, is found to contribute non–negligibly close to threshold[2,3,4].Nucleon–nucleon scattering should provide complementary information,eventually on theππdecay mode of the N∗(1440),which plays an important part in understanding the basic structure of the second excited state of the nucleon[5,6,7].Exclusive CELSIUS data from the PROMICE/W ASA setup on the reactions pp→ppπ+π−,pp→ppπ0π0and pp→pnπ+π0[8,9,10]are well described by model cal-culations[11]:For theπ+π−andπ0π0channels,the reaction preferentially proceeds close to threshold via heavy meson exchange and excitation of the N∗(1440)Roper resonance,with a subsequent pure s–wave decay to the Nσchannel1.While nonres-onant contributions are expected to be small,resonant processes with Roper excita-tion and decay via an intermediate∆(pp→pN∗→p∆π→ppππ)and∆∆excitation (pp→∆∆→pπpπ)are strongly momentum dependent and vanish directly at thresh-old.Double∆excitation,which is expected to dominate at higher excess energies be-yond Q=250MeV[11]involves higher angular momenta and consequently strongly anisotropic proton and pion angular distributions.On the other hand,the Roper decay amplitude via an intermediate∆depends predominantly on a term symmetric in the pion momenta(eq.(1)),leading to the p(π+π−)I=l=0channel and an interference with the direct Nσdecay.Experimentally,for the reaction pp→ppπ+π−at excess energies of Q=64.4MeV and Q=75MeV angular distributions give evidence for only s–waves in thefinal state,in line with a dominating pp→pN∗→pp(π+π−)I=l=0process,with the initial inelastic pp collision governed by heavy meson(σ,ρ)exchange.Roper excitation is disclosed in the pπ+π−invariant mass distribution(Fig.1a),where the data are shifted towards higher invariant masses compared to phase space in agreement with resonance excitation in the low energy tail of the N∗(1440).Compared with Monte Carlo simulations including both heavy meson exchange for N∗excitation,and pp S–wave final state interaction,but only the direct decay N∗→p(π+π−)I=l=0(dotted lines),the production process involves additional dynamics,which is apparent from discrepancies especially in observables depending on theπmomentum correlation k1· k2,i.e.π+π−invariant mass Mππ(Fig.1b)and opening angleδππ=1For the pnπ+π0final state,this reaction mechanism is trivially forbidden by isospin conservation.An underestimation of the total cross section data[9]by the model predictions[11]might be explained by the neglect of effects from the pnfinal state interaction in the calculation[12].M π+π- [MeV/c 2]d σ/d M π+π- [n b /(M e V /c 2)]-π+πδcos d σ/d c o s δπ+π- [n b ]a)M p π+π- [MeV/c 2]d σ/d M p π+π- [n b /(M e V /c 2)]b)c)FIGURE 1.Differential cross sections for the reaction pp →pp π+π−at an excess energy of Q =75MeV.Experimental data (solid circles)for invariant mass distributions of the (p π+π−)–(a)and(π+π−)–subsystems (b),and the π+π−opening angle (c)are compared to pure phase space (shaded areas)and Monte Carlo simulations for direct decays N ∗→N σ(dotted lines),decays via an intermediate ∆resonance N ∗→∆π→N σ(dashed lines)and an interference of the two decay routes (solid lines)according to eq.(1).Figures are taken from [10].allows to determine the ratio of partial decay widths R (M N ∗)=ΓN ∗→∆π→N ππ/ΓN ∗→N σat average masses <M N ∗>corresponding to excess energies Q =64.4MeV and Q =75MeV relative to the π+π−threshold.The numerical results,R (1264)=0.034±0.004and R (1272)=0.054±0.006,exhibit the clear dominance of the direct decay to the N σchannel in the low energy region of the Roper resonance.On the other hand they indicate the strong energy dependence of the ratio from the momentum dependence in the decay branch via an intermediate ∆,which will surpass the direct decay at higher energies [10].A model dependent extrapolation based on the validity of ansatz (1)leads to R (1440)=3.9±0.3at the nominal resonance pole in good agreement with the PDG value of 4±2[13].Within the experimental programme to determine the energy dependence of the N ∗→N ππdecay exclusive data (for details see [14])have been taken simultaneously at the CELSIUS/W ASA facility on both the pp π+π−and pp π0π0final states.In case of the π+π−system the preliminary results at an excess energy of Q =75MeV are in good agreement with the relative strength of the decay routes adjusted to an extrapolated ratio R (1440)=3.However,at slightly higher excess energy (Q =127MeV)the data might be equally well described by a value R (1440)=1,which is noticeably favoured at both excess energies by the data on π0π0production,indicating distinct underlying dynam-ics in π0π0and π+π−production.One difference becomes obvious from the isospin decomposition of the total cross section [9]:An isospin I =1amplitude in the ππsys-tem,and accordingly a p–wave admixture,is forbidden by symmetry to contribute to the neutral pion system in contrast to the charged complement.A p–wave component was neglected so far in the analysis,since the unpolarized angular distributions show no devi-ation from isotropy.However,there is evidence for small,but non–negligible analysing powers from a first exclusive measurement of π+π−production with a polarized beam at the COSY–TOF facility [14,15],suggesting higher partial waves especially in the ππsystem.At higher energies,i.e.Q =208MeV and Q =286MeV with respect to the π+π−threshold,preliminary data for both π+π−and π0π0from CELSIUS/W ASA rather fol-low phasespace than expectations based on a dominating pp →pN ∗→pp σreaction mechanism[14].At these energies,the ∆∆excitation process should influence observ-ables significantly,and,thus,a phase space behaviour becomes even more surprising,unless the ∆∆system is excited in a correlated way.THE PROTON–PROTON–ETA FINAL STATEAs a general trait in meson production in nucleon–nucleon scattering,the primary pro-duction amplitude,i.e.the underlying dynamics can be regarded as energy independent in the vicinity of threshold [16,17,18].Consequently,for s–wave production processes,the energy dependence of the total cross section is essentially given by a phase space behaviour modified by the influence of final state interactions.In Fig.2total cross sec-tion data obtained in proton–proton scattering are shown for the pseudoscalar isosinglet mesons ηand η′[19].In both cases,the energy dependence of the total cross sec-σ[n b ]10101010excess energy [MeV]110102FIGURE 2.Total cross section data for η(squares [20,21,22,23,24,25])and η′(circles [24,26,27,28,29])production in proton–proton scattering versus excess energy Q [19].In comparison,the energy dependences from a pure phase space behaviour (dotted lines,normalized arbitrarily),from phase space modified by the 1S 0proton–proton FSI including Coulomb interaction (solid lines),and from additionally including the proton–ηinteraction phenomenologically (dashed line),are shown.Meson exchange calculations for ηproduction including a P–wave component in the proton–proton system [30]are depicted by the dashed–dotted line,while the dashed–double–dotted line corresponds to the arbitrarily normalized energy dependence from a full three–body treatment of the pp ηfinal state [31](see also [32]).tion deviates significantly from phase space expectations.Including the on–shell 1S 0proton–proton FSI enhances the cross section close to threshold by more than an order of magnitude,in good agreement with data in case of η′.As expected from kinemat-ical considerations[1]the cross section for ηproduction deviates from phase space including the pp FSI at excess energies Q ≥40MeV,where the 1S 0final state is no longer dominant compared to higher partial waves.Deviations at low excess energies seem to be well accounted for by an attractive proton–ηFSI (dashed line),treated phe-nomenologically as an incoherent pairwise interaction [1,17,33].In comparison to the proton–η′(Fig.2)and proton–π0systems only the p ηinteraction is strong enough to become apparent in the energy dependence of the total cross section [34].In differen-tial observables,effects should be more pronounced in the phase space region of low proton–ηinvariant masses.However,to discern effects of proton–ηscattering from the influence of proton–proton FSI,which is stronger by two orders of magnitude,requires high statistics measurements,which have only become available recently [19,35,36]:Close to threshold,the distribution of the invariant mass of the proton–proton subsys-s pp [GeV 2/c 4]d σ/d s p p [µb /(Ge V 2/c 4)]FIGURE 3.Invariant mass squared of the (pp )–subsystem in the reaction pp →pp ηat excess energies of Q =15.5MeV (COSY–11,solid circles [19],Q =15MeV (COSY–TOF,open circles [36]and Q =16MeV (PROMICE/W ASA,open triangles [35]).The dotted and dashed lines follow a pure phase space behaviour and its modification by the phenomenological treatment of the three–body FSI as an incoherent pairwise interaction,respectively.The latter was normalized at small invariant mass values.Effects from including a P–wave admixture in the pp system are depicted by the dashed–dotted line [30],while the dashed–double–dotted line corresponds to a pure s–wave final state with a full three–body treatment [32].tem is characteristically shifted towards low invariant masses compared to phase space (dotted line in Fig.3).This low–energy enhancement is well reproduced by modifying phase space with the 1S 0pp on–shell interaction.A second enhancement at higher pp invariant masses,i.e.low energy in the p ηsystem,is not accounted for even when including additionally the proton–ηinteraction incoherently (dashed line).However,in-cluding a P–wave admixture in the pp system by considering a 1S 0→3P 0s transition in addition to the 3P 0→1S 0s threshold amplitude,excellent agreement with the ex-perimental invariant mass distribution is obtained (dashed–dotted line [30]).In return,with the P–wave strength adjusted to fit the invariant mass data,the approach fails to reproduce the energy dependence of the total cross section (Fig.2)below excess ener-gies of Q =40MeV.Preliminary calculations considering only s–waves in the final statebut using a rigorous three–body treatment of the ppηfinal state actually decrease the cross section at large values of the pp invariant mass(dashed–double–dotted lines[32]) compared to an incoherent two–body calculation within the same framework.However, close to threshold the energy dependence of the total cross section is enhanced com-pared to the phenomenological incoherent treatment and the data(Fig.2).Although part of this enhancement has to be attributed to the neglect of Coulomb repulsion in the pp system,consequently overestimating the pp invariant mass at low values,qualitatively the full three–body treatment has opposite effects compared to a P–wave admixture in the proton–proton system in view of both the total cross section as well as the pp in-variant mass distribution.In the approximate description of the total cross section by the phenomenological s–wave approach with an incoherent FSI treatment these two effects seem to cancel casually.Close to threshold,resonance excitation of the S11(1535)and subsequent decay to the pηfinal state is generally2believed to be the dominantηproduction mechanism [17,30,38,39,40,41,42,43].In this context,the issue of the actual excitation mechanism of the S11(1535)remains to be addressed.Theηangular distribution is sensitive to the underlying dynamics:A dominantρexchange favoured in[41]results in an inverted curvature of theηangular distribution compared toπandηexchanges which are inferred to give the largest contribution to resonance excitation in[42].In the latter approach the interference of the pseudoscalar exchanges in the resonance current with non–resonant nucleonic and mesonic exchange currents turns the curvature to the same angular dependence as expected forρexchange.Presently,due to the statistical errors of the available unpolarised data at an excess energy of Q≈40MeV[35,36]it is not possible to differentiate between a dominantρorπ,ηexchange,as discussed in [36].Data recently taken at the CELSIUS/W ASA facility with statistics increased by an order of magnitude compared to the available data might provide an answer in the near future[44].Spin observables,like theηanalyzing power,should even disentangle a dominantρmeson exchange and the interference ofπandηexchanges in resonance excitation with small nucleonic and mesonic currents[42],which result in identical predictions for the unpolarisedηangular distribution.First data[45]seem to favour the vector dominance model,butfinal conclusions both on the underlying reaction dynamics and the admixture of higher partial waves[30]have to await the analysis of data taken with higher statistics for the energy dependence of theηanalysing power[46].ASSOCIATED STRANGENESS PRODUCTIONIn elementary hadronic interactions with no strange valence quark in the initial state the associated strangeness production provides a powerful tool to study reaction dynamicsby introducing a“tracer”to hadronic matter.Thus,quark model concepts might even-tually be related to mesonic or baryonic degrees of freedom,with the onset of quark degrees of freedom expected for kinematical situations with large enough transverse momentum transfer.First exclusive close–to–threshold data onΛandΣ0production[47,48]obtained at the COSY–11facility showed at equal excess energies below Q=13MeV a cross section ratio ofRΛ/Σ0(Q≤13MeV)=σ(pp→pK+Λ)3For further complementary theoretical approaches see references in[1,58,59].Σ0p FSI being much weaker compared to the Λp system.However,the interpretation implies dominant S–wave production and reaction dynamics that can be regarded as energy independent.Within the present level of statistics,contributions from higher partial waves can be neither ruled out nor confirmed at higher excess energies for Σ0production.The energy dependence of the production ratio RΛ/Σ0is shown in Fig.4in comparisonwith theoretical calculations obtained within the approach of [50]assuming a destructive interference of πand K exchange and employing different choices of the microscopic hyperon nucleon model to describe the interaction in the final state [61].The resultexcess energy [MeV]4060200σ (p p → p K +Λ)σ (p p→p K +Σ)010203040FIGURE 4.Λ/Σ0production ratio in proton–proton scattering as a function of the excess energy.Data are from [48](shaded area)and [60].Calculations [61]within the Jülich meson exchange model imply a destructive interference of K and πexchange using the microscopic Nijmegen NSC89(dashed line [62])and the new Jülich model (solid line [63])for the Y N final state interaction.crucially depends on the details —especially the off–shell properties —of the hyperon–nucleon interaction employed.At the present stage both the good agreement found in[50]with the threshold enhancement (2)and for the Nijmegen model (dashed line in Fig.4)with the energy dependence of the cross section ratio should rather be regarded as accidental 4.Calculations using the new Jülich model (solid line in Fig.4)do not reproduce the tendency of the experimental data.It is suggested in [61]that neglecting the energy dependence of the elementary amplitudes and higher partial waves might no longer be justified beyond excess energies of Q =20MeV.However,once the reaction mechanism for close–to–threshold hyperon production is understood,exclusive data should provide a strong constraint on the details of hyperon–nucleon interaction models.PRESENT AND FUTUREIntermediate baryon resonances emerge as a common feature in the dynamics of the exemplary cases for threshold meson production in nucleon–nucleon scattering dis-cussed in this article.However,this does not hold in general for meson production in the1GeV/c2mass range(for a discussion onη′production see[64]).Moreover,the extent to which resonances are evident in the observables or actually govern the reaction mechanism depends on the specific channels,which differ in view of the level of present experimental and theoretical understanding.The N∗(1440)resonance dominatesπ+π−production at threshold,and exclusive data allow to extract resonance decay properties in the low–energy tail of the Roper. Dynamical differences between the different isospin configurations of theππsystem and the behaviour at higher energies remains to be understood withfirst experimental clues appearing.With three strongly interacting particles in thefinal state,a consistent description ofηproduction close to threshold requires an accurate three–body approach taking into account the possible influence of higher partial waves.High statistics differential cross sections and polarization observables coming up should straighten out both the excitation mechanism of the N∗(1535)and the admixture of higher partial waves.At present,the available experimental data on the elementary strangeness produc-tion channels give evidence for both an important role of resonances coupling to the hyperon–kaon channels and on a dominant non–resonant kaon exchange mechanism. Experiments on different isospin configurations,high statistics and spin transfer mea-surements close to threshold should disentangle the situation in future.From the cornerstone of total cross section measurements,it is apparent from the above examples to what extent our knowledge is presently enlarged by differential observables and what will be the impact of polarization experiments in future to get new perspectives in threshold meson production.ACKNOWLEDGMENTSThe author gratefully acknowledges the pleasure to work with the CELSIUS/W ASA and COSY–11collaborations,and,in particular,thanks M.Bashkanov,H.Clement,R. 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学术英语(社科)Unit3三单元原文及翻译
UNIT 3 Unemployment1. Losing a job can be the most distressing economic event in a person’s life. Most people rely on their labor earnings to maintain their standard of living, and many people get from their work not only income but also a sense of personal accomplishment.A job loss means a lower living standard in the present, anxiety about the future, and reducedself-esteem. It is not surprising, therefore, that politicians campaigning for office often speak about how their proposed policies will help create jobs.失去一份工作可能是最痛苦的经济事件在一个人的生活。
大多数人们依靠自己的劳动收入来维持他们的生活标准,许多人会从他们的工作得到的不仅是收入,还有自己的成就感。
一个失去工作意味着现在要定一个更低的生活标准,焦虑未来,并丧失自尊心。
这并不奇怪,因此,政治家竞选办公室经常谈论他们所提出的政策将帮助创造就业机会。
4.In judging how serious the problem of unemployment is, one question to consider is whether unemployment is typically a short-term or long-term condition. If unemployment is short-term, one might conclude that it is not a big problem. Workers may require a few weeks between jobs to find the openings that best suit their tastes and skills. Yet if unemployment is long-term, one might conclude that it is a serious problem. Workers unemployed for many months are more likely to suffer economic and psychological hardship.判断失业问题有多么严重时,其中一个问题就是要考虑是否失业通常是一个短期或长期的条件。
时间依赖问题
Ωn (t) ,
(5)
Ω1 (t) =
0 ′ 2.) Ω2 = −1/2[Ω1, A] so that t t1
A(t1 )dt1 ,
(6)
Ω2 (t) = 1/2
0 0
[A(t1 ), A(t2 )]dt2 dt1 ,Leabharlann (7)and so on.
3
The procedure can be written as Magnus expansion generator: ′ Ω2 = −1/2[Ω1, A] so that
Multi-product expansion, Suzuki’s method and the Magnus integrator for solving time-dependent problems
J¨ urgen Geiser and Siu A. Chin
geiser@mathematik.hu-berlin.de
4
The fourth order method is given in [5], see also the coefficients in the appendix. The convergence results are given in [17]. In the next we present the algorithms for a Hamiltonian application. Application to a Hamiltonian The algorithm is given for a Hamiltonian as: H = T (p, t) + V (q, t) For example : H = p2 /2 + V (q, t), where T (p, t) = p2 /2 and
community structure in time-dependent,multiscale,and multiplex networks
DOI: 10.1126/science.1184819, 876 (2010);328 Science , et al.Peter J. Mucha NetworksCommunity Structure in Time-Dependent, Multiscale, and MultiplexThis copy is for your personal, non-commercial use only.clicking here.colleagues, clients, or customers by , you can order high-quality copies for your If you wish to distribute this article to othershere.following the guidelines can be obtained by Permission to republish or repurpose articles or portions of articles): December 2, 2010 (this infomation is current as of The following resources related to this article are available online at/content/329/5989/277.3.full.html A correction has been published for this article at:/content/328/5980/876.full.html version of this article at:including high-resolution figures, can be found in the online Updated information and services,/content/suppl/2010/05/13/328.5980.876.DC1.html can be found at:Supporting Online Material /content/328/5980/876.full.html#related found at:can be related to this article A list of selected additional articles on the Science Web sites /content/328/5980/876.full.html#ref-list-1, 3 of which can be accessed free:cites 19 articles This article /content/328/5980/876.full.html#related-urls 1 articles hosted by HighWire Press; see:cited by This article has been/cgi/collection/comp_math Computers, Mathematicssubject collections:This article appears in the following registered trademark of AAAS.is a Science 2010 by the American Association for the Advancement of Science; all rights reserved. The title Copyright American Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005. (print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by the Science o n D e c e m b e r 2, 2010w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o mCommunity Structure inTime-Dependent,Multiscale,and Multiplex NetworksPeter J.Mucha,1,2*Thomas Richardson,1,3Kevin Macon,1Mason A.Porter,4,5Jukka-Pekka Onnela 6,7Network science is an interdisciplinary endeavor,with methods and applications drawn from across the natural,social,and information sciences.A prominent problem in network science is the algorithmic detection of tightly connected groups of nodes known as communities.We developed a generalized framework of network quality functions that allowed us to study the community structure of arbitrary multislice networks,which are combinations of individual networks coupled through links that connect each node in one network slice to itself in other slices.This framework allows studies of community structure in a general setting encompassing networks that evolve over time,have multiple types of links (multiplexity),and have multiple scales.The study of graphs,or networks,has a long tradition in fields such as sociology and mathematics,and it is now ubiquitous in academic and everyday settings.An important tool in network analysis is the detection of mesoscopic structures known as communities (or cohesive groups),which are defined intuitively as groups of nodes that are more tightly connected to each other than they are to the rest of the network (1–3).One way to quantify communities is by a quality function that compares the number of intracommunity edges to what one would expect at random.Given the network adjacency matrix A ,where the element A ij details a direct connection between nodes i and j ,one can construct a qual-ity function Q (4,5)for the partitioning of nodes into communities as Q =∑ij (A ij −P ij )d (g i ,g j ),where d (g i ,g j )=1if the community assignments g i and g j of nodes i and j are the same and 0otherwise,and P ij is the expected weight of the edge between i and j under a specified null model.The choice of null model is a crucial con-sideration in studying network community struc-ture (2).After selecting a null model appropriate to the network and application at hand,one can use a variety of computational heuristics to assign nodes to communities to optimize the quality Q (2,3).However,such null models have not been available for time-dependent networks;analyses have instead depended on ad hoc methods topiece together the structures obtained at different times (6–9)or have abandoned quality functions in favor of such alternatives as the Minimum Description Length principle (10).Although tensor decompositions (11)have been used to cluster network data with different types of connections,no quality-function method has been developed for such multiplex networks.We developed a methodology to remove these limits,generalizing the determination of commu-nity structure via quality functions to multislice networks that are defined by coupling multiple adjacency matrices (Fig.1).The connections encoded by the network slices are flexible;they can represent variations across time,variations across different types of connections,or even community detection of the same network at different scales.However,the usual procedure for establishing a quality function as a direct count of the intracommunity edge weight minus thatexpected at random fails to provide any contribu-tion from these interslice couplings.Because they are specified by common identifications of nodes across slices,interslice couplings are either present or absent by definition,so when they do fall inside communities,their contribution in the count of intra-community edges exactly cancels that expected at random.In contrast,by formulating a null model in terms of stability of communities under Laplacian dynamics,we have derived a principled generaliza-tion of community detection to multislice networks,1Carolina Center for Interdisciplinary Applied Mathematics,Department of Mathematics,University of North Carolina,Chapel Hill,NC 27599,USA.2Institute for Advanced Materials,Nanoscience and Technology,University of North Carolina,Chapel Hill,NC 27599,USA.3Operations Research,North Carolina State University,Raleigh,NC 27695,USA.4Oxford Centre for Industrial and Applied Mathematics,Mathematical Institute,University of Oxford,Oxford OX13LB,UK.5CABDyN Complexity Centre,University of Oxford,Oxford OX11HP,UK.6Department of Health Care Policy,Harvard Medical School,Boston,MA 02115,USA.7Harvard Kennedy School,Harvard University,Cambridge,MA 02138,USA.*To whom correspondence should be addressed.E-mail:mucha@1234Fig.1.Schematic of a multislice network.Four slices s ={1,2,3,4}represented by adjacencies A ijs encode intraslice connections (solid lines).Interslice con-nections (dashed lines)are encoded by C jrs ,specifying the coupling of node j to itself between slices r and s .For clarity,interslice couplings are shown for only two nodes and depict two different types of couplings:(i)coupling between neighboring slices,appropriate for ordered slices;and (ii)all-to-all interslice coupling,appropriate for categoricalslices.n o d e sresolution parameterscoupling = 0123451015202530n o d e s resolution parameterscoupling = 0.1123451015202530n o d e sresolution parameterscoupling = 1123451015202530Fig. 2.Multislice community detection of the Zachary Karate Club network (22)across multiple resolutions.Colors depict community assignments of the 34nodes (renumbered vertically to group similarly assigned nodes)in each of the 16slices (with resolution parameters g s ={0.25,0.5,…,4}),for w =0(top),w =0.1(middle),and w =1(bottom).Dashed lines bound the communities obtained using the default resolution (g =1).14MAY 2010VOL 328SCIENCE876CORRECTED 16 JULY 2010; SEE LAST PAGEo n D e c e m b e r 2, 2010w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o mwith a single parameter controlling the interslice correspondence of communities.Important to our method is the equivalence between the modularity quality function (12)[with a resolution parameter (5)]and stability of com-munities under Laplacian dynamics (13),which we have generalized to recover the null models for bipartite,directed,and signed networks (14).First,we obtained the resolution-parameter generaliza-tion of Barber ’s null model for bipartite networks (15)by requiring the independent joint probability contribution to stability in (13)to be conditional on the type of connection necessary to step between two nodes.Second,we recovered the standard null model for directed networks (16,17)(again with a resolution parameter)by generaliz-ing the Laplacian dynamics to include motion along different kinds of connections —in this case,both with and against the direction of a link.By this generalization,we similarly recovered a null model for signed networks (18).Third,we interpreted the stability under Laplacian dynamics flexibly to permit different spreading weights on the different types of links,giving multiple reso-lution parameters to recover a general null model for signed networks (19).We applied these generalizations to derive null models for multislice networks that extend the existing quality-function methodology,including an additional parameter w to control the coupling between slices.Representing each network slice s by adjacencies A ijs between nodes i and j ,with interslice couplings C jrs that connect node j in slice r to itself in slice s (Fig.1),we have restricted our attention to unipartite,undirected network slices (A ijs =A jis )and couplings (C jrs =C jsr ),but we can incorporate additional structure in the slices and couplings in the same manner as demonstrated for single-slice null models.Notating the strengths of each node individually in each slice by k js =∑i A ijs and across slices by c js =∑r C jsr ,we define the multislice strength by k js =k js +c js .The continuous-time Laplacian dynamics given byp˙is ¼∑jr ðA ijs d sr þd ij C jsr Þp jrk jr−p isð1Þrespects the intraslice nature of A ijs and the interslice couplings of C jsr .Using the steady-state probability distribution p ∗jr ¼k jr =2m ,where 2m =∑jr k jr ,we obtained the multislice null model in terms of the probability r is |jr of sampling node i in slice s conditional on whether the multislice struc-ture allows one to step from (j ,r )to (i ,s ),accounting for intra-and interslice steps separately asr is j jr p ∗jr ¼k is2m s k jr k jr d sr þC jsr c jr c jr k jr d ijk jr 2m ð2Þwhere m s =∑j k js .The second term in parentheses,which describes the conditional probability of motion between two slices,leverages the definition of the C jsr coupling.That is,the conditional probability of stepping from (j ,r )to (i ,s )along an interslice coupling is nonzero if and only if i =j ,and it is proportional to the probability C jsr /k jr of selecting the precise interslice link that connects to slice s .Subtracting this conditional joint probability from the linear (in time)approximation of the exponential describing the Laplacian dynamics,we obtained a multislice generalization of modularity (14):Q multislice ¼12m ∑ijsrhA ijs −g sk is k js 2m s d sr þd ij C jsr id ðg is ,g jr Þð3Þwhere we have used reweighting of the conditionalprobabilities,which allows a different resolution g s in each slice.We have absorbed the resolution pa-rameter for the interslice couplings into the mag-nitude of the elements of C jsr ,which,for simplicity,we presume to take binary values {0,w }indicating the absence (0)or presence (w )of interslice links.YearS e n a t o rCTMARI DENYIL IN MIWI IA KSMONDVA AL ARFL GALA MSSC KYOK WVCOID MTNMWYORAK HI Congress #ABFig.3.Multislice community detection of U.S.Senate roll call vote similarities (23)with w =0.5coupling of 110slices (i.e.,the number of 2-year Congresses from 1789to 2008)across time.(A )Colors indicate assignments to nine communities of the 1884unique senators (sorted vertically and connected across Congresses by dashed lines)in each Congress in which they appear.The dark blue and red communities correspond closely to the modern Democratic and Republican parties,respectively.Horizontal bars indicate the historical period of each community,with accompanying text enumerating nominal party affiliations of the single-slice nodes (each representing a senator in a Congress):PA,pro-administration;AA,anti-administration;F,Federalist;DR,Democratic-Republican;W,Whig;AJ,anti-Jackson;A,Adams;J,Jackson;D,Democratic;R,Republican.Vertical gray bars indicate Congresses in which three communities appeared simultaneously.(B )The same assignments according to state affiliations.SCIENCEVOL 32814MAY 2010877REPORTSo n D e c e m b e r 2, 2010w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o mCommunity detection in multislice networks can then proceed using many of the same com-putational heuristics that are currently available for single-slice networks [although,as with the stan-dard definition of modularity,one must be cautious about the resolution of communities (20)and the likelihood of complex quality landscapes that necessitate caution in interpreting results on real networks (21)].We studied examples that have multiple resolutions [Zachary Karate Club (22)],vary over time [voting similarities in the U.S.Senate (23)],or are multiplex [the “Tastes,Ties,and Time ”cohort of university students (24)].We provide additional details for each example in (14).We performed simultaneous community de-tection across multiple resolutions (scales)in the well-known Zachary Karate Club network,which encodes the friendships between 34members of a 1970s university karate club (22).Keeping the same unweighted adjacency matrix across slices (A ijs =A ij for all s ),the resolution associated with each slice is dictated by a specified sequence of g s parameters,which we chose to be the 16values g s ={0.25,0.5,0.75,…,4}.In Fig.2,we depict the community assignments obtained for cou-pling strengths w ={0,0.1,1}between each neighboring pair of the 16ordered slices.These results simultaneously probe all scales,includ-ing the partition of the Karate Club into four com-munities at the default resolution of modularity (3,25).Additionally,we identified nodes that have an especially strong tendency to break off from larger communities (e.g.,nodes 24to 29in Fig.2).We also considered roll call voting in the U.S.Senate across time,from the 1st Congress to the 110th,covering the years 1789to 2008and includ-ing 1884distinct senator IDs (26).We defined weighted connections between each pair of sen-ators by a similarity between their voting,specified independently for each 2-year Congress (23).We studied the multislice collection of these 110networks,with each individual senator coupled to himself or herself when appearing in consecutive Congresses.Multislice community detection un-covered interesting details about the continuity of individual and group voting trends over time that are not captured by the union of the 110in-dependent partitions of the separate Congresses.Figure 3depicts a partition into nine communities that we obtained using coupling w =0.5.The Congresses in which three communities appeared simultaneously are each historically noteworthy:The 4th and 5th Congresses were the first with political parties;the 10th and 11th Congresses occurred during the political drama of former Vice President Aaron Burr ’s indictment for treason;the 14th and 15th Congresses witnessed the beginning of changing group structures in the Democratic-Republican party amidst the dying Federalist party (23);the 31st Congress included the Compromise of 1850;the 37th Congress occurred during the beginning of the American Civil War;the 73rd and 74th Congresses followed the landslide 1932election (during the Great Depression);and the 85th to 88th Congresses brought the major American civil rights acts,including the congressio-nal fights over the Civil Rights Acts of 1957,1960,and 1964.Finally,we applied multislice community detection to a multiplex network of 1640college students at a northeastern American university (24),including symmetrized connections from the first wave of this data representing (i)Facebook friendships,(ii)picture friendships,(iii)roommates,and (iv)student housing-group preferences.Be-cause the different connection types are categorical,the natural interslice couplings connect an individ-ual in a slice to himself or herself in each of the other three network slices.This coupling between categorical slices thus differs from that above,which connected only neighboring (ordered)slices.Table 1indicates the numbers of communities and the percentages of individuals assigned to one,two,three,or four communities across the four types of connections for different values of w ,as a first investigation of the relative redundancy across the connection types.Our multislice framework makes it possible to study community structure in a much broader class of networks than was previously possible.Instead of detecting communities in one static network at a time,our formulation generalizing the Laplacian dynamics approach of (13)permits the simulta-neous quality-function study of community struc-ture across multiple times,multiple resolution parameter values,and multiple types of links.Weused this method to demonstrate insights in real-world networks that would have been difficult or impossible to obtain without the simultaneous consideration of multiple network slices.Although our examples included only one kind of variation at a time,our framework applies equally well to networks that have multiple such features (e.g.,time-dependent multiplex networks).We expect multislice community detection to become a powerful tool for studying such systems.References and Notes1.M.Girvan,M.E.J.Newman,Proc.Natl.Acad.Sci.U.S.A.99,7821(2002).2.M.A.Porter,J.-P.Onnela,P.J.Mucha,Not.Am.Math.Soc.56,1082(2009).3.S.Fortunato,Phys.Rep.486,75(2010).4.M.E.J.Newman,Phys.Rev.E 74,036104(2006).5.J.Reichardt,S.Bornholdt,Phys.Rev.E 74,016110(2006).6.J.Hopcroft,O.Khan,B.Kulis,B.Selman,Proc.Natl.Acad.Sci.U.S.A.101(suppl.1),5249(2004).7.T.Y.Berger-Wolf,J.Saia,in Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2006),p.523(10.1145/1150402.1150462).8.G.Palla,A.-L.Barabási,T.Vicsek,Nature 446,664(2007).9.D.J.Fenn et al .,Chaos 19,033119(2009).10.J.Sun,C.Faloutsos,S.Papadimitriou,P.S.Yu,inProceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2007),p.687(10.1145/1281192.1281266).11.T.M.Selee,T.G.Kolda,W.P.Kegelmeyer,J.D.Griffin,CSRI Summer Proceedings 2007,Technical Report SAND2007-7977,Sandia National Laboratories,Albuquerque,NM and Livermore,CA ,M.L.Parks,S.S.Collis,Eds.(2007),p.87(/CSRI/Proceedings).12.M.E.J.Newman,M.Girvan,Phys.Rev.E 69,026113(2004)mbiotte,J.C.Delvenne,M.Barahona,http://arxiv.org/abs/0812.1770(2008).14.See supporting material on Science Online.15.M.J.Barber,Phys.Rev.E 76,066102(2007).16.A.Arenas,J.Duch,A.Fernandez,S.Gomez,N.J.Phys.9,176(2007).17.E.A.Leicht,M.E.J.Newman,Phys.Rev.Lett.100,118703(2008).18.S.Gómez,P.Jensen,A.Arenas,Phys.Rev.E 80,016114(2009).19.V.A.Traag,J.Bruggeman,Phys.Rev.E 80,036115(2009).20.S.Fortunato,M.Barthélemy ,Proc.Natl.Acad.Sci.U.S.A.104,36(2007).21.B.H.Good,Y.-A.de Montjoye,A.Clauset,Phys.Rev.E81,046106(2010).22.W.W.Zachary,J.Anthropol.Res.33,452(1977).23.A.S.Waugh,L.Pei,J.H.Fowler,P.J.Mucha,M.A.Porter,/abs/0907.3509(2009).24.K.Lewis,J.Kaufman,M.Gonzalez,A.Wimmer,N.Christakis,works 30,330(2008).25.T.Richardson,P.J.Mucha,M.A.Porter,Phys.Rev.E 80,036111(2009).26.K.T.Poole,Voteview ()(2008).27.We thank N.A.Christakis,L.Meneades,and K.Lewis foraccess to and helping with the “Tastes,Ties,and Time ”data;S.Reid and A.L.Traud for help developing code;and A.Clauset,J.-C.Delvenne,S.Fortunato,M.Gould,and V.Traag for discussions.Congressional roll call data are from (26).Supported by NSF grant DMS-0645369(P.J.M.),James S.McDonnellFoundation grant 220020177(M.A.P.),and the Fulbright Program (J.-P.O.).Supporting Online Material/cgi/content/full/328/5980/876/DC1SOM Text References17November 2009;accepted 22March 201010.1126/science.1184819Table munities in the first wave of the multiplex “Tastes,Ties,and Time ”network (24),using the default resolution (g =1)in each of the four slices of data (Facebook friendships,picture friendships,roommates,and housing groups)under various couplings w across slices,which changed the number of communities and percentages of individuals assigned on a per-slice basis to one,two,three,or four communities.w Number of communitiesCommunities per individual (%)1234010360001000.112214.040.537.38.20.26619.949.125.3 5.70.34926.248.321.6 3.90.43631.847.018.4 2.80.53139.342.416.8 1.511610014MAY 2010VOL 328SCIENCE878REPORTSo n D e c e m b e r 2, 2010w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o m1 sCiEnCE erratum post date 16 july 2010 ErratumReports: “Community structure in time-dependent, multiscale, and multiplex networks” by P. J. Mucha et al . (14 May, p. 876). Equation 3 contained a typographical error that was not caught during the editing process: The δsr term should have been outside of the paren-theses within the square brackets. The correct equation, which also appears in the support-ing online material as equation 9, is as follows:See the revised supporting online material (/cgi/content/full/sci;328/5980/876/DC2), which also includes a correction to equation 11. The computations supporting the examples described in the Report were all performed with the correct for-mula for Q multislice . The authors thank Giuseppe Mangioni for pointing out the error.Post date 16 July 2010o n D e c e m b e r 2, 2010w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o mCOMMENTARY16 JULY 2010 VOL 329 SCIENCE 276LETTERSedited by Jennifer SillsLETTERS I BOOKS I POLICY FORUM I EDUCATION FORUM I PERSPECTIVESC R ED I T : ME H M E T K A R A T A Y /W I K I M E D I A C O M M O N SBrazilian Law:Full Speed in Reverse?IS IT POSSIBLE TO COMBINE MODERN TROPI-cal agriculture with environmental conserva-tion? Brazilian agriculture offers encourag-ing examples that achieve high production together with adequate environmental pro-tection (1, 2). However, these effective prac-tices may soon lose ground to the conven-tional custom of resource overexploitation and environmental degradation.A revision to the Forest Act, the main Bra-zilian environmental legislation on private land, has just been submitted to Congress, and there is a strong chance that it will be approved. The proposed revision raises seri-ous concerns in the Brazilian scientifi c com-munity, which was largely ignored during its elaboration. The new rules will benefi t sectors that depend on expanding frontiers by clear-cutting forests and savannas and will reduce mandatory restoration of native vegetation illegally cleared since 1965. If approved, CO 2 emissions may increase substantially, instead of being reduced as was recently pledged in Copenhagen. Simple species-area relation-ship analyses also pro j ect the extinction of more than 100,000 species, a massive loss that will invalidate any commitment to biodi-versity conservation. Proponents of the new law, with well-known ties to specifi c agribusi-ness groups, claim an alleged shortage of land for agricultural expansion, and accuse the current legislation of being overprotective ofFunding Should Come to Those Who WaitWE APPLAUD THE PERSPECTIVE BY T. CLUTTON-BROCK ANDB. C. Sheldon (“The Seven Ages of Pan ,” 5 March, p. 1207) on the value of long-term behavior and ecologi-cal research. We pick up where they left off: funding. Long-term research has cumulative value that far exceeds its annual rate of return. Sadly, quick empiri-cal studies trump long-term research in the reward sys-tem for academic promotion in ecology and behavior. If long-term research is to fl ourish, we must build a reward system for studies characterized by deferred gratifi ca-tion. A sea change in these values must precede attemptsto address funding.To secure the future of long-term fi eld projects, we must act on three fronts:(i) We must devise funding mechanisms for “legacy” projects deemed too valuable to falter. Whereas the National Science Foundation’s (NSF’s) National Ecological Observatory Network and Long-Term Ecological Research programs support long-term collaborative, site-based research, there is a compelling need to support the diversity of long-term investiga-tor-initiated programs. As implemented, NSF’s Long-Term Research in Environmental Biol-ogy program is a fi rst step, but has insuffi cient support to maintain many valuable projects.(ii) We must develop mechanisms to fund the establishment of new programs with long-term potential. Such potential may not be initially appreciated, but with vision and support, new systems studied over the long run will produce novel insights.(iii) Support for ecological research must be increased. We do not advocate robbing Peter (short-term research) to pay Paul (long-term research). However, we maintain that Paul has already been robbed and some balance needs to be restored.Most of us involved in long-term research have a story to share, in which time-lim-ited funding shortages took our programs to the edge of a precipice. Investigators that suc-ceed and become known for long-term research, almost by defi nition, have found a way to adapt to funding shortfalls, usually at great personal sacrifi ce. A recent case at the Los Amigos Biological Station in the Peruvian Amazon speaks to the value of funding continuity (1). During a 4-year period of programmatic support, the scientifi c productivity of the station surged, producing many valuable fi ndings and building substantial scientifi c capacity for the region. Since the funding evaporated, the station has failed to return to its former glory, at great loss to our ability to make scientifi c inroads into understanding the ecology of this area, characterized by unrivaled biodiversity.Of course, long-term programs must remain intellectually vibrant and methodologically rigorous if they are to be supported. In the end, the onus is on ecologists to convince ourselves, society, and funding agencies that long-term research has unique and irreplaceable value.RONALD R. SWAISGOOD,1* JOHN W. TERBORGH,2 DANIEL T. BLUMSTEIN 31Applied Animal Ecology, San Diego Zoo’s Institute for Conservation Research, San Diego, CA 92027, USA. 2Center for Tropi-cal Conservation, Duke University, Durham, NC 27705, USA. 3Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA.*To whom correspondence should be addressed. E-mail: rswaisgood@Reference1. N. C. A. Pitman, Trends Ecol. Evol . 25, 381 (2010).Long-term studies. Studies spanning decades have yielded insights into red deer and other species. Published by AAASo n D e c e m b e r 2, 2010w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o m SCIENCE VOL 329 16 JULY 2010277the environment in response to foreign inter-ests fronted by green nongovernmental orga-nizations. However, recent studies (3) show that, without further conversion of natural vegetation, crop production can be increased by converting suitable pastures to agriculture and intensifying livestock production on the remaining pasture. Brazil has a high poten-tial for achieving sustainable development and thereby conserving its unique biological heritage. Although opposed by the Ministry of the Environment and most scientists, the combination of traditional politicians, oppor-tunistic economic groups, and powerful land-owners may be hard to resist. The situation is delicate and serious. Under the new ForestAct, Brazil risks suffering its worst environ-mental setback in half a century, with criti-cal and irreversible consequences beyond itsborders.JEAN PAUL METZGER,1* THOMAS M. LEWINSOHN,2CARLOS A. JOLY,3 LUCIANO M. VERDADE,4 LUIZ ANTONIO MARTINELLI,5 RICARDO R. RODRIGUES 61Department of Ecology, Institute of Bioscience, University of São Paulo, 05508-900, São Paulo, SP, Brazil. 2Depart-ment of Animal Biology, State University of Campinas, Campinas, SP, Brazil. 3Department of Plant Biology, Biol-ogy Institute, State University of Campinas, Campinas, SP, Brazil. 4Center of Nuclear Energy in Agriculture, University of São Paulo, Piracicaba, Brazil. 5Program on Food Secu-rity and the Environment, Stanford University, Stanford, CA94305, USA. 6Department of Biological Sciences, “Luiz deQueiroz” College of Agriculture, University of São Paulo, Piracicaba, Brazil.*To whom correspondence should be addressed. E-mail: jpm@p.brReferences1. D. Nepstad et al., Science 326, 1350 (2009).2. C. R. Fonseca et al., Biol. Conserv. 142, 1209 (2009).3. G. Sparovek et al., Considerações sobre o Código Florestalbrasileiro (“Luiz de Queiroz” College of Agriculture, Uni-versity of São Paulo, Piracicaba, Brazil, 2010); p.br/lepac/codigo_fl orestal/Sparovek_etal_2010.pdf.Sponsors of Traumatic Brain Injury Project I’M DELIGHTED THAT SCIENCE TOOK THE TIMEto highlight the ongoing efforts of the Common Data Elements Project for research in psychological health and traumatic brain injury (“New guidelines a im to improve studies of traumatic brain injury,” G. Miller,News of the Week, 16 April, p. 297). The level of interagency collaboration that made the project possible is exactly the type of lea dership tha t America ns should expectfrom the federal government.As noted in the story, the project is co-sponsored by four federal agencies—threeof whom were mentioned. The other agency is the National Institute on Disability andRehabilitation Research (NIDRR) withinthe Department of Education. NIDRR hasleadership, resources, and subject matter experts without which this project would nothave been nearly as successful. Together, all four agencies will continue to develop rec-ommendations and support ongoing efforts to improve and refine the Common Data Elements.GEOFFREY MANLEYDepartment of Neurosurgery, Brain and Spinal Injury Cen-ter, University of California, San Francisco, CA 94110, USA. E-mail: manleyg@Warming, Photoperiods, and Tree PhenologyC. KÖRNER ANDD. BASLER (“PHENOLOGY under global warming,” Perspectives, 19 March, p. 1461) suggest that because of photoperiodic constraints, observed effects of temperature on spring life-cycle events cannot be extrapolated to future tempera-ture conditions.However, no study has demonstrated that photoperiod is more dominant than temper-ature when predicting leaf senescence (1), leafing, or flowering, even in beech—one of the species most sensitive to photoperiod (2, 3). On the contrary, the literature [e.g., (4, 5)] supports the idea that spring phenol-ogy is highly dependent on temperature dur-ing both the endodormancy phase (the period during which the plant remains dormant dueTECHNICAL COMMENT ABSTRACTS Comment on “Observational and Model Evidence for Positive Low-Level Cloud Feedback”Anthony J. Broccoli and Stephen A. KleinClement et al . (Reports, 24 July 2009, p. 460) provided observational evidence for systematic relationships between variations in marine low cloudiness and other climatic variables and found that most current-generation climate models were defi cient in reproducing such relationships. Our analysis of one of these models (GFDL CM2.1), using more com-plete model output, indicates better agreement with observations, suggesting that more detailed analysis of climate model simulations is necessary.Full text at /cgi/content/full/329/5989/277-aResponse to Comment on “Observational and Model Evidence for Positive Low-Level Cloud Feedback”Amy C. Clement, Robert Burgman, Joel R. NorrisBroccoli and Klein argue for additional diagnostics to better assess the simulation of cloud feedbacks in climate models. We agree, and here provide additional analysis of two climate models that reveals where model defi ciencies in cloud simulation in the Northeast Pacifi c may occur. Cloud diagnostics from the forthcoming Climate Model Intercomparison Project 5 should make such additional analyses possible for a large number of climate models.Full text at /cgi/content/full/329/5989/277-bCORRECTIONS AND CLARIFICATIONSNews of the Week: “Invisibility cloaks for visible light must remain tiny, theorists predict” by A. Cho (25 June, p. 1621). The size limit on a cloak for infrared or visible light was misstated. It is a few hundred micrometers, not a few micrometers.News Focus: “Putting light’s light touch to work as optics meets mechanics” by A. Cho (14 May, p. 812). In the third para-graph, “pitchfork” should have been “tuning fork.”Reports: “Community structure in time-dependent, multiscale, and multiplex networks” by P. J. Mucha et al . (14 May, p. 876). Equation 3 contained a typographical error that was not caught during the editing process: The δsr term should have been outside of the parentheses within the square brackets. The correct equation, which also appears in the support-ing online material as equation 9, is to the right. See the revised supporting online material (/cgi/content/full/sci;328/5980/876/DC2), which also includes a correction to equation 11. The computations supporting theexamples described in the Report were allperformed with the correct formula for Q multislice . The authors thank Giuseppe Mangioni for point-ing out the error.Published by AAASo n D e c e m b e r 2, 2010w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o m。
时间相依协变量Cox模型的变量选择
第10卷第6期2019年3月黑龙江科学HEILONGJIANG SCIENCEVol.10March 2019时间相依协变量Cox 模型的变量选择韦新星(河池学院数学与统计学院,广西宜州546300)摘要:结合R软件对时间相依协变量Cox 模型进行变量选择研究。
介绍了时间相依协变量Cox 模型的一般形式。
分析了时间相依协变量Cox 模型的数据来源和建模过程。
结果表明,时间相依协变量Cox 模型就是一种对Cox 模型的扩展和改进。
当数据中存在伴随时间而发生变化的变量时,时间相依协变量Cox 模型能弥补时间独立协变量Cox 模型的不足,使分析更加全面合理。
关键词:时间相依协变量;Cox 模型;变量选择中图分类号:O212.1文献标志码:A 文章编号:1674-8646(2019)06-0034-02Study on variable selection of Cox model with time dependent covariatesWEI Xin-xing(School of Mathematics and Statistics ,Hechi University ,Yizhou 546300,China )Abstract :In this paper ,the Cox model of time-dependent covariates is studied with Rsoftware.The general form of Cox model with time dependent covariates is introduced.The data sources and modeling process of Cox model with time-dependent covariates are analyzed.The results show that Cox model is an extension and improvement of Cox model.The results show that the Cox model of time-dependent covariate can make up for the deficiency of Cox model of time-independent covariate and make the analysis more comprehensive and reasonable when there are variables that change with time in the data.Key words :Time-dependent covariates ;Cox model ;Variable selection 收稿日期:2019-01-07基金项目:广西高校中青年教师基础能力提升项目(2018KY0503);河池学院教育教学改革课题(2017EB012);广西大学生创新创业训练计划项目(201810605010)作者简介:韦新星(1990-),女,硕士,河池学院数学与统计学院讲师,统计师,研究方向:应用统计。
2024-2025学年辽宁省大连市滨城高中联盟高三上学期期中考试英语试卷
2024-2025学年辽宁省大连市滨城高中联盟高三上学期期中考试英语试卷The skin is an essential part of your body and is its largest organ. As you can imagine, getting burnt can lead to very serious injuries. The first and most important step in the treatment of burns is giving first aid. CAUSES OF BURNSYou can get burnt by a variety of things: hot liquids, steam, fire, radiation, the sun, electricity, acids, or other chemicals. TYPES OF BURNSBurns are divided into three types, depending on the depth of skin damage. ● First- degree burns These affect only the top few millimetres of the skin. These burns are not serious. Examples include mild sunburn and burns caused by other minor household incidents.● Second- degree burns These go below the top layer of the skin. They are serious and take a few weeks to get better. Examples include burns caused by hot liquids.● Third- degree burns These affect every layer of the skin, and sometimes the tissue under it. Examples include burns caused by electric shocks, burning clothes, or petrol fires. These burns cause very severe internal injuries and the victim must go to the hospital at once.FIRST-AID TREATMENT1. Place burns under cool running water, especially within the first ten minutes. The cool water stops the burning process and reduces the pain and swelling.2. Dry the burnt area gently with a clean cloth.3. Remove any clothes using scissors if necessary, unless you see the fabric sticking to the burnt skin.4. Cover the burnt area with a loose clean cloth. Applying oil to the injured areas is a bad idea, as it will keep the heat in the wounds and may cause infection.5. If burns are on the face, make sure the victim can still breathe.6. If the victim is suffering from second or third- degree burns, there is an urgent need to take him/ her to the hospital at once.1. What is an example of a first- degree burn mentioned in the text?A.A slight kitchen burn. B.A burn from very hot water.C.A severe burn from a petrol fire. D.A deep tissue damage from steam.2. Why shouldn't oil be applied to burn?A.It is a poor conductor of heat.B.It can worsen the burn by trapping heat.C.It will increase pain and cause immediate scarring.D.It may lead to infection by creating a wet environment.3. Where would you expect to find the information above?A.A financial newsletter. B.A beauty and skincare guide.C.A home improvement magazine. D.A first- aid book.On a quiet afternoon, as the sunlight shone through the curtains and cast a warm glow on the attic (阁楼) floor, I started a journey through time. It was there, in the corner behind the old suitcase, that I made a fascinating discovery—a shoebox filled with old letters.These letters, tied together with a faded ribbon, were a collection of conversations between my grandmother and her friends from past time. The dusty smell of aged paper and ink filled the air, transporting me to a time when communication was a deliberate and heartfelt act.In an age where a simple text or email can convey our thoughts, these letters served as a deeply touching reminder of the depth and meaning that can be found in the written word. They were more than just messages; they were pieces of a life, snapshots of a time, and most importantly, they were a bridge between the past and the present, between my grandmother's generation and my own.With the letters safely back in their resting place, I made a quiet promise to myself— to pick up pen and paper more often, to write not just messages, but little pieces of history that future generations might one day cherish.In a world racing towards the future, it's the old letters that remind us to slow down, to appreciate the moment, and to write our own stories with care. And perhaps, one day, someone will find my letters and experience the same joy of discovery, the same sense of connection across the years. For now, the attic holds not just boxes of old letters but also the promise of stories yet to be told.4. What does the author consider the letters to be?A.Simple messages from the past. B.Bridges between different generations.C.Outdated communication methods. D.Unimportant things of past time.5. What personal resolution does the author make after reflecting on the letters?A.To clean the attic of unnecessary items.B.To digitize all family letters for preservation.C.To learn more about the history of the family.D.To write more frequently to maintain connections.6. Which sentence may the author agree according to the passage?A.Every family has a story to tell.B.The pen is stronger than the sword.C.Old letters carry voices from the past.D.The hand that writes the history makes the history.7. Which of the following is a suitable title for the text?A.Treasure in Letters. B.A Journey Through the Attic.C.Digital Distraction. D.The Power of Pen and Ink.Research into whether the human voice helps plants isn't conclusive. Even so, there are convincing reasons that chatting up your potted friends is good for them—and you.Plants don't interrupt when you' re speaking. They don't argue or ask difficult questions. And regardless of whether they're actually listening, research has shown them to be a calming presence. It's no wonder, then, that so many of us talk to ours.In a 2022 survey by trees. com. 50 percent of the 1, 250 respondents reported talking to their plants and trees. When asked why, 65 percent said they believe it helps them grow. The research. however, isn't definitive about this point. While studies have found that vibrations (震动) caused by sound do affect plants, the jury's still out on whether the human voice offers any specific benefit.A study in a 2003 issue of the journal Ultrasonics investigated the effects of classical music and the sounds of birds, insects and water on the growth of Chinese cabbage and cucumber. The conclusion? Both forms of sound exposure increased the vegetables' growth.“Plants definitely respond to vibrations in their environment — which can cause plants to grow differently and become more resistant to falling over, " says Heidi Appel. a professor of environmental sciences at the University of Toledo in Ohio. “Those vibrations can come from airborne (空气传播的) sounds or insects moving on the plants themselves. And plants will respond differently to tones and music than to silence. "Despite the lack of studies and evidence about the benefits of talking to your plants, there is at least one potential benefit. “If we identify with a living organism that we' re tasked with taking care of, we' re going to take better car c of it, " Appel says. For example, if talking to your plants helps you feel more connected to them, you might water, dust and prune (修剪) them more regularly and take other measures to care for them and help them thrive.8. What does “the jury's still out” imply about the effect of the human voice on plants in the paragraph 3?A.The result is still up in the air. B.The fact will be proven.C.General agreement has been reached. D.The possibility is ruled out.9. What does Heidi Appel suggest about the relationship between plants and humans?A.Plants prefer music over other sounds.B.Sound has little effect on plant growth.C.Feeling connected to plants can lead to better care.D.Plants can communicate with humans through sound.10. What is the author's attitude to the benefits of talking to plants?A.Indifferent and unconvinced. B.Objective with a positive outlook.C.Critical and dismissive. D.Highly enthusiastic and supportive.11. What is the main idea of the passage?A.The best ways to care for plants. B.The history of plant research.C.How talking to plants can affect them. D.The advantages of indoor gardening. Why does one plus one equal two? One possible answer is “It just does!” Math can seem like a world of rules you just have to follow, which makes it seem rigid and boring. Whereas my love of math is somewhat driven by my love of breaking rules, or at least pushing against them. Sometimes, one plus one can equal more than two. If you and your friend both have enough cash to buy one cup of coffee, then together you still might have enough to buy three. If one pair of tennis players gets together with another pair for an afternoon of tennis, there ends up being more than two pairs of tennis players because they could play in all sorts of different combinations. Sometimes, one plus one is just one, like if you put a pile of sand on top of another pile of sand, then you just get on c pile of sand. Or, as an art student of mine pointed out, if you mix one color with on c color, you get one color.Actually, Math isn't really about getting the right answer. It's about building good justifications. I often hear parents complaining if children can do something one way, why do they need to know all these other ways?Imagine we were designing a jungle gym for children. We'd want to test it in every possible way to make sure it's safe. We'd want to jump on it, swing from it, fall from it and try to pull it out of the ground, rather than simply trusting that we built it well. The solidity of math comes from not wanting to trust things, but wanting to jump and swing and know that our framework will hold up. One of the reasons the framework is so strong is preciscly because we question it so deeply.I hope that we will start seeing mathematics as a place to pose questions and explore answers, rather than a place where the answers are fixed and we' re supposed to know them. And I hope we will place more emphasis on those who are curious, and who follow their curiosity on a journey that may be slow and without a clear destination, a quiet walk through the countryside rather than a race to the finish.12. In what way does the author approach mathematical rules?A.Thinking outside the box. B.Following them strictly.C.Finding them entertaining. D.Recognizing their importance.13. In the context of tennis players, what does the author mean by “one plus one can be more than two”?A.Tennis players can teach each other new techniques.B.More tennis equipment is needed for each additional player.C.The enjoyment of tennis doubles when more players are involved.D.Two pairs of tennis players can form multiple doubles combinations.14. What is the purpose of mentioning the jungle gym in paragraph 5?A.To simplify the complexity of mathematical learning.B.To illustrate the value of diverse mathematical approaches.C.To demonstrate that math is only useful in practical applications.D.To argue that a single method is sufficient for understanding math.15. What does the author hope for the future of mathematics?A.It will become more rule- based. B.It will focus on getting the correctanswer.C.It will promote the joy of discovery. D.It will emphasize speed and efficiency. Summer can be fun—until boredom strikes. Scientists have learned that boredom reflects our human need for meaningful and challenging activities—and it often spurs us to find them. But where to start? 16 .Seek something meaningfulWe get a ton of satisfaction from looking beyond ourselves, helping others, and working to solve problems. Think of one tiny step you can take to help solve a problem that’s often on your mind.17 . Talk with a parent about volunteering at a children’s library or an animal shelter.18Putting yourself out of your comfort zone is a surefire way to wake up your senses. Learn how to say three sentences in a language that has always fascinated you. Spend an afternoon playing a sport you never tried before. What makes you nervous? Tackle your fear: Sing in front of others. Ride a roller coaster. Learn about snakes.Add variety19 . Invite a new kid to join you in an activity. Try tasting a new food every week. Mix things up a little!Be a friend (OR two)When you try a new activity with someone, it’s double the fun! And it doesn’t matter if you’ re awesome or terrible at it. 20 . Go rollerskating, or try two- person juggling. Film a funny news show. Add mystery ingredients to cookies, then ask your famil y and friends to guess what’s in them. Leave room for surprisesNOT planning out every detail of your day can lead to wonderful things. Listen more closely to other people’s suggestions. Ask yourself “Why Not?” more often. Pay attention to what’s around you, and make time to explore!Every day, as I commute to school on the bus, I’m part of a diverse group of individuals. The bus is filled with the _______ faces of labor workers, the energetic chatting of students. and the thoughtful expressions of office professionals. The bus, with its constant movement, is a small _______ of the busy world outside, where everyone is on their own journey.One particular day, I was seated next to an elderly man whose eyes seemed to hold a depth of experience and wisdom. His presence served as a gentle _______ that each person carries unique stories shaped by the years.As the bus rolled along, it _______ me that our lives, much like this bus ride, are full of brief encounters and shared moments. We share the same space with others, yet often _______ to take the time to understand one another’s stories. This realization made me value each interaction more deeply. Each person I _______ on the bus, no matter how _______ , might have something valuable to share, something that could broaden my _______ into the world.Now. I’ve made it a _______ to appreciate these chance encounters. They may appear as ordinary folks, but each one has the potential to offer a new perspective or a life lesson. Life is a ________ of small, significant moments, and being mindful of them can greatly enrich our experiences and enable us to ________ more quickly to the intentions and feelings of other s. So, let’s not be too________ in our journey through life. Let’s take a moment to appreciate the beauty and connections we make, for they are the ________ teachers and the storytellers of our shared human experience. By doing so, we ________ ourselves to learn from the people we meet and the world around us,________ depth and color to our own lives that we might otherwise overlook.21.A.annoyed B.tired C.confused D.thrilled22.A.imagination B.thought C.reflection D.impression23.A.reminder B.warning C.sign D.mark24.A.stuck B.occurred C.told D.hit25.A.start B.manage C.struggle D.fail26.A.run into B.find out C.come up D.go through27.A.instantly B.regularly C.briefly D.deliberately28.A.recognition B.insight C.awareness D.knowledge29.A.duty B.point C.purpose D.mistake30.A.collection B.part C.couple D.bit31.A.pick up B.catch on C.work out D.bring back32.A.casual B.focused C.hurried D.concerned33.A.strict B.patient C.silent D.motivated34.A.force B.persuade C.advocate D.allow35.A.engaging B.leaving C.making D.adding阅读下面短文,在空白处填入1个适当的词或括号内单词的正确形式。
the-name-and-nature-of-translation-studies翻译的名与实
2.3 “translation studies” term
❖ Indeed, for disciplines that within the old distinction of the universities tend to fall under the humanities or arts, the word would be active.
1lexicographicalandterminological词典编纂和术语2grammars语法323translationpolicy翻译政策?itisdeterminedbywhatkindofsocialandeconomicpositionthetranslatorshouldbein?orwhatparttranslatingshouldplayintheteachingandlearningofforeignlanguages主要解释译者及译本的角色和地位研究某社会应引进和翻译哪些作品研究翻译在外语教学中的作用translationcriticism翻译批评?translationcriticism翻译批评theevaluationofthetargettexts即对译文进行评价331conclusion?therelationsamongdescriptivetheoreticalandappliedtranslationstudiesaredialecticalattentiontoallthreebranchesisrequiredifthedisciplineistogrowandflourish?三者的关系是辩证统一的缺少其中任何一个分支这一学科都不能发展和繁荣
Parallel and Distributed Computing and Systems
Proceedings of the IASTED International ConferenceParallel and Distributed Computing and SystemsNovember3-6,1999,MIT,Boston,USAParallel Refinement of Unstructured MeshesJos´e G.Casta˜n os and John E.SavageDepartment of Computer ScienceBrown UniversityE-mail:jgc,jes@AbstractIn this paper we describe a parallel-refinement al-gorithm for unstructuredfinite element meshes based on the longest-edge bisection of triangles and tetrahedrons. This algorithm is implemented in P ARED,a system that supports the parallel adaptive solution of PDEs.We dis-cuss the design of such an algorithm for distributed mem-ory machines including the problem of propagating refine-ment across processor boundaries to obtain meshes that are conforming and non-degenerate.We also demonstrate that the meshes obtained by this algorithm are equivalent to the ones obtained using the serial longest-edge refine-ment method.Wefinally report on the performance of this refinement algorithm on a network of workstations.Keywords:mesh refinement,unstructured meshes,finite element methods,adaptation.1.IntroductionThefinite element method(FEM)is a powerful and successful technique for the numerical solution of partial differential equations.When applied to problems that ex-hibit highly localized or moving physical phenomena,such as occurs on the study of turbulence influidflows,it is de-sirable to compute their solutions adaptively.In such cases, adaptive computation has the potential to significantly im-prove the quality of the numerical simulations by focusing the available computational resources on regions of high relative error.Unfortunately,the complexity of algorithms and soft-ware for mesh adaptation in a parallel or distributed en-vironment is significantly greater than that it is for non-adaptive computations.Because a portion of the given mesh and its corresponding equations and unknowns is as-signed to each processor,the refinement(coarsening)of a mesh element might cause the refinement(coarsening)of adjacent elements some of which might be in neighboring processors.To maintain approximately the same number of elements and vertices on every processor a mesh must be dynamically repartitioned after it is refined and portions of the mesh migrated between processors to balance the work.In this paper we discuss a method for the paral-lel refinement of two-and three-dimensional unstructured meshes.Our refinement method is based on Rivara’s serial bisection algorithm[1,2,3]in which a triangle or tetrahe-dron is bisected by its longest edge.Alternative efforts to parallelize this algorithm for two-dimensional meshes by Jones and Plassman[4]use randomized heuristics to refine adjacent elements located in different processors.The parallel mesh refinement algorithm discussed in this paper has been implemented as part of P ARED[5,6,7], an object oriented system for the parallel adaptive solu-tion of partial differential equations that we have devel-oped.P ARED provides a variety of solvers,handles selec-tive mesh refinement and coarsening,mesh repartitioning for load balancing,and interprocessor mesh migration.2.Adaptive Mesh RefinementIn thefinite element method a given domain is di-vided into a set of non-overlapping elements such as tri-angles or quadrilaterals in2D and tetrahedrons or hexahe-drons in3D.The set of elements and its as-sociated vertices form a mesh.With theaddition of boundary conditions,a set of linear equations is then constructed and solved.In this paper we concentrate on the refinement of conforming unstructured meshes com-posed of triangles or tetrahedrons.On unstructured meshes, a vertex can have a varying number of elements adjacent to it.Unstructured meshes are well suited to modeling do-mains that have complex geometry.A mesh is said to be conforming if the triangles and tetrahedrons intersect only at their shared vertices,edges or faces.The FEM can also be applied to non-conforming meshes,but conformality is a property that greatly simplifies the method.It is also as-sumed to be a requirement in this paper.The rate of convergence and quality of the solutions provided by the FEM depends heavily on the number,size and shape of the mesh elements.The condition number(a)(b)(c)Figure1:The refinement of the mesh in using a nested refinement algorithm creates a forest of trees as shown in and.The dotted lines identify the leaf triangles.of the matrices used in the FEM and the approximation error are related to the minimum and maximum angle of all the elements in the mesh[8].In three dimensions,the solid angle of all tetrahedrons and their ratio of the radius of the circumsphere to the inscribed sphere(which implies a bounded minimum angle)are usually used as measures of the quality of the mesh[9,10].A mesh is non-degenerate if its interior angles are never too small or too large.For a given shape,the approximation error increases with ele-ment size(),which is usually measured by the length of the longest edge of an element.The goal of adaptive computation is to optimize the computational resources used in the simulation.This goal can be achieved by refining a mesh to increase its resolution on regions of high relative error in static problems or by re-fining and coarsening the mesh to follow physical anoma-lies in transient problems[11].The adaptation of the mesh can be performed by changing the order of the polynomi-als used in the approximation(-refinement),by modifying the structure of the mesh(-refinement),or a combination of both(-refinement).Although it is possible to replace an old mesh with a new one with smaller elements,most -refinement algorithms divide each element in a selected set of elements from the current mesh into two or more nested subelements.In P ARED,when an element is refined,it does not get destroyed.Instead,the refined element inserts itself into a tree,where the root of each tree is an element in the initial mesh and the leaves of the trees are the unrefined elements as illustrated in Figure1.Therefore,the refined mesh forms a forest of refinement trees.These trees are used in many of our algorithms.Error estimates are used to determine regions where adaptation is necessary.These estimates are obtained from previously computed solutions of the system of equations. After adaptation imbalances may result in the work as-signed to processors in a parallel or distributed environ-ment.Efficient use of resources may require that elements and vertices be reassigned to processors at runtime.There-fore,any such system for the parallel adaptive solution of PDEs must integrate subsystems for solving equations,adapting a mesh,finding a good assignment of work to processors,migrating portions of a mesh according to anew assignment,and handling interprocessor communica-tion efficiently.3.P ARED:An OverviewP ARED is a system of the kind described in the lastparagraph.It provides a number of standard iterativesolvers such as Conjugate Gradient and GMRES and pre-conditioned versions thereof.It also provides both-and -refinement of meshes,algorithms for adaptation,graph repartitioning using standard techniques[12]and our ownParallel Nested Repartitioning(PNR)[7,13],and work mi-gration.P ARED runs on distributed memory parallel comput-ers such as the IBM SP-2and networks of workstations.These machines consist of coarse-grained nodes connectedthrough a high to moderate latency network.Each nodecannot directly address a memory location in another node. In P ARED nodes exchange messages using MPI(Message Passing Interface)[14,15,16].Because each message has a high startup cost,efficient message passing algorithms must minimize the number of messages delivered.Thus, it is better to send a few large messages rather than many small ones.This is a very important constraint and has a significant impact on the design of message passing algo-rithms.P ARED can be run interactively(so that the user canvisualize the changes in the mesh that results from meshadaptation,partitioning and migration)or without directintervention from the user.The user controls the systemthrough a GUI in a distinguished node called the coordina-tor,.This node collects information from all the other processors(such as its elements and vertices).This tool uses OpenGL[17]to permit the user to view3D meshes from different angles.Through the coordinator,the user can also give instructions to all processors such as specify-ing when and how to adapt the mesh or which strategy to use when repartitioning the mesh.In our computation,we assume that an initial coarse mesh is given and that it is loaded into the coordinator.The initial mesh can then be partitioned using one of a num-ber of serial graph partitioning algorithms and distributed between the processors.P ARED then starts the simulation. Based on some adaptation criterion[18],P ARED adapts the mesh using the algorithms explained in Section5.Af-ter the adaptation phase,P ARED determines if a workload imbalance exists due to increases and decreases in the num-ber of mesh elements on individual processors.If so,it invokes a procedure to decide how to repartition mesh el-ements between processors;and then moves the elements and vertices.We have found that PNR gives partitions with a quality comparable to those provided by standard meth-ods such as Recursive Spectral Bisection[19]but which(b)(a)Figure2:Mesh representation in a distributed memory ma-chine using remote references.handles much larger problems than can be handled by stan-dard methods.3.1.Object-Oriented Mesh RepresentationsIn P ARED every element of the mesh is assigned to a unique processor.V ertices are shared between two or more processors if they lie on a boundary between parti-tions.Each of these processors has a copy of the shared vertices and vertices refer to each other using remote ref-erences,a concept used in object-oriented programming. This is illustrated in Figure2on which the remote refer-ences(marked with dashed arrows)are used to maintain the consistency of multiple copies of the same vertex in differ-ent processors.Remote references are functionally similar to standard C pointers but they address objects in a different address space.A processor can use remote references to invoke meth-ods on objects located in a different processor.In this case, the method invocations and arguments destined to remote processors are marshalled into messages that contain the memory addresses of the remote objects.In the destina-tion processors these addresses are converted to pointers to objects of the corresponding type through which the meth-ods are invoked.Because the different nodes are inher-ently trusted and MPI guarantees reliable communication, P ARED does not incur the overhead traditionally associated with distributed object systems.Another idea commonly found in object oriented pro-gramming and which is used in P ARED is that of smart pointers.An object can be destroyed when there are no more references to it.In P ARED vertices are shared be-tween several elements and each vertex counts the number of elements referring to it.When an element is created, the reference count of its vertices is incremented.Simi-larly,when the element is destroyed,the reference count of its vertices is decremented.When the reference count of a vertex reaches zero,the vertex is no longer attached to any element located in the processor and can be destroyed.If a vertex is shared,then some other processor might have a re-mote reference to it.In that case,before a copy of a shared vertex is destroyed,it informs the copies in other processors to delete their references to itself.This procedure insures that the shared vertex can then be safely destroyed without leaving dangerous dangling pointers referring to it in other processors.Smart pointers and remote references provide a simple replication mechanism that is tightly integrated with our mesh data structures.In adaptive computation,the struc-ture of the mesh evolves during the computation.During the adaptation phase,elements and vertices are created and destroyed.They may also be assigned to a different pro-cessor to rebalance the work.As explained above,remote references and smart pointers greatly simplify the task of creating dynamic meshes.4.Adaptation Using the Longest Edge Bisec-tion AlgorithmMany-refinement techniques[20,21,22]have been proposed to serially refine triangular and tetrahedral meshes.One widely used method is the longest-edge bisec-tion algorithm proposed by Rivara[1,2].This is a recursive procedure(see Figure3)that in two dimensions splits each triangle from a selected set of triangles by adding an edge between the midpoint of its longest side to the opposite vertex.In the case that makes a neighboring triangle,,non-conforming,then is refined using the same algorithm.This may cause the refinement to prop-agate throughout the mesh.Nevertheless,this procedure is guaranteed to terminate because the edges it bisects in-crease in length.Building on the work of Rosenberg and Stenger[23]on bisection of triangles,Rivara[1,2]shows that this refinement procedure provably produces two di-mensional meshes in which the smallest angle of the re-fined mesh is no less than half of the smallest angle of the original mesh.The longest-edge bisection algorithm can be general-ized to three dimensions[3]where a tetrahedron is bisected into two tetrahedrons by inserting a triangle between the midpoint of its longest edge and the two vertices not in-cluded in this edge.The refinement propagates to neigh-boring tetrahedrons in a similar way.This procedure is also guaranteed to terminate,but unlike the two dimensional case,there is no known bound on the size of the small-est angle.Nevertheless,experiments conducted by Rivara [3]suggest that this method does not produce degenerate meshes.In two dimensions there are several variations on the algorithm.For example a triangle can initially be bisected by the longest edge,but then its children are bisected by the non-conforming edge,even if it is that is not their longest edge[1].In three dimensions,the bisection is always per-formed by the longest edge so that matching faces in neigh-boring tetrahedrons are always bisected by the same com-mon edge.Bisect()let,and be vertices of the trianglelet be the longest side of and let be the midpoint ofbisect by the edge,generating two new triangles andwhile is a non-conforming vertex dofind the non-conforming triangle adjacent to the edgeBisect()end whileFigure3:Longest edge(Rivara)bisection algorithm for triangular meshes.Because in P ARED refined elements are not destroyed in the refinement tree,the mesh can be coarsened by replac-ing all the children of an element by their parent.If a parent element is selected for coarsening,it is important that all the elements that are adjacent to the longest edge of are also selected for coarsening.If neighbors are located in different processors then only a simple message exchange is necessary.This algorithm generates conforming meshes: a vertex is removed only if all the elements that contain that vertex are all coarsened.It does not propagate like the re-finement algorithm and it is much simpler to implement in parallel.For this reason,in the rest of the paper we will focus on the refinement of meshes.5.Parallel Longest-Edge RefinementThe longest-edge bisection algorithm and many other mesh refinement algorithms that propagate the refinement to guarantee conformality of the mesh are not local.The refinement of one particular triangle or tetrahedron can propagate through the mesh and potentially cause changes in regions far removed from.If neighboring elements are located in different processors,it is necessary to prop-agate this refinement across processor boundaries to main-tain the conformality of the mesh.In our parallel longest edge bisection algorithm each processor iterates between a serial phase,in which there is no communication,and a parallel phase,in which each processor sends and receives messages from other proces-sors.In the serial phase,processor selects a setof its elements for refinement and refines them using the serial longest edge bisection algorithms outlined earlier. The refinement often creates shared vertices in the bound-ary between adjacent processors.To minimize the number of messages exchanged between and,delays the propagation of refinement to until has refined all the elements in.The serial phase terminates when has no more elements to refine.A processor informs an adjacent processor that some of its elements need to be refined by sending a mes-sage from to containing the non-conforming edges and the vertices to be inserted at their midpoint.Each edge is identified by its endpoints and and its remote ref-erences(see Figure4).If and are sharedvertices,(a)(c)(b)Figure4:In the parallel longest edge bisection algo-rithm some elements(shaded)are initially selected for re-finement.If the refinement creates a new(black)ver-tex on a processor boundary,the refinement propagates to neighbors.Finally the references are updated accord-ingly.then has a remote reference to copies of and lo-cated in processor.These references are included in the message,so that can identify the non-conforming edge and insert the new vertex.A similar strategy can be used when the edge is refined several times during the re-finement phase,but in this case,the vertex is not located at the midpoint of.Different processors can be in different phases during the refinement.For example,at any given time a processor can be refining some of its elements(serial phase)while neighboring processors have refined all their elements and are waiting for propagation messages(parallel phase)from adjacent processors.waits until it has no elements to refine before receiving a message from.For every non-conforming edge included in a message to,creates its shared copy of the midpoint(unless it already exists) and inserts the new non-conforming elements adjacent to into a new set of elements to be refined.The copy of in must also have a remote reference to the copy of in.For this reason,when propagates the refine-ment to it also includes in the message a reference to its copies of shared vertices.These steps are illustrated in Figure4.then enters the serial phase again,where the elements in are refined.(c)(b)(a)Figure5:Both processors select(shaded)mesh el-ements for refinement.The refinement propagates to a neighboring processor resulting in more elements be-ing refined.5.1.The Challenge of Refining in ParallelThe description of the parallel refinement algorithm is not complete because refinement propagation across pro-cessor boundaries can create two synchronization prob-lems.Thefirst problem,adaptation collision,occurs when two(or more)processors decide to refine adjacent elements (one in each processor)during the serial phase,creating two(or more)vertex copies over a shared edge,one in each processor.It is important that all copies refer to the same logical vertex because in a numerical simulation each ver-tex must include the contribution of all the elements around it(see Figure5).The second problem that arises,termination detection, is the determination that a refinement phase is complete. The serial refinement algorithm terminates when the pro-cessor has no more elements to refine.In the parallel ver-sion termination is a global decision that cannot be deter-mined by an individual processor and requires a collabora-tive effort of all the processors involved in the refinement. Although a processor may have adapted all of its mesh elements in,it cannot determine whether this condition holds for all other processors.For example,at any given time,no processor might have any more elements to re-fine.Nevertheless,the refinement cannot terminate because there might be some propagation messages in transit.The algorithm for detecting the termination of parallel refinement is based on Dijkstra’s general distributed termi-nation algorithm[24,25].A global termination condition is reached when no element is selected for refinement.Hence if is the set of all elements in the mesh currently marked for refinement,then the algorithmfinishes when.The termination detection procedure uses message ac-knowledgments.For every propagation message that receives,it maintains the identity of its source()and to which processors it propagated refinements.Each prop-agation message is acknowledged.acknowledges to after it has refined all the non-conforming elements created by’s message and has also received acknowledgments from all the processors to which it propagated refinements.A processor can be in two states:an inactive state is one in which has no elements to refine(it cannot send new propagation messages to other processors)but can re-ceive messages.If receives a propagation message from a neighboring processor,it moves from an inactive state to an active state,selects the elements for refinement as spec-ified in the message and proceeds to refine them.Let be the set of elements in needing refinement.A processor becomes inactive when:has received an acknowledgment for every propa-gation message it has sent.has acknowledged every propagation message it has received..Using this definition,a processor might have no more elements to refine()but it might still be in an active state waiting for acknowledgments from adjacent processors.When a processor becomes inactive,sends an acknowledgment to the processors whose propagation message caused to move from an inactive state to an active state.We assume that the refinement is started by the coordi-nator processor,.At this stage,is in the active state while all the processors are in the inactive state.ini-tiates the refinement by sending the appropriate messages to other processors.This message also specifies the adapta-tion criterion to use to select the elements for refinement in.When a processor receives a message from,it changes to an active state,selects some elements for refine-ment either explicitly or by using the specified adaptation criterion,and then refines them using the serial bisection algorithm,keeping track of the vertices created over shared edges as described earlier.When itfinishes refining its ele-ments,sends a message to each processor on whose shared edges created a shared vertex.then listens for messages.Only when has refined all the elements specified by and is not waiting for any acknowledgment message from other processors does it sends an acknowledgment to .Global termination is detected when the coordinator becomes inactive.When receives an acknowledgment from every processor this implies that no processor is re-fining an element and that no processor is waiting for an acknowledgment.Hence it is safe to terminate the refine-ment.then broadcasts this fact to all the other proces-sors.6.Properties of Meshes Refined in ParallelOur parallel refinement algorithm is guaranteed to ter-minate.In every serial phase the longest edge bisectionLet be a set of elements to be refinedwhile there is an element dobisect by its longest edgeinsert any non-conforming element intoend whileFigure6:General longest-edge bisection(GLB)algorithm.algorithm is used.In this algorithm the refinement prop-agates towards progressively longer edges and will even-tually reach the longest edge in each processor.Between processors the refinement also propagates towards longer edges.Global termination is detected by using the global termination detection procedure described in the previous section.The resulting mesh is conforming.Every time a new vertex is created over a shared edge,the refinement propagates to adjacent processors.Because every element is always bisected by its longest edge,for triangular meshes the results by Rosenberg and Stenger on the size of the min-imum angle of two-dimensional meshes also hold.It is not immediately obvious if the resulting meshes obtained by the serial and parallel longest edge bisection al-gorithms are the same or if different partitions of the mesh generate the same refined mesh.As we mentioned earlier, messages can arrive from different sources in different or-ders and elements may be selected for refinement in differ-ent sequences.We now show that the meshes that result from refining a set of elements from a given mesh using the serial and parallel algorithms described in Sections4and5,re-spectively,are the same.In this proof we use the general longest-edge bisection(GLB)algorithm outlined in Figure 6where the order in which elements are refined is not spec-ified.In a parallel environment,this order depends on the partition of the mesh between processors.After showing that the resulting refined mesh is independent of the order in which the elements are refined using the serial GLB al-gorithm,we show that every possible distribution of ele-ments between processors and every order of parallel re-finement yields the same mesh as would be produced by the serial algorithm.Theorem6.1The mesh that results from the refinement of a selected set of elements of a given mesh using the GLB algorithm is independent of the order in which the elements are refined.Proof:An element is refined using the GLBalgorithm if it is in the initial set or refinementpropagates to it.An element is refinedif one of its neighbors creates a non-conformingvertex at the midpoint of one of its edges.Therefinement of by its longest edge divides theelement into two nested subelements andcalled the children of.These children are inturn refined by their longest edge if one of their edges is non-conforming.The refinement proce-dure creates a forest of trees of nested elements where the root of each tree is an element in theinitial mesh and the leaves are unrefined ele-ments.For every element,let be the refinement tree of nested elements rooted atwhen the refinement procedure terminates. Using the GLB procedure elements can be se-lected for refinement in different orders,creating possible different refinement histories.To show that this cannot happen we assume the converse, namely,that two refinement histories and generate different refined meshes,and establish a contradiction.Thus,assume that there is an ele-ment such that the refinement trees and,associated with the refinement histories and of respectively,are different.Be-cause the root of and is the same in both refinement histories,there is a place where both treesfirst differ.That is,starting at the root,there is an element that is common to both trees but for some reason,its children are different.Be-cause is always bisected by the longest edge, the children of are different only when is refined in one refinement history and it is not re-fined in the other.In other words,in only one of the histories does have children.Because is refined in only one refinement his-tory,then,the initial set of elements to refine.This implies that must have been refined because one of its edges became non-conforming during one of the refinement histo-ries.Let be the set of elements that are present in both refinement histories,but are re-fined in and not in.We define in a similar way.For each refinement history,every time an ele-ment is refined,it is assigned an increasing num-ber.Select an element from either or that has the lowest number.Assume that we choose from so that is refined in but not in.In,is refined because a neigh-boring element created a non-conforming ver-tex at the midpoint of their shared edge.There-fore is refined in but not in because otherwise it would cause to be refined in both sequences.This implies that is also in and has a lower refinement number than con-。
Ination Targets and Debt Accumulation in a Monetary Union ¤
In‡ation T argets and Debt Accumulation in aMonetary Union¤Roel BeetsmaUniversity of Amsterdam and CEPR yns BovenbergTilburg University and CEPR zOctober1999AbstractThis paper explores the interaction between centralized monetary policyand decentralized…scal policy in a monetary union.Discretionary mone-tary policy su¤ers from a failure to commit.Moreover,decentralized…scalpolicymakers impose externalities on each other through the in‡uence oftheir debt policies on the common monetary policy.These imperfectionscan be alleviated by adopting state-contingent in‡ation targets(to com-bat the monetary policy commitment problem)and shock-contingent debttargets(to internalize the externalities due to decentralized…scal policy).Keywords:discretionary monetary policy,decentralized…scal policy, monetary union,in‡ation targets,debt targets.JEL Codes:E52,E58,E61,E62.¤We thank David Vestin and the participants of the EPRU Workshop“Structural Change and European Economic Integration”for helpful comments on an earlier version of this paper. The usual disclaimer applies.y Mailing address Roel Beetsma:Department of Economics,University of Amsterdam, Roetersstraat11,1018WB Amsterdam,The Netherlands(phone:+31.20.5255280;fax: +31.20.5254254;e-mail:Beetsma@fee.uva.nl).z Mailing address Lans Bovenberg:Department of Economics,Tilburg University,P.O.Box 90153,5000LE Tilburg,The Netherlands(phone:+31.13.4662912;fax:+31.13.4663042;e-mail: A.L.Bovenberg@kub.nl).1.IntroductionAlthough the Maatricht Treaty has laid the institutional foundations for European Monetary Union(EMU),how these institutions can best be operated in practice remains to be seen in the coming years.For example,the European Central Bank (ECB)has announced a two-tier monetary policy strategy based on a reference value for money growth and an indicator that is based on a number of other measures,such as output gaps,in‡ation expectations,etcetera(see European Central Bank,1999).Over time the ECB may well shift to implicit targeting of in‡ation.Indeed,a number of economists has argued(e.g,see Svensson,1998) that also the Bundesbank has pursued such a strategy.Furthermore,how the Excessive De…cit Procedure and the Stability and Growth Pact(see Beetsma and Uhlig,1999)will work in practice is not yet clear.This paper deals with the interaction between in‡ation targets and constraints on decentralized…scal policy in a monetary union.To do so,we extend our earlier work on the interaction between a common monetary policy and decentralized …scal policies in a monetary union.In particular,in Beetsma and Bovenberg (1999)we showed that monetary uni…cation raises debt accumulation,because in a monetary union countries only partly internalize the e¤ects of their debt policies on future monetary policy.This additional debt accumulation is actually welfare enhancing(if the governments share societal preferences).We showed that,in the absence of shocks,making the central bank su¢ciently conservative(in the sense of Rogo¤,1985,that is by imposing on the central bank a loss function that attaches a su¢ciently high weight to price stability)can lead the economy to the second-best equilibrium.However,this is no longer the case in the presence of common shocks,as the economies are confronted with a trade o¤between credibility and‡exibility.While Beetsma and Bovenberg(1999)emphasized the e¤ects of lack of com-mitment in monetary policy,this paper introduces another complication in the form of strategic interactions between decentralized…scal policymakers who have di¤erent views on the stance of the common monetary policy.1These di¤erent views originate in di¤erences among the economies in the monetary union.In particular,we allow for systematic di¤erences in labour and product market dis-tortions,public spending requirements and initial public debt levels.We also allow for idiosyncratic stochastic shocks hitting the countries.In combination with the decentralization of…scal policy these di¤erences lead to con‡icts about the preferred future stance of the common monetary policy.In particular,coun-tries that su¤er from severe distortions in labor and commodity markets,feature 1Our earlier model incorporated another potential distortion:the possibility that govern-ments discount the future at a higher rate than their societies do.We ignore this distortion throughout the current paper.2higher public spending or initial debt levels or are hit by worse shocks prefer a laxer future stance of monetary policy.These con‡icts about monetary policy induce individual governments to employ their debt policy strategically,so as to induce the union’s central bank to move monetary policy into the direction they prefer.This strategic behavior imposes negative externalities on other countries, thereby producing welfare losses.In contrast to Beetsma and Bovenberg(1999),we do not address the distor-tions in the model by making the common central bank su¢ciently conservative. Instead,we focus on state-contingent in‡ation targets which,in contrast to a con-servative central bank,can lead the economy to the second-best equilibrium if countries are identical.Hence,as stressed by Svensson(1997)in a model with-out…scal policy and debt accumulation,in‡ation targets eliminate the standard credibility-‡exibility trade-o¤.If…scal policy is decentralized to heterogeneous countries,however,the optimal state-contingent in‡ation targets need to be com-plemented by(country-speci…c)debt targets to establish the second best.In this way,in‡ation targets address the lack of commitment in monetary policy,while debt targets eliminate strategic interaction among heterogeneous governments with di¤erent views about the common monetary policy stance.The remainder of this paper is structured as follows.Section2presents the model.Section3discusses the second-best equilibrium in which not only monetary but also…scal policy is centralized and in which monetary policy is conducted under commitment.This is the second-best optimum that can be attained under monetary uni…cation,assuming that the supranational authorities attach an equal weight to the preferences of each of the participating countries.Section4derives the equilibrium for the case of a common,discretionary monetary policy with decentralized…scal policies.Section5explores institutional arrangements(i.e. in‡ation targets and public debt targets)that may alleviate the welfare losses arising from the lack of monetary policy commitment and the wasteful strategic interaction among the decentralized governments.Finally,Section6concludes the main body of this paper.The derivations are contained in the appendix.2.The modelA monetary union,which is small relative to the rest of the world,is formed by n countries.2A common central bank(CCB)sets monetary policy for the entire union,while…scal policy is determined at a decentralized,national level by the n governments.There are two periods.2Monetary uni…cation is taken as given.Hence,we do not explore the incentives of countries to join a monetary union.3Workers are represented by trade unions who aim for some target real wage rate(e.g.see Alesina and Tabellini,1987,and Jensen,1994).They set nominal wages so as to minimize the expected squared deviation of the realized real wage rate from this target.Monetary policy(i.e.,the in‡ation rate)is selected after nominal wages have been…xed.In each country,…rms face a standard production function with decreasing returns to scale in labour.Output in period t is taxed at a rate¿it.Therefore,output in country i in periods1and2,respectively,is given by3x i1=º(¼1¡¼e1¡¿i1)¡¹¡²i;(2.1)x i2=º(¼2¡¼e2¡¿i2);(2.2) where¹represents a common union-wide shock,while²i stands for an idiosyn-cratic shock that solely hits country i.¼et denotes the in‡ation rate for period texpected at the start of period t(that is,before period t shocks have materialized, but after period t¡1;t¡2;::shocks have hit).We assume that E[²i]=0;8i; E[¹]=0;E[²i²j]=0;8j=i;and that¹²´1P n i=1²i=0.4The variances of¹and ²i are given by¾2¹and¾2²,respectively.We abstract from shocks in the secondperiod,because they would not a¤ect debt accumulation.Each country features a social welfare function which is shared by the govern-ment of that country.Hence,governments are benevolent.In particular,the loss function of government i is de…ned over in‡ation,output and public spending:V S;i=12X t=1¯t¡1h®¼¼2t+(x it¡~x it)2+®g(g it¡~g it)2i;0<¯ 1;®¼;®g>0:(2.3)Welfare losses increase in the deviations of in‡ation,(log)output and government spending(g it is government spending as a share of output in the absence of distor-tions)from their targets(or…rst-best levels or“bliss points”).For convenience, the target level for in‡ation corresponds to price stability.The target level for output is denoted by~x it>0.Two distortions reduce output below this optimal level.First,the output tax¿it drives a wedge between the social and private bene…ts of additional output.Second,market power enables unions to drive the real wage above its level in the absence of distortions.Hence,even in the ab-sence of taxes,output is below the…rst-best output level~x it>0.The…rst-best 3Details on the derivations of these output equations can be found in Beetsma and Bovenberg (1999).4Without this assumption,the mean¹²of the²’s would play the same role as¹does.In the outcomes given below,¹would then be replaced by^¹´¹+¹².For convenience,we assume that ¹²=0.4level of government spending,~g it,can be interpreted as the optimal share of non-distortionary output to be spent on public goods if(non-distortionary)lump-sum taxes would be available(see Debelle and Fischer,1994).The target levels for output and government spending can di¤er across countries.Parameters®¼and ®g correspond to the weights of the price stability and government spending ob-jectives,respectively,relative to the weight of the output objective.Finally,¯denotes society’s subjective discount factor.Government i’s budget constraint can be approximated by(e.g.,see Appendix A in Beetsma and Bovenberg,1999):g it+(1+½)d i;t¡1=¿it+¼t+d it;(2.4) where d i;t¡1represents the amount of public debt carried over from the previous period into period t,while d it stands for the amount of debt outstanding at the end of period t.All public debt is real,matures after one period,and is sold on the world capital market against a real rate of interest of½.This interest rate is exogenous because the countries making up the monetary union are small relative to the rest of the world.5¿it andÂ(a constant)stand for,respectively,distor-tionary tax revenue and real holdings of base money as shares of non-distortionary output.All countries share equally in the seigniorage revenues of the CCB,so that the seigniorage revenues accruing to country i amount to¼t.We combine(2.4)with the expression for output,(2.1)or(2.2),to eliminate ¿it.The resulting equation can be rewritten to yield the government…nancing requirement of period t:GF R it=~K it+(1+½)d i;t¡1¡d it+±t(¹+²i)=º=[(~x it¡x it)=º]+¼t+(~g it¡g it)+(¼t¡¼e t);(2.5) where±t is an indicator function,such that±1=1and±2=0,and where~Kit´~g it+~x it=º.The government…nancing requirement,GF R it,consists of three components.The …rst component,~K it,amounts to the government spending target,~g it,and an out-put subsidy aimed at o¤setting the implicit output tax due to labor-or product-market distortions,~x it=º.The second component involves net debt-servicing costs, 5In the following,we will occasionally explore what happens when the number of union participants becomes in…nitely large(i.e.n!1)in order to strengthen the intuition behind our results.In these exercises the real interest rate remains beyond the control of union-level policymakers.5(1+½)d i;t¡1¡d it.The…nal component(in period1only)is the stochastic shock (scaled byº),(¹+²i)=º.The last right-hand side of(2.5)represents the sources of…nance:the shortfall(scaled byº)of output from its target(henceforth re-ferred to as the output gap),(~x it¡x it)=º,seigniorage revenues,¼t,the shortfall of government spending from its target(henceforth referred to as the spending gap),~g it¡g it,and the in‡ation surprise,¼t¡¼e t.All public debt is paid o¤at the end of the second period(d i2=0;i= 1;::;n).Under this assumption,while taking the discounted(to period one)sums of the left-and right-hand sides of(2.5)(t=1;2),we obtain the intertemporal government…nancing requirement:IGF R i=~F i+(¹+²i)=º=2X t=1(1+½)¡(t¡1)[(~x it¡x it)=º+¼t+(~g it¡g it)+(¼t¡¼e t)];(2.6)where~F i´~K i1+(1+½)d i0+~K i2=(1+½)stands for the deterministic component of the intertemporal government…nancing requirement.Monetary policy is delegated to a common central banker(CCB),who has direct control over the union’s in‡ation rate.One could assume that the CCB has certain intrinsic preferences regarding the policy outcomes.Alternatively,and this is the interpretation we prefer,one could assume that the CCB is assigned a loss function by means of an appropriate contractual agreement.More speci…cally,this agreement shapes the CCB’s incentives in such a way(by appropriately specifying its salary and other bene…ts–for example,possible reappointment–conditional on its performance)that it chooses to maximize the following loss function:V CCB=12X t=1¯t¡1(®¼(¼t¡¼¤t)2+1n X i=1h(x it¡~x it)2+®g(g it¡~g it)2i);(2.7)where¼¤t is the in‡ation target in period t,which may be di¤erent from the socially-optimal in‡ation rate,which was set at zero.If¼¤1=¼¤2=0,the CCB’s objective function corresponds to an equally-weighted average of the individual societies’objective functions.We assume that ¼¤2is a linear function of d i1;i=1;::;n.This linearity assumption su¢ces for our purposes:we will see later on that the optimal second-period in‡ation target is indeed a linear function of d i1;i=1;::;n.The optimal…rst-period in‡ation target will be a function of d i0,which is exogenous.63.The second-best equilibriumAs a benchmark for the remainder of the analysis,we discuss the equilibrium resulting from centralized…scal and monetary policies under commitment.Mon-etary policy is set by the CCB.Fiscal policy is conducted by a centralized…scal authority,which minimizes:V U´1n X i=1V S;i;(3.1)where the V S;i are given by(2.3),i=1;::;n.Equation(3.1)assumes that coun-tries have equal bargaining power as regards to the…scal policy decisions taken at the union ernment spending is residually determined,so that the CCB,when it selects monetary policy,internalizes the government budget con-straints.The resulting equilibrium is Pareto optimal.In the sequel,we refer to this equilibrium as the second-best equilibrium.In the absence of…rst-best policies (such as the use of lump-sum taxation and the elimination of product-and labor-market distortions),it is the equilibrium with the smallest possible welfare loss (3.1),given monetary uni…cation.The derivation of the second-best equilibrium is contained in Appendix A.3.1.In‡ation,the output gap and the public spending gapTable1contains the outcomes for in‡ation,the output gap,6~x it¡x it,and the spending gap,~g it¡g it.We write each of these outcomes as the sum of two deterministic and two stochastic components.~F¢i is the deviation of country i’s deterministic component of its intertemporal government…nancing requirement from the cross-country average,de…ned by~F.Formally,~F´1n P n j=1~F j and ~F¢i´~F i¡~F.The factor between square brackets in each of the entries of Table1 makes clear how,within a given period,the government…nancing requirement is distributed over the…nancing sources(seigniorage,the output gap,the spending gap and an in‡ation surprise).Indeed,for each period these factors add up to unity,both across the deterministic and across the stochastic components.For example,for the…rst period one has:6Throughout,we present the outcome for the output gap instead of the outcome for the tax rate.The reason is that,in contrast to the latter,the former directly enters the welfare loss functions.7[(~x i1¡x i1)=º]+¼1+(~g i1¡g i1)+(¼1¡¼e1)=h¯¤(1+½)1+¯¤(1+½)i³~F+~F¢i´+h¯¤(1+½)(P¤=P)1+¯¤(1+½)(P=P)i³¹º+²iº´=~K i1+(1+½)d i0¡d S i1+(¹+²i)=º;(3.2)where d Si1is the second-best debt level.The last equality can be checked bysubstituting(3.4)-(3.7)into(3.3)(all given below)and substituting the resulting expression into the last line of(3.2).For each of the outcomes,the terms that follow the factor in square brackets regulate the inter temporal allocation of the intertemporal government…nancing requirement.The coe¢cients of the common stochastic shock¹º(in the fourth column ofTable1,°2)di¤er in two ways from the coe¢cients of the common determinis-tic component of the intertemporal government…nancing requirement~F(in thesecond column of Table1,°0).The…rst di¤erence is with respect to the…rst-period,intra temporal,allocation of the government…nancing requirement overthe…nancing sources.The deterministic components of the government…nancing requirement are anticipated and thus correctly incorporated in expected in‡a-tion.The common shock,in contrast,is unanticipated and,hence,not taken intoaccount when in‡ation expectations are formed.The predetermination of the in-‡ation expectation is exploited by the central policymakers so as to…nance part ofthis common shock through an in‡ation surprise.Indeed,whereas the coe¢cientof¼1¡¼e1is zero in the second column in Table1,this coe¢cient is positive in the fourth column,indicating that part of the common shock is…nanced throughan in‡ation surprise in the…rst period.With surprise in‡ation absorbing part ofthe common shock,the output gap and the spending gap have to absorb a smallershare of this shock.In the second period,the allocation over the…nancing sources for the stochastic component¹is the same as for the deterministic component~F.The reason is that the…rst-period shock¹has materialized before second-period in‡ation expectations are formed.The e¤ect of¹on the second-period outcomes will thus be perfectly anticipated.Indeed,the share of¹that is transmitted into the second period through debt policy becomes part of the deterministic component of the second-period government…nancing requirement(when viewed from the start of the second period).The second way in which the coe¢cient of the stochastic shock¹di¤ers from the coe¢cient of~F,involves the inter temporal allocation of the government…-nancing requirement.In particular,the share of¹absorbed in the…rst period (relative to the second period)is larger than that of~F(¯¤(P¤=P)c1>¯¤c0and c1<c0,where c0and c1are de…ned in Table1).The reason is again that…rst-8period in‡ation expectations are predetermined when the stochastic shock hits. This enables the policymakers to absorb a relatively large share of the stochastic shock in the…rst period through an in‡ation surprise.The responses of the output and government spending gaps to~F¢i and²i di¤er from the responses to~F and¹.Since in‡ation is attuned to cross-country averages,it cannot respond to country-speci…c circumstances as captured by~F¢i and²i.Accordingly,taxes(the output gap)and the government spending gap have to fully absorb these country-speci…c components of the government…nancing requirements.3.2.Public debt policyThe solution for debt accumulation in the second-best equilibrium can be written as:d S i1=¹d e;S1+d¢;e;Si1+¹d d;S1+d±;S i1;(3.3) where¹d e;S 1=h~K1+(1+½)¹d0¡~K2i+(1¡¯¤)~K2¤;(3.4)d¢;e;S i1=h~K¢i1+(1+½)d¢i0¡~K¢i2i+(1¡¯¤)~K¢i2¤;n>1;(3.5) =0;n=1;¹d d;S 1="11+¯¤(1+½)(P¤=P)#¹º;(3.6)d±;S i1="11+¯¤(1+½)#²iº;n>1;(3.7) =0;n=1;where the superscript“S”stands for“second-best equilibrium”,the superscript “e”denotes the expectation of a variable,an upperbar above a variable indicates its cross-country average(except for variables carrying a tilde,like~K1,where the cross-country average is indicated by dropping the country-index),a super-script“¢”denotes an idiosyncratic deviation of a deterministic variable from its cross-country average(for example,~K¢i1´~K i1¡~K1),a superscript“d”denotes9the response to a common shock,a superscript“±”indicates the response to an idiosyncratic shock,and where¯¤´¯(1+½);(3.8)P´Â2=®¼+1=º2+1=®g;P¤´(Â+1)2=®¼+1=º2+1=®g:Hence,optimal debt accumulation(3.3)is the sum of two deterministic compo-nents and two stochastic components.The component¹d e;S1optimally distributes over time the absorption of the cross-country averages of the deterministic compo-nents of the government…nancing requirements.Therefore,it is common acrosscountries.The country-speci…c components d¢;e;Si1intertemporally distribute theidiosyncratic deterministic components of the government…nancing requirements. The common(across countries)component¹d d;S1represents the optimal debt re-sponse to the common shock¹,while d±;S i1stands for the optimal debt response to the country-speci…c shock,²i.The debt response to the common shock is less active than the response to the idiosyncratic shock(since P¤=P>1).The common in‡ation rate can exploit the predetermination of in‡ation expectations only in responding to the common shock,because the common in‡ation rate can not be attuned to idiosyncratic shocks.Hence,the share of the common shock that can be absorbed in the…rst period can be larger than the corresponding share of the idiosyncratic shock. Public debt thus needs to respond less vigorously to the common shock.4.Discretionary monetary policy with decentralized…scalpolicyThis section introduces two distortions compared with the second-best equilib-rium explored in the previous section.First,the CCB is no longer able to commit to monetary policy announcements.Second,…scal policy is decentralized to in-dividual governments,which may result in wasteful strategic interaction among heterogeneous governments.From now on,the timing of events in each period is as follows.At the start of the period,the institutional parameters are set.That is,an in‡ation target is imposed on the CCB for the coming period and,if applicable,the debt targets on the individual governments are set.The in‡ation target may be conditioned on the state of the world.In particular,the in‡ation target may depend on the average debt level in the union.7Furthermore,the debt target,which represents 7The optimal in‡ation target can either be optimally reset at the start of each period,or10the amount of public debt that a government has to carry over into the next period,may be shock-contingent.8After the institutional parameters have been set,in‡ation expectations are determined(through the nominal wage-setting pro-cess).Third,the shock(s)materialize.Fourth,taking in‡ation expectations as given,the CCB selects the common in‡ation rate and the…scal authorities simul-taneously select taxes and,in the absence of a debt target,public debt.Each of the players takes the other players’policies at this stage as given.Finally,public spending levels are residually determined.As a result,the CCB internalizes the e¤ect of its policies on the government budget constraints.This section explores the outcomes under pure discretion,i.e.in the absence of both in‡ation targets(i.e.,¼¤1=¼¤2=0)and debt targets.The complete derivation of the equilibrium is contained in Appendix B.The suboptimality of the resulting equilibrium compared to the second best motivates the exploration of in‡ation and debt targets in Section5.4.1.In‡ation,the output gap and the public spending gapTable2contains the solutions for the in‡ation rate,the output gap and the spend-ing gap.The main di¤erence compared to the outcomes under the second-best equilibrium(see Table1)is that,for a given amount of debt d i1to be carried over into the second period,expected…rst-period in‡ation(and,hence,seignior-age ifÂ>0)will be higher(compare the term between the square parenthe-ses in the second column and the second row of Table2with the correspond-ing term in Table1and observe that[Â(Â+1)=®¼]=S>(Â2=®¼)=P,where S´Â(Â+1)=®¼+1=º2+1=®g).The source of the higher expected in‡ation rate under pure discretion is the inability to commit to a stringent monetary policy,which yields the familiar in‡ation bias(Barro and Gordon,1983).The outcomes for in‡ation,the output gap and the spending gap deviate from the outcomes under the second-best equilibrium also because debt accumulation un-der pure discretion di¤ers from debt accumulation under the second best.These di¤erences are discussed below.4.2.Public debt policyGovernment i’s debt can,analogous to(3.3),be written as:d D i1=¹d e;D1+d¢;e;Di1+¹d d;D1+d±;D i1;(4.1)be determined according to a state-contingent rule selected at the beginning of the…rst period. These two alternative interpretations yield equivalent results.8Debt at the end of the second period is restricted to be zero.Hence,the second period features a debt target of zero.11where the superscript“D”is used to indicate the solution of the purely discre-tionary equilibrium with decentralized…scal policies and where¹d e;D 1=h~K1+(1+½)d0¡~K2i+[1¡¯¤(S¤=S)]~K2¤;(4.2)d¢;e;D i1=h~K¢i1+(1+½)d¢i0¡~K¢i2i+[1¡¯¤(Q=S)]~K¢i21+¯¤(1+½)(Q=S);if n>1;(4.3) =0;if n=1;¹d d;D 1="11+¯¤(1+½)(S¤=S)(P¤=S)#¹º;(4.4)d±;D i1="11+¯¤(1+½)(Q=S)#²iº;if n>1;(4.5) =0;if n=1;and whereS´Â(Â+1)=®¼+1=º2+1=®g;(4.6)S¤´Â(Â+1)=®¼+(Â+1)=(n®¼)+1=º2+1=®g;Q´[(n¡1)=n][Â(Â+1)=®¼]+1=º2+1=®g:4.2.1.Response to the common deterministic components of the gov-ernment…nancing requirementsPositive analysis:This subsection explores the solution for expected average debt¹d e;D1in(4.2). Whereas current in‡ation expectations are predetermined at the moment that debt is selected,future in‡ation expectations still need to be determined.A re-duction in debt reduces the future government…nancing requirement and,thus, the tax rate in the future.This,in turn,weakens the CCB’s incentive to raise future in‡ation in order to protect employment.Hence,by restraining debt ac-cumulation,governments help to reduce future in‡ation expectations,which are endogenous from a…rst-period perspective.The reduction in future in‡ation expectations implies a lower in‡ation bias in the future.In other words,asset accumulation is an indirect way to enhance the commitment of a central bank to low future in‡ation.12。
美丽心灵中英文字幕
美丽心灵 A Beautiful MindMathe maticians won the war.是数学家赢得了二次大战。
Mathematicians brokethe Japanese codes-是数学家破解了日本的密码——and built the A-bomb.建造了原子炸弹。
Mathematicians...like you.就是……像你们这样的数学家。
The stated goal of the Sovietsis global Communism.苏联所定的目标是让共产党布遍全球。
In medicine or economics,无论在医药还是经济上,in technology or space,在科技或太空技术上battle lines are being drawn. 战线已经清楚了。
To triumph,we need results- 想要胜利,我们就需要有成果——publishable,applicable results.可以发表,实用的成果。
Now who among youwill be the next Morse?你们当中谁会成为第二个莫尔斯?The next Einstein?第二个爱因斯坦?Who among you will be the vanguard...你们当中谁会成为……of democracy, freedom,and discovery?民主、自由和探索的先锋?Today, we be queath America's future...今天,我们将美国的未来……into your able hands.交于你们的手中。
Welcome toPrinceton,gentlemen.各位,欢送来到普林斯顿大学。
It's not enough Hansen wonthe Carnegie Scholarship.汉森得了卡内基奖学金还不满足。
时空依赖 英语表述
时空依赖英语表述Temporal and Spatial Dependencies.Temporal and spatial dependencies are two fundamental concepts that underlie our understanding of the interconnectedness and evolving nature of phenomena in various domains, ranging from physics to social sciences. These dependencies refer to the relationships between events or objects that are influenced by time and space, respectively.Temporal dependency is the relationship between events or observations that occur at different points in time. It encapsulates the idea that what happens at one time can influence what happens at another time. This is a crucial consideration in areas like meteorology, where the weather patterns of today can inform predictions for tomorrow. In the realm of finance, temporal dependencies are essential for understanding how market trends evolve over time, influencing investment decisions. Similarly, inneuroscience, temporal dependencies underlie our understanding of how neural activity patterns change over time, leading to the perception of motion or the processing of information.Spatial dependency, on the other hand, refers to the relationships between events or objects that are influenced by their physical proximity or location. This concept is central to fields like geography, where spatial patterns of population distribution, resource availability, and environmental factors influence regional development. In ecology, spatial dependencies are key to understanding how species interactions and habitats are distributed across landscapes. Urban planning also relies heavily on spatial dependencies, as they determine how cities grow, the flow of traffic, and the distribution of services.Temporal and spatial dependencies often coexist and intersect in complex systems. For instance, in climate science, changes in temperature and precipitation patterns over time are influenced by spatial factors like the distribution of land masses, ocean currents, and elevation.In social networks, the spread of information or trends can be influenced by both temporal factors like the time of day or week and spatial factors like the geographic location of users.The analysis of temporal and spatial dependencies requires sophisticated statistical techniques and models. Time series analysis, for instance, is a widely used method for studying temporal dependencies by examining how variables change over time. Spatial analysis techniques, such as geographic information systems (GIS) and spatial statistics, allow researchers to identify patterns and relationships between events or objects based on their spatial arrangement.In conclusion, temporal and spatial dependencies are fundamental to our understanding of the world. They underlie the interconnectedness of events and objects, shaping the evolution of systems and influencing our decisions and actions. As we continue to explore and model these dependencies, we gain deeper insights into thecomplexity of the world and the ability to make more informed predictions and decisions.。
On a Factorization of Symmetric Matrices and Antilinear Symmetries
2
3
Motivation: Consequences of antilinear symmetries
Consider a diagonalizable linear operator H : H → H acting in a finite-dimensional complex inner-product space H with inner-product ( , ). Let n label the eigenvalues En of H , µn be the multiplicity of En , and ψn,a be the eigenvectors corresponding to the eigenvalue En where a ∈ {1, 2, · · · , µn } is the degeneracy label. Then it is well-known [3] that the adjoint ˜n of H ∗ are complex conjugate of those of H , i.e., H ∗ of H is diagonalizable; the eigenvalues E ˜n = E ¯n ; the multiplicity of E ˜n is equal to µn ; and one can choose the eigenvectors φn,a of H ∗ E in such a way that for all spectral labels m, n and degeneracy labels a, b, (φn,a, ψn,a ) = δn,m δa,b . Clearly, both sets of eigenvectors ψn,a of H and eigenvectors φa,n of H ∗ form bases of H; {ψn,a , φn,a } is a complete biorthonormal system. Recently [6], we have shown that if the eigenvalues of H are real, then H has an antilinear symmetry. More generally, we proved the following theorem. Theorem 1: The presence of an antilinear symmetry of H is a necessary and sufficient condition for the eigenvalues of H to either be real or come in complex conjugate pairs. The proof of Theorem 1 uses the following lemma. Lemma 1: Every diagonalizable linear operator H : H → H acting in a finitedimensional complex inner-product space H is T -Hermitian, H ∗ = T H T −1 , for some Hermitian, invertible, antilinear operator T : H → H. It turns out [6] that any such T may be expressed in terms of the eigenvectors φn,a of H ∗ according to
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a rXiv:solv-int/9922v131Ja n1999On time-dependent symmetries and formal symmetries of evolution equations Artur Sergyeyev Institute of Mathematics of NAS of Ukraine,3Tereshchenkivs’ka Str.,252004Kyiv,Ukraine E-mail:arthurser@imath.kiev.ua,arthur@apmat.freenet.kiev.ua Abstract We present the explicit formulae,describing the structure of symme-tries and formal symmetries of any scalar (1+1)-dimensional evolution ing these results,the formulae for the leading terms of com-mutators of two symmetries and two formal symmetries are found.The generalization of these results to the case of system of evolution equations is also discussed.1Introduction It is well known that provided scalar (1+1)-dimensional evolution equation pos-sesses the infinite-dimensional commutative Lie algebra of time-independent gen-eralized (Lie –B¨a cklund)symmetries,it is either linearizable or integrable via inverse scattering transform (see e.g.[1],[2],[3]for the survey of known results and [4]for the generalization to (2+1)dimensions).The existence of such alge-bra is usually proved by exhibiting the recursion operator [3]or mastersymmetry [5].But in order to possess the latter,the equation in question must have some (possibly nonlocal)time-dependent symmetries.This fact is one of the main reasons of growing interest to the study of whole algebra of time-dependent symmetries of evolution equations [6],[7].However,to the best of author’s knowledge,there exist almost no results,describing the structure of this algebra for the generic scalar evolution equation (even in 1+1dimensions)without any initial conjectures about the specific properties of this equation,like the existence of formal symmetry,Lax pair,mastersymmetry,etc.1Although Vinogradov et al.[10]had outlined the generalscheme of study of local and nonlocal symmetries of evolution equations,it remained unrealized in its general form until now.In this paper we put the part of this scheme into life and go even ly,in Theorems 1and 2we describe the general structure of local sym-metries and formal symmetries of scalar evolution equation,and in Theorems 3and 5we present the formulae for the leading terms of the commutators of two symmetries (of sufficiently high order)and of two formal symmetries.We present also the generalization of these results to the case of systems of evolution equations.2Basic definitions and known factsWe consider the scalar1+1-dimensional evolution equation∂u/∂t=F(x,t,u,u1,...,u n),n≥2,∂F/∂u n=0,(1)where u l=∂l u/∂x l,l=0,1,2,...,u0≡u,and the symmetries of this equation, i.e.the right hand sides G of evolution equations∂u/∂τ=G(x,t,u,u1,...,u k),(2)compatible with equation(1).The greatest number k such that∂G/∂u k=0is called the order of symmetry and is denoted as k=ord G.If G is independent of u,u1,...,we assume that ord G=0.Let S(k)be the space of symmetries of order not higher than k of(1)and S= ∞j=0S(k).S is Lie algebra with respect to the so-called Lie bracket[1],[3]{h,r}=r∗(h)−h∗(r),where for any sufficiently smooth function f of x,t,u,u1,...,u s we have intro-duced the notationf∗=si=0∂h/∂u i D i,∇f=∞ i=0D i(f)∂/∂u i,where D=∂/∂x+∞i=0u i+1∂/∂u i.G is symmetry of Eq.(1)if and only if[3]∂G/∂t=−{F,G}.(3) In many examples Eq.(1)is quasilinear,so letn0= max(1−j,0),if∂F/∂u n−i=φi(x,t),i=0,...,j,2otherwise.(4)It is known[3]that for any G∈S,ord G=k≥n0,we have∂G/∂u k=c k(t)Φk/n,(5) where c k(t)is a function of t andΦ=∂F/∂u n.It is also well known[1]that for any sufficiently smooth functions P,Q of x,t,u,u1,u2,...the relation R={P,Q}impliesR∗=∇P(Q∗)−∇Q(P∗)+[Q∗,P∗],(6)where∇P(Q∗)≡∞i,j=0D j(P)∂2QIn particular,Eq.(3)yields∂G∗/∂t≡(∂G/∂t)∗=∇G(F∗)−∇F(G∗)+[F∗,G∗].(7) Equating the coefficients at D s,s=0,1,2,...on right and left hand sides of Eq.(7),we obtain∂2G∂u m∂u l −k r=0D r(F)∂2G∂u iD i+j−l ∂G∂u jD i+j−l ∂Fp!(q−p)!and we assume that1/p!=0for negative integer p.Let us also remind some facts concerning the formal series in powers of D (see e.g.[2],[4]for more information),i.e.the expressions of the formH=mj=−∞h j(x,t,u,u1,...)D j.(9)The greatest integer m such that h m=0is called the degree of formal series H and is denoted by deg H.For any formal series H of degree m there exists unique(up to the multiplication by m-th root of unity)formal series H1/m of degree1such that(H1/m)m=H.Now we can define the fractional powers of H as H l/m=(H1/m)l for all integer l.The key result here is that[H p/m,H q/m]=0(10) for all integer p and q.The formal symmetry of Eq.(1)of rank l is the formal series R,satisfying the relation[2]deg(∂R/∂t+∇F(R)−[F∗,R])≤deg F∗+deg R−l.(11) The commutator of two formal symmetries of ranks l and m obviously is again a formal symmetry of rank not lower than min(l,m),and thus the set F S r of all formal symmetries of given equation(1)of rank not lower than r is a Lie algebra.Like for the case of symmetries,we shall denote by F S(k)r the set of formal symmetries of degree not higher than k and of rank not lower than r. Note that if G is symmetry of order k,then by virtue of Eq.(7)G∗is the formal symmetry of degree k and rank k+n−deg∇G(F∗).33Explicit form of symmetries and formal sym-metriesIn this section we shall consider a symmetry G of order k≥n0.The successive solving of Eq.(8)for l=k+n−1,...,n0+n−1yields Eq.(5)and∂G/∂u i=c i(t)Φi/n+k p=i+1[p−in2c k(t)D−1(Φ−1−1/n˙Φ)F(k−n+1)/n∗+(1/n)˙c k(t)D−1(Φ−1/n)F(k−n+1)/n∗,(14) where d i(t)are some functions of t(in fact they are linear combinations ofc max(k−n+1,n0)(t),...,c k(t))and N is some formal series,deg N<max(k−n+1,n0).Likewise,for n0≤k≤n+n0−2Eq.(14)remains true,if two last terms on its right hand side are rejected.Dot here and below stands for the partial derivative with respect to t.The analysis of Eq.(11),similar to the above analysis of Eq.(7),yields Theorem2For any formal symmetry R of(1)of degree k and of rank r>nR=˜R+k j=k−n+1d j(t)F j/n∗+kTheorem 3Let P,Q ∈S/S (n +n 0−2),ord P =p ,ord Q =q .By virtue of Eq.(5)∂P/∂u p =c p (t )Φp/n ,∂Q/∂u q =d q (t )Φq/n .Then ord {P,Q }≤p +q −n and{P,Q }=1n u p +q −n q ˙c p (t )d q (t )−pc p (t )˙d q (t ) +˜R,(16)where ord ˜R<p +q −n .Corollary 1For all integer p ≥n +n 0−1the spaces S (p )are invariant under the adjoint action of S (n ),i.e.the Lie bracket of any symmetry from S (p )with any symmetry from S (n )again belongs to S (p ).Theorem 4For all p =0,...,n S (p )are Lie subalgebras in S .Note that for p =0,1the result of Theorem 4is well known,while for p =2,...,n it is essentially new.Theorem 3shows that Lie algebra S has Virasoro type structure (if we forget about low order symmetries and consider just the leading terms of symmetries).In particular,one may easily establish the existence of Virasoro (or hereditary)algebra [5],[6]of time-independent symmetries and mastersymmetries for many integrable equations (1),using Eq.(16).More generally,Theorem 3is very use-ful in the proof of existence of infinite number of symmetries for given evolution equation,starting from few initially found ones and analyzing their commuta-tors,as described in [10].Note that for particular cases of KdV and Burgers equations it was proved in [10].Likewise,for formal symmetries we have proved the following results:Theorem 5Let P ,Q be formal symmetries of Eq.(1),deg P =p ,deg Q =q ,and the ranks of P and Q are greater than n .By virtue of Theorem 2P =c p (t )F p/n ∗+˜P and Q =d q (t )F q/n ∗+˜Q,deg ˜P <p ,deg ˜Q <q .Then deg[P ,Q]≤p +q −n and[P ,Q]=−1n ∗ q ˙c p (t )d q (t )−pc p (t )˙d q (t ) +˜R ,(17)where deg ˜R<p +q −n .Corollary 2For all integer p the spaces F S (p )r are invariant under the adjointaction of F S (n )r ,provided r >n .Corollary 3For all integer p ≤n ,r >n F S (p )r are Lie subalgebras in F S r .55Some possible generalizationsOur results may be easily generalized to the case of systems of evolution equa-tions of the form(1),when u,u1,u2,...,F,G,P,Q become m-component vec-tors,while c p(t),d q(t)become m×m matrices,which should commute with the m×m matrixΦ=∂F/∂u n,etc.(see[2]for more information).Namely,the second part of Theorem1,concerning the symmetries of order k,n0≤k≤n+ n0−2,Theorem3,Theorem4for n0≤1,Corollary1,Corollary3for p<n hold true,provided all the eigenvalues ofΦare distinct.The part of Theorem1,con-cerning the symmetries of order k>n+n0−2,Theorems2,4,5,Corollaries2and 3hold true if,in addition to the above,detΦ=0.For the case,when detΦ=0, we have proved instead of thefirst part of Theorem1the following result: Theorem6If detΦ=0and all the eigenvalues ofΦare distinct,for any symmetry G of system(1)of order k>n+n0−2G∗=N+kj=k−n+2d j(t)F j/n∗,(18)where d j(t)are some matrices,commuting withΦ,and N is some formal series (with matrix coefficients),deg N<k−n+2.In its turn,Theorem2is replaced by the followingTheorem7If detΦ=0and all the eigenvalues ofΦare distinct,for any formal symmetry R of system(1)of degree k≥0and of rank r>nR=˜R+kj=max(k−n+2,0)d j(t)F j/n∗,(19)where d j(t)are some matrices,commuting withΦ,and˜R is some formal series (with matrix coefficients),deg˜R<max(k−n+2,0).As afinal remark,let us note that Theorems1–7and Corollaries1–3may be also extended(under some extra conditions)to the symmetries and formal symmetries,involving nonlocal variables.We shall discuss this in more detail in separate paper.AcknowledgementsI am sincerely grateful to Profs.B.Fuchssteiner and V.V.Sokolov for stimu-lating discussions.References[1]V.V.Sokolov,Russian Math.Surveys43,,no.5,165(1988).6[2]A V Mikhailov,A B Shabat and V V Sokolov in What is integrability?,ed.V E Zakharov(Springer,N.Y.,1991).[3]P Olver,Applications of Lie Groups to Differential Equations(Springer,N.Y.,1986).[4]A.V.Mikhailov,R.I.Yamilov,J.Phys.A31,6707(1998).[5]B.Fuchssteiner,Progr.Theor.Phys.70,1508(1983).[6]B.Fuchssteiner,J.Math.Phys.34,5140(1993).[7]W.X.Ma,P.K.Bullough,P.J.Caudrey and W.I.Fushchych,J.Phys.A30,5141(1997).[8]B.Flach,Lett.Math.Phys.17,321(1989).[9]Magadeev B A1994St.Petersburg Math.J.5,,no.2,345(.)[10]A M Vinogradov,I S Krasil’shchik,V V Lychagin,Introduction toGeometry of Nonlinear Differential Equations(Nauka,Moscow,1986).7。