The Algebra of Conjugacy Classes in Symmetric Groups and Partial Permutations
大学生选课现象英语作文
大学生选课现象英语作文The Phenomenon of Course Selection Among College Students。
In recent years, the phenomenon of course selection among college students has attracted increasing attention. With the development of higher education and the diversification of majors, students are facing more choices when it comes to selecting courses. This has led to a variety of behaviors and attitudes among college studentsin terms of course selection.One of the most common behaviors among college students is the tendency to choose courses based on their interests and career goals. Many students prioritize courses that align with their passions and future career plans,believing that these courses will help them achieve success in their chosen field. For example, a student who is interested in computer science may choose to take coursesin programming and software development, while a studentwho is passionate about literature may opt for courses in creative writing and literary analysis.However, not all students approach course selection in this way. Some students choose courses based on their perceived difficulty or workload, opting for easier courses to maintain a high GPA or reduce their academic stress.This can lead to a mismatch between a student's interests and the courses they take, resulting in a lack ofmotivation and engagement in their studies.Another factor that influences course selection among college students is peer pressure. Students may choose courses based on recommendations from friends or classmates, or to fit in with a certain social group. This can lead to students taking courses that they are not interested in or that do not align with their career goals, simply toconform to the expectations of others.In addition, the availability of courses and scheduling conflicts can also impact course selection among college students. Some students may be limited in their coursechoices due to prerequisites or course availability, leading them to make compromises in their course selection. Others may struggle to balance their course load with other commitments, such as part-time jobs or extracurricular activities, leading them to prioritize courses that fit their schedule rather than their interests.Overall, the phenomenon of course selection among college students is complex and multifaceted. While some students prioritize their interests and career goals when choosing courses, others may be influenced by factors such as perceived difficulty, peer pressure, and scheduling conflicts. It is important for college students tocarefully consider their course selections and make choices that align with their passions and future aspirations, rather than simply following the crowd or taking the easy way out. By taking a thoughtful and intentional approach to course selection, students can maximize their learning experience and set themselves up for success in their academic and professional endeavors.。
Twisted vertex representations via spin groups and the McKay correspondence
TWISTED VERTEX REPRESENTATIONS VIA SPIN GROUPS AND THE MCKAY CORRESPONDENCE
IGOR B. FRENKEL, NAIHUAN JING, AND WEIQIANG WANG Abstract. We establish a twisted analog of our recent work on vertex representations and the McKay correspondence. For each finite group Γ and a virtual character of Γ we construct twisted vertex operators on the Fock space spanned by the super spin characters of the spin wreath products Γ ≀ Sn of Γ and a double cover of the symmetric group Sn for all n. When Γ is a subgroup of SL2 (C) with the McKay virtual character, our construction gives a group theoretic realization of the basic representations of the twisted affine and twisted toroidal algebras. When Γ is an arbitrary finite group and the virtual character is trivial, our vertex operator construction yields the spin character tables for Γ ≀ Sn .
A Calculus for Predicative Programming Emil Sekerinski ¢
A Calculus for Predicative ProgrammingEmil SekerinskiForschungszentrum Informatik Karlsruhe,Haid-und-Neu Strasse10-14,7500Karlsruhe,Germany,sekerinski@fzi.deAbstract.A calculus for developing programs from specifications written aspredicates that describe the relationship between the initial andfinal state is pro-posed.Such specifications are well known from the specification language Z.Allelements of a simple sequential programming notation are defined in terms ofpredicates.Hence programs form a subset of specifications.In particular,sequen-tial composition is defined by’demonic composition’,nondeterministic choiceby’demonic disjunction’,and iteration byfixed ws are derived whichallow proving equivalence and refinement of specifications and programs.Theweakest precondition is expressed by sequential composition.The approach iscompared to the predicative programming approach of E.Hehner and to otherrefinement calculi.1IntroductionWe view a specification as a predicate which describes the admissiblefinal state of a computing machine with respect to some initial state.A program is a predicate restricted to operators which can be implemented efficiently.Hence the task of a programmer is to transform a specification written in the rich mathematical notation into a corresponding one expressed in the restricted programming notation,perhaps by a series of transforma-tion steps.In this report,the programming notation consists of assignment,sequential composition,conditional,nondeterministic choice,variable declaration,and iteration.The predicative programming approach was originally proposed by Eric Hehner in [5]for both a sequential and concurrent programming notation,and later refined in[6], [7],and[8].The benefit of this approach is that there are no separated worlds for spec-ification and programming with cumbersome proof rules for the transition from spec-ification to programs;rather the laws can be used for development of programs from specifications,for the transformation of programs to equivalent,perhaps more efficient ones,and for deriving properties of programs.By using programming operators like the conditional for specifying as well,we can also get clearer specifications.Another benefit is that when presenting the calculus,we can start with the specification notation and gradually introduce the programming operators by their definition.For specifications we use a style which is similar to the specification language Z [16].Specifications are basically predicates relating the initial to thefinal state,given by the values of primed and unprimed symbols respectively.We will use the Z notation whenever appropriate,for example for the predicates and for the refinement relation. However,as our aim are compact calculations,we refrain form using the graphical conventions for the layout.We also ignore the typing problems and rather concentrate on the definitions and properties of the’control structures’.It should be also noted that we prefer to view predicates as boolean valued functions and will make use of quantifications over predicates.The calculus presented here allows stating the equivalence of two specifications (or programs),not just refinement.When developing a program from a specification by a series of transformations,we like to state for each intermediate result whether it is equivalent to or a refinement of the previous one,even though only refinement is required(similarly as when proving that one real expression is less than another real expression).Stating equivalence expresses that no premature design decisions have been made.However,it should be clarified what the equivalence of an executable program with a specification does mean:For some initial state,a specification is either defined,in which case it does relate to somefinal state,or is undefined.A program,when executed, does either terminates with some valid result,performs some undefined operation(like indexing out of range),or does not terminate at all.From our point of view nontermina-tion is as undesirable as an undefined operation.Hence we do not distinguish them and represent both by undefinedness.This allows us to define sequential composition by’demonic composition’and non-deterministic choice by’demonic disjunction’.When comparing relational composi-tion and disjunction with sequential composition and nondeterministic choice,it turns out that the former two’deliver a result’whenever a sensible result exists.They are therefore called angelic operators.However,they cannot be implemented effectively.In contrast,the latter two are undefined whenever the possibility of failure exists.They are called demonic operators,as if several possibilities for execution exist,the implementor is free to choose one arbitrarily(and we have to be prepared that always the worst one is chosen).This approach leads to a nice way for expressing Dijkstras[2]weakest precondi-tions wp P b:Let b be a condition,i.e.a specification over the initial state only.P generalized to the case that it is a specification,not necessarily a program.The meaning of wp P b is given by sequential composition P;b.This is made possible as the condi-tion b is just a specification and sequential composition is defined for any specification. As a consequence,the definition of the sequential composition and the conditional by weakest preconditionswp P;Q b wp P wp Q bwp if c then P else Q end b c wp P b c wp Q bcorrespond to the associativity of sequential composition and distributivity of sequential composition over the conditional.2P;Q;b P;Q;bif c then P else Q end;b if c then P;b else Q;b endAn obvious advantage is that we saved introducing a new function.However,a deeper advantage is that by mere notation we save applications of theorems like associativity and make theorems look simpler and easier to memorize.The following section introduces all programming operators except iteration.Each definition is followed by a number of properties of the operator in question.The third section introduces the refinement ordering and states relationships between the pro-gramming operators and the refinement ordering.The fourth section discusses weakest preconditions.Iteration is treated in thefifth section:First the definition in terms offixed points is given,its soundness established,and the main iteration theorem derived.The main iteration theorem makes use of weakest preconditions.The last section presents a small example of the use of the calculus,in particular of the main iteration theorem.2Straight Line Programming OperatorsBasic Notation(”Basics”)The boolean values are written as and,the boolean operators are written as,, ,,with their usual meaning,binding strongest,and binding weaker, and binding weakest.Let P Q stand for predicates.For the universal and existential quantifiers,we will also use the”restricted”forms:d P Q d P Qd P Q d P Qwhere d is the dummy over which the quantification ranges,with the possibility of quantifying over list of dummies.The substitution of a free symbol s in P by some expression e is written as P s:e,and the simultaneous substitution of symbols of the list S by the corresponding ones of the list of expressions E as P S:E.The everywhere operator P stands for the universal quantification of the symbols of interest in P.We write and over predicates for the universal equivalence and universal implication:P Q P QP Q P QThey bind weaker than all other boolean operators.The context of a specification is a list of symbols,called the variables.For a variable v we allow priming by v,and similarly for lists of variables.A specification describes how the initial values of the variables relate to theirfinal values.Hence in the context V,a specification is written as a predicate over V,V,and possibly some(unprimed)constants.Note that,although a specification can only be understood with respect to a context,we will leave the context in this paper usually implicit.3A condition is a specification in which no primed symbols occur,i.e.which does not say anything about thefinal values of the variables.For a condition b,b stands for that condition with all the free(unprimed)variables of the context primed.Throughout the paper,P Q R X Y stand for specifications,b c for conditions,V for the current context,v for a variable(element of the context V),and x y for symbols not in V.An example of a condition is the domain∆P of a specification P:∆P V PThe domain of a condition is the condition itself.The domain operator distributes over disjunctions but not over conjunctions.However,if one of the conjuncts is a condition, it can be moved out of the domain:(1)∆b P b∆PThe void specification II(also called skip)leaves all variables of the context unmodified: II V VRelational composition of specifications is defined by identifying thefinal state of the first component with the initial state of the second component:P Q V P V:V Q V:VBy convention,∆binds as strong as and weaker than and but stronger than =and.Relational composition has zero,identity II,is associative,and distributes through disjunction in both directions.The domain of the relational composition can be ”pushed”into the second operand:(2)∆P Q P∆QFor conjunctions with conditions,following laws hold:(3)b P Q b P Q(4)P b Q P b QFor the purpose of defining sequential composition,we introduce the condition P b. Informally,we can think of P b as characterizing those initial states which only relate tofinal states satisfying b,if they relate to any state at all.P b V P bThe subsequent laws about can be proved by predicate calculus:(5)P b P b P b∆P(6)P b c P b P cIn the sequel,we will visit each programming operator in turn and uncover many laws holding for each operator.4Assignment(”:=”)The assignment v:e changes variable v to e and leaves all other variables of the context unmodified.v must be an element of the context.v:e II v:eWe assume that the expression e is everywhere defined,therefore:(1)∆v:eSequential Composition(”;”)The sequential composition P;Q means thatfirst P is executed,then Q.If P is nondeter-ministic,Q must be defined whatever choice in P is taken.Hence P;Q behaves like the relational composition restricted to those initial states which only lead to intermediate states for which Q is defined.P;Q P∆Q P QSequential composition is assigned the same binding power as””.P;Q is defined if P is defined and P leads to a state for which Q is defined.(1)∆P;Q∆P P∆QProof L.H.S.∆P∆Q P Q by def.”;”P∆Q∆P Q by(1)under”Basics”P∆Q P∆Q by(2)under”Basics”R.H.S.by(5)under”Basics”Sequential composition has zero,identity II,and is associative.(2)P;;P(3)P;II II;P P(4)P;Q;R P;Q;RAssociativity is proved in the appendix.In general,sequential composition does neither distribute through disjunction nor conjunction.However,if one of the conjuncts is a condition,following theorems hold:(5)b P;Q b P;QProof L.H.S.b P∆Q b P Q by def.”;”b P∆Q b P Q by(3)under”Basics”P∆Q b P Q as for any c:b P c b P c =R.H.S by def.”;”(6)P;b Q P b P;Q5Proof L.H.S.P∆b Q P b Q by def.”;”P b∆Q P b Q by(1)and(4)under”Basics”P∆Q P b P b Q by(6)and(3)under”Basics”P∆Q P b P Q as for any b:P b P bR.H.S.by(3)under”Basics”,def.”;”Sequential compositions with assignments can be simplified as follows:(7)v:e;P P v:eConditional(”if”)The conditional”if b then P else Q end”behaves like P if b initially holds,and as Q if b does not initially hold.The choice between P and Q depends only on b.if b then P else Q end b P b Q(1)∆if b then P else Q end if b then∆P else∆Q endThere are many simple laws for manipulating conditionals.We give some which will be needed later on.(2)b if b then P else Q end b P(3)b if b then P else Q end b Q(4)b if c then P else Q end if c then b P else b Q end(5)if b then P else Q end if b then b P else b Q end(6)if b then P else P end P(7)if b then P else Q end;R if b then P;R else Q;R endLaws(2)to(6)are best proved by direct manipulations in the predicate calculus,law(7)by case analysis,which is expressed as follows:(8)”Principle of case analysis”P Q R P R Q R P R QFor the proof of law(7),we distinguish the cases”b”and”b”.We consider thefirst case only,as the second follows the same pattern.Proof b if b then P else Q end;R b if b then P;R else Q;R endb if b then P else Q end;R b if b then P;R else Q;R endby(5)under”;”b P;R b P;R by(2)by(5)under”;”We will also use the shorthand”if b then P end”:if b then P end if b then P else II end6Choice(””)The binary choice P Q means that initially either P or Q is chosen for execution. As we have no control over the choice,we must be prepared for the worst case in the following sense:P Q is only defined if both P and Q are defined,and if defined,the result is either that of P or Q.P Q∆P∆Q P Q(1)∆P Q∆P∆QProof L.H.S.∆∆P∆Q P Q by def.””∆P∆Q∆P Q by(1)under”Basics”∆P∆Q∆P∆Q∆distributes over=w of absorption By convention,””binds as strong as””and””.Binary choice has zero,is idem-potent,symmetric(which all follows immediately from the definition),and associative.(2)P P(3)P P P(4)P Q Q P(5)P Q R P Q RProof L.H.S.∆P∆Q R P Q R by def.””∆P∆Q∆R P∆Q∆R Q R by(1),def.””∆P∆Q∆R P Q R by pred.calc.=R.H.S.by repeating the argument Furthermore,restricting one of the operands by a condition is the same as restricting the whole choice by the condition.(6)b P Q b P QProof L.H.S.∆b P∆Q b P Q by def.””b∆P∆Q b P Q by(1)under”Basics”R.H.S.by pred.calc.,def.””Sequential composition distributes through binary choice in both directions.The proofs are given in the appendix.(7)P;Q R P;Q P;R(8)P Q;R P;R Q;RThe following two laws express that choosing between P and Q under a condition is the same asfirst choosing and then evaluating the condition.7(9)if b then P Q else R end if b then P else R end if b then Q else R end(10)if b then P else Q R end if b then P else Q end if b then P else R end Finally,binary choice distributes through the conditional.(11)if b then P else Q end R if b then P R else Q R endThe last three laws are most easily proved by case analysis.The unrestricted choice x P chooses the initial value of x in P arbitrarily.We assume that x is not in the current context.x P x∆P x PThe symbol x is bound by the choice.The rules for renaming bound symbols of quan-tifiers apply here as well.The choice x P is defined only in those initial states for which P will accept any value of x.(12)∆x P x∆PWe give some laws about unrestricted choice without proof.The order by which the value of two symbols are chosen does not matter.(13)x y P y x PChoosing the value of x and then choosing between P and Q is the same asfirst choosing between P and Q and then the value of x.(14)x P Q x P x QChoosing a value for x and accepting any(final)value of y in P is equivalent to accept-ing any value of y and choosing a value for x.(15)x y P y x PFinally if x is not free in P,following laws for sequential composition hold:(16)x P;Q P;x Q(17)x Q;P x Q;PVariable Declaration(”var”)The variable declaration var x P extends the current context V by x.We assume that x is not in the current context.The initial value of x is arbitrary and anyfinal value is acceptable.var x P x x PBoth x and x are bound by the variable declaration.var x P is defined if,for any initial value of x,P is defined.8(1)∆var x P x∆PThe order,in which variables are declared,does not matter:(2)var x var y P var y var x PProof L.H.S.x x y y P by def.”var”x y x y P by(15)under””y x y x P by(13)under””,pred.calc.y y x x P by(15)under””=R.H.S.by def.”var”We give some laws about variable declarations without proof.Let R be a specification which does not depend on x being in the current context.(3)var x P Q var x P var x P(4)var x R;P R;var x P(5)var x P;R var x P;R(6)var x x:e II3The Refinement Relation(””)We define an ordering relation on specifications with the intention that P Q holds if Q is an acceptable replacement for P:When expecting P,we cannot tell whether Q has been executed in place of P.P Q∆P∆Q Q P∆P∆Q states that Q has to be defined where P is and∆P Q P states that within the domain of P,Q is at least as deterministic as P.Outside the domain of P, Q may behave arbitrarily.We assign the same lowest binding power as and. Our confidence in the above definition is reassured by the following basic law about, which we could have taken as the definition as well.(1)P Q P Q PThis means that Q serves all the purposes P does,but it may serve more.Hence we call Q better than P and P worse than Q.The refinement relation is a partial order in that it is reflexive,antisymmetric,transitive,and it has as bottom element.(2)P P(3)P Q Q P P Q(4)P Q Q R P R(5)P9The proofs are straightforward using theorem(1)and the laws given under.There are many laws about,some of which are given below.Their use in program development is for restricting the nondeterminism and for enlarging the domains of specifications.(6)b P P(7)P Q P(8)P Q R P Q P RAgain,they are most easily proved using(1).All the programming operators introduced in the last section are monotonic with respect to in all their specification operands:(9)P QP;R Q;RR;P R;Qif b then P else R end if b then Q else R endif b then R else P end if b then R else Q endP R Q RR P R Qx P x Qvar x P var x QThe proof is most easily carried out using following theorem.Let R X be a specifica-tion over X.(10)R P Q R P R Q R X monotonic in XProof Assuming R distributes over,we calculate:X YX Y X by(1) R X Y R X by Leibnitz R X R Y R X by assumption R X R Y by(1)Theorem(9)follows from the distributivity of over all the programming operators as shown in the last section.4Weakest Precondition(”wp”)Informally,the weakest precondition of a specification P with respect to a condition b characterizes those initial states,for which P is defined and which only relate to states within b.The following theorem supports the informal claim that P;b is the weakest precondition of P with respect to b.(1)P;b P b∆P10Proof L.H.S.P∆b P b by def.”;”P b P b as∆b b =R.H.S.by(5)under”Basics”Before further elaborating the properties of weakest preconditions,we give two small theorems about conditions,which will be useful in proofs.(2)b c b c(3)b c b cWe further underpin the correspondence of P;b and wp P b by investigating Dijkstras ”healthiness”properties.The”law of the excluded miracle:wp P”translates to P;,which follows from the fact that is zero of”;”.The monotonicity of wp P b in b with respect to implication is expressed as follows:(4)b c P;b P;cProof L.H.S.b c by(2) P;b P;c as”;”-monotonicR.H.S.by(2) Now consider the property”wp P b c wp P b wp P c”,which translates to (5)P;b c P;b P;cRather than proving this theorem we prove the following generalization,which ex-presses that P;b Q behaves as P;Q restricted to the weakest precondition of P with respect to b.(6)P;b Q P;b P;QProof L.H.S.P b P;Q by(6)under”;”P b∆P P;Q as P;Q∆P =R.H.S.by(1) For practical program development,it is important to be able to calculate the weakest precondition of a given specification with respect to some postcondition.Here we give the laws for weakest preconditions of the programming operators.We assume that x is not in the current context and x is not free in b.(7);b(8)II;b b(9)x:e;b b x:e(10)P;Q;b P;Q;b(11)if c then P else Q end;b if c then P;b else Q;b end11(12)P Q;b P;b Q;b(13)x P;b x P;b(14)var x P;b x P;bLaws(7)to(11)follow directly from laws given in earlier w(12)follows from the distributivity of;over and property(3).For(13)we observe:Proof L.H.S.x P;b by(17)under ∆x P;b for any b:∆b b=R.H.S.by(12)under The proof of(14)follows the same pattern.Finally we state that the weakest precondi-tion with respect to is the domain:(15)∆P P;Our use of weakest preconditions will be for proving properties of iterations.5IterationIn this section we define the iteration”while b do P end”,show that it is well defined, and give the main iteration theorem.The next section applies the main iteration theorem to the linear search.For the definition of the iteration we observe,that the body P may be any specification,and hence unboundedly nondeterministic.It is known that unbounded nondeterminism leads to noncontinuity,which rules out the definition of iteration as a limit of a countable sequence of specifications.Hence,we define the iteration as afixed point based on the refinement relation as a partial order with bottom element.We give a self-contained account of the theory.Let W stand for”while b do P end”.As”W if b then P;W end”is an essential property of W,we like to define the iteration W as the solution of the recursive equation (*)Y if b then P;Y endHowever,in case the iteration does not terminate for some states,there may be many solutions.Consider for example”while do II end”:any Y will solve(*).Having de-cided that nontermination is represented by undefinedness,we have to choose the worst (least with respect to the refinement ordering)solution:Q worst Y such that r Y r Q X r X Q Xwhile b do P end worst Y such that Y if b then P;Y endwhere r X is for any specification X either or.We are obviously faced with the question of existence and uniqueness of the solutions,i.e.with the well-definedness of iteration.We do so by giving an equivalent,but explicit definition of iteration.To this end,we introduce the choice over a range of specifications.Let r be for any specification X either or:12X r P X r∆P X r PWe state some consequences of this definition.The next theorem states a relationship between universal quantification and choice over ranges.It can be seen as a generaliza-tion of(8)under””and is used in the proof of the subsequent theorem.We assume that X is not free in Q.(1)Q X r P X r Q PProof L.H.S.∆Q∆X r P X r P Q by def.””∆Q X r∆P X r∆P X r P Qby def.””∆Q X r∆P X r P Q by pred.calc.∆Q X r∆P P Q by pred.calc.X r Q∆P P Q by pred.calc.R.H.S.by def.””(2)Q worst Y such that r Y r Q Q X r X XThe implication from left to right states that if Q is the worst solution of r Q,then r Q holds(trivially),and Q is given by some unique expression.Hence,if a worst solution exists,it is unique.However,there does not necessarily exist a solution Y for r Y,but if one Q is a solution of r Q and Q is X r X X,then the converse implication states that it is the worst one.Here is the proof:Proof L.H.S.r Q X r X Q X by def.”worst”r Q Q X r X X by(1)r Q Q X r X X as r Q X r X X QR.H.S.This establishes the uniqueness of worst solutions of r Y.Next we turn our attention to the existence of solutions.We show the existence of solutions only for r Y of the form P Y Y,which suffices our purposes.We do so in two steps,first establishing the existence of solutions for P Y Y,then for P Y Y.We need some properties of the restricted choice:(3)X r P Q X r P X r QThe proof of this theorem is done by simple manipulations in the predicate calculus.It is used for the justification of the following theorem.(4)X r P Q X r P X r QProof Assuming X r P Q,we calculateX r P X r QX r P X r Q X r P by(1)under””X r P Q X r P property of””by assumption and(3)with Q:P Q13(5)P X monotonic in X P X r X X r P XProof Assuming P X monotonic in X,we calculateP X r X X r P XX r P X r X P X by(1)X r X r X X P X monotonic in Xproperty of””(6)P X monotonic in X there exists worst Y such that P Y YProof According to(2)it suffices to show that X P X X X is a solution.P X P X X XX P X X P X by assumption and(5)X P X X X by(4)with r P Q:P X X P X X This result establishes the existence and uniqueness of the worst solution for P Y Y, but iteration is defined by the worst solution of P Y Y.The theorem of Knaster and Tarski does the rest:(7)”Theorem of Knaster-Tarski”If P X monotonic in X,then(a)worst Y such that P Y Y,and(b)worst Y such that P Y Yhave the same solution.Proof According to(6),(b)has a solution.Let it be denoted by Q.Now we show that Q is also the solution of(a),i.e.(c)Q P Q,and(d)X X P X Q XFor(c)we observe:Q P QQ P Q P Q Q as””antisymmetric Q P Q as Q solution of(b) P P Q P Q as X P X X Q X with X:P QP Q Q P X monotonic in Xas Q solution of(b) For(d)we observe for any X:X P XP X X property of””Q X as X P X X X Q hence X X P X Q X.For iteration we observe,that both sequential composition and conditional are mono-tonic,hence”if b then P;X end”is monotonic in X,and”worst Y such that Y if b then P;Y end”has a unique solution according to Knaster-Tarski.This establishes the well-definedness of iterations.Next we turn to the question of how to prove properties about iterations.To this end,we need induction over well-founded sets.14(set C partially ordered by is well-founded)(all decreasing chains in C arefinite)(mathematical induction over C is valid)(for any predicate p c over c C:c c C p c c c Cd d C d c p d p c(8)”Principle of mathematical induction”(set C is well-founded)(mathematical induction over C is valid)The definitions above are taken from[3],where also a proof of the principle of mathe-matical induction is given.This givesfinally all the prerequisites for the main theorem about iterations.(9)”Main Iteration Theorem”Let D be a set partially ordered by C a well founded subset of D t a function from the context V to D P and Q specifications and b a condition.Then(a)∆Q t C b(b)c c C∆Q t c b P;t c(c)if b then P;Q end Q(d)while b do P end QThe function t is known as the termination rmally,if t is not in C(but in D), then according to requirement(a)the iteration is sure to terminate as b,the condition for termination holds.Otherwise,if t is in C,then the iteration might or might not terminate.However,in case it does not,requirement(b)ensures that t will be decreased by the body of the iteration,and hence eventually terminate:as C is well founded,all decreasing chains in C arefinite.Finally,requirement(c)states that the iteration does indeed compute the desired result:Q is a solution of equation defining the iteration. Proof For the purpose of the proof we define W byW while b do P endand conclude by”unfolding”the iteration:(e)W if b then P;W end by def.”while”The proof is carried out by showing separately(f)∆Q t C W t C Q(g)∆Q t C W t C Q(h)∆Q Wwhich together,by the principle of case analysis,establish(d).(f)caters for the case that the iteration terminates immediately,(g)for the case that it will terminate sometime,and (g)for the case that it is undefined.For(f)we observe:t C∆Q W t C Qt C∆Q b W t C∆Q b Q by(a) t C∆Q b II t C∆Q b II by(c),(e),and(3)under”if”15For the proof of(g)and(h)we need a couple of lemmas:(i)b P;∆Q∆Q(j)P;∆Q∆Q(k)b∆QThey are all consequences of requirement(c):if b then P;Q end Q∆if b then P;Q end∆Q rule of Leibnitz b∆P;Q b∆II∆Q by(1)under”if”,def.”if”b P;∆Q b∆Q by(15),(10)under”wp”P;∆Q b∆Q law of absorption P;∆Q∆Q b∆Q pred.calc.(i)is equivalent to the second last line.Now,for(g)we observet C∆Q W t C Qc c C t c∆Q W t c Q by pred.calc. According to the principle of mathematical induction,this is proved by deriving (l)t c∆Q W t c Qfrom(m)d d C d c t d∆Q W t d Qfor any c C.To this end,we calculate:d d C d c t d∆Q W t d Qt c t C∆Q W t c t C Q by pred.calc.t c∆Q W t c Q by(f) t c∆Q if b then P;t c∆Q W endt c∆Q if b then P;t c Q end by rule of Leibnitz t c∆Q if b then P;t c P;∆Q P;W endt c∆Q if b then P;t c P;Q end by(6)under”wp”t c∆Q if b then P;W endt c∆Q if b then P;Q end by(b),(i),and(4),(5)under”if”t c∆Q W t c Q by(e)and(c) For(h)we calculate:∆Q WW∆Q by pred.calc.∆W∆Q as for any P b:P b∆P b ∆X X if b then P;X end X∆Q property of”while”X X if b then P;X end∆X∆Q property of””X X if b then P;X end∆X∆Q by pred.calc.b II if b then P;b II end as∆b II∆Q(k)b II if b then P;b P end by(6)under”wp”b II if b then∆Q P;b P end as P;b P;∆Q∆Q by(k),(j)b II b∆Q P;b P b II by def.”if”as b∆Q by(k) This concludes the proof of the main iteration theorem.16。
SYMMETRIC GROUPS AND CONJUGACY CLASSES
a rXiv:078.225v1[math.G R]1Aug27SYMMETRIC GROUPS AND CONJUGACY CLASSES EDITH ADAN-BANTE AND HELENA VERRILL Abstract.Let S n be the symmetric group on n -letters.Fix n >5.Given any nontrivial α,β∈S n ,we prove that the product αS n βS n of the conjugacy classes αS n and βS n is never a conjugacy class.Furthermore,if n is not even and n is not a multiple of three,then αS n βS n is the union of at least three distinct conjugacy classes.We also describe the elements α,β∈S n in the case when αS n βS n is the union of exactly two distinct conjugacy classes.1.Introduction Let G be a finite group,a ∈G and a G ={a g |g ∈G }be the conjugacy class of a in G .Let X be a G -invariant subset of G ,i.e.X g ={x g |x ∈X }=X for all g ∈G .Then X can be expressed as a union of n distinct conjugacy classes of G ,for some integer n >0.Set η(X )=n .For any a,b ∈G ,the product a G b G ={xy |x ∈a G ,y ∈b G }is a G -invariant set.In this note we explore η(a G b G )when G is the symmetric group S n on n -letters,and a G ,b G are conjugacy classes of S n .We denote the identity of any group by e .Arad and Herzog conjectured that the product of two nontrivial conjugacy classes in a finite simple nonabelian group is never a conjugacy class [AH],i.e.,if a,b =e ,then η(a G b G )=1.This has been proved in some cases [AH],in particular,it has been proved for the alternating group A n ,i.e.if n ≥5and α,β∈A n \{e },then η(αA n βA n )≥2.In this note,we show that the symmetric group behaves similarly,and we give an explicit description of the minimum possible value of η.Theorem A.Let S n be the symmetric group on n -letters,n >5,and α,β∈S n \{e }.Then η(αS n βS n )≥2,and if η(αS n βS n )=2then either αor βis a fixed point free permutation.Assume that αis fixed point free.Then one of the following holdsi)n is even,αis the product of n3disjoint 3-cycles and βis a trans-position.Since for any group G and any a,b ∈G ,we have a G b G =b G a G (see Lemma 3),Theorem A describes αand βwhen η(αS n βS n )=2.Corollary A.Fix n >5.Let m be the least integer in {η(αS n βS n )|α,β∈S n \{e }}.Theni)m =2if n is divisible by 2or 3,ii)m =3otherwise.SYMMETRIC GROUPS AND CONJUGACY CLASSES February1,2008EDITH ADAN-BANTE AND HELENA VERRILL February 1,2008c c c qq q q q q q q q q qq q q q q q q q q q q q q q q q q q q d d ¨¨¨%¨¨¨%d d $$$$$$The second picture shows the re-sult of conjugating αby (k t )βασT t k u v q q q q q q q q q q qq q q q q q q q q q q q q q q q q q q $$$$$$W q q $$$$$$W $$$$$$Remark 2.Lemma 5also holds for n =4,except (up to conjugacy and order)in the case α=(123),β=(12)(34).One can check this case by case.Corollary 6.If α,β∈S n ,n ≥4,and αis a fixed point free permutation,then for some σ∈S n ,ασβis also fixed point free.Proof.By Lemma 5and Remark 2,there exists σwith (α−1)σ(i )=β(i )for i =1,...,n ,and so ασβ(i )=i for i =1,...,n ,i.e.,ασβhas no fixed points.3SYMMETRIC GROUPS AND CONJUGACY CLASSES February1,2008EDITH ADAN-BANTE AND HELENA VERRILL February1,2008c c cc c cSYMMETRIC GROUPS AND CONJUGACY CLASSES February1,2008EDITH ADAN-BANTE AND HELENA VERRILL February1,2008。
The algebraic structure of the Onsager algebra
a rX iv:c ond-ma t/2418v1[c ond-m at.stat-m ec h]27Feb2THE ALGEBRAIC STRUCTURE OF THE ONSAGER ALGEBRA 1Etsuro Date 23Department of Mathematics,Osaka University ,Osaka 560,Japan Shi-shyr Roan 45Institute of Mathematics ,Academia Sinica ,Taipei ,Taiwan Abstract We study the Lie algebra structure of the Onsager algebra from the ideal theoretic point of view.A structure theorem of ideals in the Onsager algebra is obtained with the connection to the finite-dimensional representations.We also discuss the solvable algebra aspect of the Onsager algebra through the formal Lie algebra theory.1Introduction In this note,we are going to discuss the algebraic structure of a certain infinite-dimensional Lie algebra which appeared in the seminal work of Onsager of 1944on the solution of 2D Ising model [1].Due to some other simpler and powerful methods introduced later in the study of Ising model,the algebra in the Onsager’s original work,now called the Onsager algebra,had not received enough attention in the substantial years until the 1980-s when its new-found role appeared in the superintegrable chiral Potts model,[2-12](for a review of the subject,see [13]and references therein ).Since the work of Onsager it was known that there exists an intimate relationship between the Onsager algebra and sl 2,a connection now clarified in [8,14].Namely,the Onsager algebra is isomorphic to the fixed subalgebra of sl 2-loop algebra (or alternatively,its central extension A (1)1,)by a certain involution.A generalization of the Onsager algebra to other Kac-Moody algebras was later introduced in [13,15],with some interesting relations with integrable motions.Due to the close relationship of the Onsager algebra with 2D integrable models in statistical mechanics,especially in the chiral Potts model,a thorough mathematical understanding of this infinite-dimensional algebra is desirable to warrant the further investigation.In this note,we summarize our recent results on the algebraic study of the structure of the Onsager algebra.Detailed derivations,as well as extended references to the literature,may be found in [16].We have established the structure theorem of a certain class of (Lie)-ideals of the Onsager algebra,originated from the study of (reducible orirreducible)finite dimensional representations of the Onsager algebra,through the theory of thereciprocal polynomials.In the process,we have found a profound structure of the Onsager algebra with some interesting applications to solvable and nilpotent Lie algebras.It suggests that the further study of the ideals in the Onsager algebra and its possible generalization should provide certain useful information on the theory of solvable Lie algebras.The mathematical results obtained would be expected to have some feedback to the original physical theory.Such a program is now under progress and partial results are promising.2Hamiltonian of Superintegrable Chiral Potts ModelThe superintegrable chiral Potts N-state spin chain Hamiltonian has the following form of a pa-rameter k′,H(k′)=H0+k′H1,with H0,H1the Hermitian operators acting on the vector space of L-tensor of I C N,defined byH0=−2Ll=1N−1n=1(1−ω−n)−1X n l,H1=−2Ll=1N−1n=1(1−ω−n)−1Z n l Z N−nl+1,whereω=e2πi2,−√2H(k′)=Ll=1(e−πi6X2l)+k′Ll=1(e−πi6Z2l Z l+1),which was studied by Howes,Kadanoffand M.den Nijs[11].Note that the Potts model is given bythe chiral angles,ϕ=φ=0.For a general N,H(k′)was constructed in a paper of G.von Gehlen and R.Rittenberg[10],in which the models were shown to be”superintegrable”in the sense that the Dolan-Grady(DG)condition[9]is satisfied for A0=−2N−1H0,A1=−2N−1H0,[A1,[A1,[A1,A0]]]=16[A1,A0],[A0,[A0,[A0,A1]]]=16[A0,A1].For a pair of operators,A0,A1,we denote,4G1=[A1,A0],and define an infinite sequence of operators,A m,G m,(m∈Z Z),by relations,A m−1−A m+1=14[A m,A0].The DG-condition on A1,A0,are equivalent[8,14]to the statement that the collection of A m,G m forms the Onsager algebra,which means they satisfy the Onsager relations,[A m,A l]=4G m−l,[A m,G l]=2(A m−l−A m+l),[G m,G l]=0.(1)The above relations ensure that the k′-dependence eigenvalues of H(k′)have the following special form as in the Ising model,a+bk′+2Nnj=1 m jIt is easy to see that zeros of a reciprocal polynomial P(t)not equal to±1must occur in the reciprocal pairs,and I P(t)is invariant under the involution of OA,A m→A−m,G m→G−m. Through the Chinese remainder theorem,one can establish the a canonical(Lie-)isomorphism of the quotient algebras,OA/I P(t)∼−→Jj=1OA/I Pj(t),P(t):=Jj=1P j(t)where P j(t)are pairwise relatively prime reciprocal polynomials.The role of reciprocal polynomials in the study of the Onsager algebra is given by the following structure theorem of closed ideals of OA.Theorem1.An ideal I of OA is closed if and only if I=I P(t)for a reciprocal polynomial P(t) whose zero at t=±1are of the even multiplicity.The ideal I P(t)is characterized as the minimal closed ideal of OA containing P(t)e+P(t−1)f.2For an irreducible special representation of OA on afinite dimensional vector space V,ρ:OA−→sl(V),the generating polynomial of the kernel Ker(ρ)is given by P(t)= n j=1U a j(t),where a j∈I C∗−{±1},a j=a±1i for j=i,and U a(t):=(t−a)(t−a−1).In this situation,the evaluation morphism of OA,induced from L(sl2),into the sum of n copies of sl2,e a1,...,a n :OA−→nsl2,X→(e a1(X),...,e a n(X)),gives rise the isomorphism between OA/Ker(ρ)andn sl2.Hence irreducible representations of the sl2-factors determine an irreducible representation of OA.4Completion of the Onsager Algebra and Solvable Lie Algebras By the previous discussion,the study of closed ideals in OA can be reduced to the case,I=I P(t) with P(t)=(t±1)L or U a(t)L for L∈Z Z≥0,a∈I C∗−{±1}.In this report,we shall only discuss the case,P(t)=(t±1)L.As the map,t→−t,gives rise an involution of OA,one has the isomorphism,OA/I(t−1)L≃OA/I(t+1)L.We may assume,P(t)=(t−1)L,(L∈Z Z≥0).DenoteπL,πKL the canonical projections,πL:OA−→OA/I(t−1)L,πKL:OA/I(t−1)L−→OA/I(t−1)K,L≥K≥0,and OA the projective limit of the projective system,(OA/I(t−1)L,πKL).Then OA is a Lie algebra and denote the canonical morphism,ψL: OA−→OA/I(t−1)L,L∈Z Z≥0,with the kernel, OA L:= Ker(ψL).We have, OA/ OA L≃OA/I(t−1)L.We have afiltration of ideals in OA,OA= OA0⊃ OA1⊃···⊃ OA L⊃···.There exists a morphism,π:OA−→ OA,withψLπ=πL.The Lie algebra OA is regarded as a completion of OA.For the convenience,we shall write the elementπ(X)of OA again by X for X∈OA if no confusion could arise.There exists the unique sequence of elements,X k ,Y k ,(k ∈Z Z ≥0),in OAsuch that the following identities hold in OA ,A m (=π(A m ))=k ≥0m (k )k !Y k ,where x (n )is the shifted factorial defined by x (0):=1,x (n ):=x (x −1)···(x −n +1),n ∈Z Z >0.In fact,with the infinite formal sum OA has X k ,Y k as the generators of the formal Lie algebra,while OA L is the ideal generated by X k ,Y k ,(k ≥L ).In OA /I (t −1)L ,one has,ψL (A m )=L −1 k =0m (k )k !ψL (Y k ),m ∈Z Z .The relations (1)for OA now become the following relations in OA, n,k ≥0a !b !k !s k a +b Y k , n,k (−1)n a !b !k !s k a +b X k ,[Y n ,Y k ]=0,where s n k ,S n k ,(n,k ∈Z Z ≥0),are the Stirling numbers,i.e.,the integers with the relations,x (n )= k ≥0x k s n k ,x n = k ≥0x (k )S n k .Note that s n n =S n n =1,and s n k =S n k =0for k >n .By the identities among Stirling’s numbers [18],k s a k S k b =δa b ,b !j !S j a = lk !(a +l )!k −n +1(2k 2n −1)Y 2k +1,where B j (j ≥1)are the Bernoulli numbers,B j =(−1)j −1b 2j ,with x j !x j .For thestudy of the Lie algebra structure of OA,it is more natural to use a local coordinate system near t =1for expressing elements in L (sl 2).A convenient variable is,λ:=t −t−1There is a formal Lie-algebra isomorphism,OA≃sl2 λ ,under which OA L is corresponding to sl2 λ L.As a consequence,≃sl2 λ /sl2 λ L.OA/I(t−1)L2By the above Theorem,OA/I(t−1)L is a solvable Lie algebra of dimension L+[L1+λ2,t−1−1=−λ−1+2)λ2j.jBy taking the expression of of A0,A1modularλL sl2[[λ]],one can construct reducible representationsof OA with the kernel ideal generated by(t−1)L.5Further RemarksFor the understanding of representations of the Onsager algebra,both the reducible and irreducible ones,the structure of OA/I P(t)with a reciprocal polynomial P(t)warrants the mathematical inves-tigation.But,just to keep things simple,we restrict our attention in this present report only to the case,P(t)=(t±1)L,L≥1,or U a(t),a=±1.With a similar argument,one can also obtain the structure of quotients for closed ideals generated by P(t)=U a(t)L,L∈Z Z>0,(for the details, see[16]).The results,together with the mixed types,should have some interesting applications and implications in solvable or nilpotent algebras,which we shall leave to future work.Here is the one example which appeared in[14]:Example.OA/I(t2+1)2≃sl2[ε]/ε2sl2[ε].Denote e k,f k,h k,(k=0,1)the basis elements of sl2[ε]/ε2sl2[ε] corresponding to the standard basis of sl2with the index k indicating the grade ofε.Define the linear map,ϕ:OA−→sl2[ε]/ε2sl2[ε],by the expression:ϕ(A m)=2(i m e0+i−m f0+m i m−1e1+m i−m+1f1),ϕ(G m)=(i m−i−m)h0+m(i m−1−i m−1)h1.Thenϕis a surjective morphism.Since sl2[ε]/ε2sl2[ε]has only trivial center,Ker(ϕ)is a closed ideal with(t2+1)2as the generating polynomial.2Generalizations of the Onsager algebra to other loop algebras or Kac-Moody algebras as in[13,15] should provide ample examples of solvable algebras of the above type.We hope that the further development of the study of the subject will eventually lead to some interesting results in Lie-theory with possible applications in quantum integrable models.References[1]L.Onsager:Phys.Rev.65(1944)117.[2]G.Albertini,B.M.McCoy,J.H.H.Perk,and S.Tang:Nucl.Phys.B314(1989)741.[3]G.Albertini,B.M.McCoy,and J.H.H.Perk:Phys.Lett.A135(1989)159;Phys.Lett.A139(1989)204;Adv.Stud.Pure Math.,vol.19,Kinokuniya Academic1989.[4]H.Au-Yang,B.M.McCoy,J.H.H.Perk,S.Tang,and M.L.Yan:Phys.Lett.123A(1987)219.[5]R.J.Baxter:Phys.Letts.A133(1988)185.[6]R.J.Baxter,J.H.H.Perk and H.Au-Yang:Phys.Letts.A128(1988)138.[7]R.J.Baxter,V.V.Bazhanov and J.H.H.Perk:Int.J.Mod.Phys.B4(1990)803.[8]B.Davies:J.Phys.A:Math.Gen.23(1990)2245;J.Math.Phys.32(1991)2945.[9]L.Dolan and M.Grady:Phys.Rev.D25(1982)1587.[10]G.von Gehlen and R.Rittenberg,Nucl.Phys.B257(1985)351.[11]S.Howes,L.P.Kadanoffand M.den Nijs:Nucl.Phys.B215(1983)169.[12]J.H.H.Perk:in P roc.Symp.inP ureMathematics,American Mathematical Society,1989,Vol.49,part1p.341.[13]D.B.Uglov and I.T.Ivanov:J.Stat.Phys.82(1996)87.[14]S.S.Roan:Onsager’s algebra,loop algebra and chiral Potts model,MPI91-70,Max-Planck-Institut f¨u r Mathematik,Bonn,1991.[15]C.Ahn and K.Shigemoto:Modern Phys.Lett.A6(1991)3509.[16]E.Date and S.S.Roan:The structure of quotients of the Onsager algebra by closed ideals,Preprint math.QA/9911018.[17]J.B.Kogus:Rev.Mod.Phys.51(1979)659and references therein.[18]J.Riordan:An introduction to combinatorial analysis,Wiley publication in statistics1958;Combinatorial identities,Wiley series in probabilty and mathematical statistics1968.。
algebra2 知识点总结
algebra2 知识点总结Linear Equations and FunctionsOne of the fundamental concepts in Algebra 2 is linear equations and functions. A linear equation is an equation of the form y = mx + b, where m is the slope and b is the y-intercept. Students learn how to graph linear equations, find the slope and y-intercept, and solve systems of linear equations using various methods such as substitution, elimination, and graphing.Functions are a core concept in Algebra 2, and students study various types of functions such as linear, quadratic, exponential, and logarithmic functions. They learn how to analyze the behavior of functions, find their domain and range, and determine whether a function is even, odd, or periodic. Students also explore transformations of functions, such as shifts, stretches, and reflections, and how they affect the graph of a function.Inequalities and Absolute Value EquationsIn Algebra 2, students also study inequalities and absolute value equations. They learn how to solve and graph linear inequalities, quadratic inequalities, rational inequalities, and absolute value inequalities. They also explore the concept of compound inequalities and how to solve systems of inequalities.Absolute value equations are another important topic in Algebra 2. Students learn how to solve and graph absolute value equations, as well as inequalities involving absolute value expressions. They also study the properties of absolute value functions and their applications in real-life scenarios.Polynomials and Polynomial FunctionsPolynomials are algebraic expressions that consist of variables and coefficients, combined using addition, subtraction, and multiplication. In Algebra 2, students learn how to add, subtract, multiply, and divide polynomials, as well as factor and solve polynomial equations. They also study the properties of polynomial functions, such as end behavior, zeros, and turning points.Students delve into advanced topics such as polynomial long division, synthetic division, the remainder theorem, and the factor theorem. They also explore the relationship between polynomial functions and their graphs, and how to use this information to solve real-world problems.Rational Expressions and Rational FunctionsRational expressions are fractions that contain polynomials in the numerator and denominator. In Algebra 2, students learn how to simplify, multiply, divide, add, and subtract rational expressions, as well as solve rational equations. They also study the properties of rational functions, such as asymptotes, intercepts, and end behavior.Students explore the relationship between rational functions and their graphs, and how to use this information to analyze and solve real-world problems. They also study advanced topics such as partial fraction decomposition, complex fractions, and applications of rational functions in areas such as economics, physics, and engineering.Exponential and Logarithmic FunctionsExponential and logarithmic functions are essential in Algebra 2, and students learn how to solve exponential and logarithmic equations, as well as graph exponential and logarithmic functions. They study the properties of exponential and logarithmic functions, such as growth and decay, domain and range, and asymptotic behavior.Students also explore the relationship between exponential and logarithmic functions, and how to use this information to solve real-world problems. They study applications of exponential and logarithmic functions in areas such as finance, population growth, radioactive decay, and pH levels.Sequences and SeriesSequences and series are important topics in Algebra 2, and students learn how to find the nth term of a sequence, as well as the sum of a finite or infinite series. They study arithmetic sequences and series, geometric sequences and series, and other types of sequences such as Fibonacci and recursive sequences.Students explore the properties of sequences and series, such as common difference, common ratio, and convergence. They also study applications of sequences and series in areas such as finance, physics, and computer science.Complex NumbersComplex numbers are numbers of the form a + bi, where a and b are real numbers, and i is the imaginary unit (√-1). In Algebra 2, students learn how to perform operations with complex numbers, such as addition, subtraction, multiplication, division, and simplification. They also study the properties of complex numbers, such as the conjugate, modulus, and argument.Students explore the relationship between complex numbers and their graphs on the complex plane, and how to use this information to solve equations involving complex numbers. They also study applications of complex numbers in areas such as electrical engineering, signal processing, and quantum mechanics.Matrices and DeterminantsMatrices are arrays of numbers arranged in rows and columns, and they are used to represent and solve systems of linear equations. In Algebra 2, students learn how to add, subtract, multiply, and invert matrices, as well as find the determinant of a matrix. They also study the properties of matrices, such as the identity matrix, transpose, and rank.Students explore the relationship between matrices, determinants, and systems of linear equations, and how to use this information to solve real-world problems. They also study applications of matrices in areas such as computer graphics, cryptography, and economics.Conic SectionsConic sections are curves obtained by intersecting a cone with a plane, and they include the circle, ellipse, parabola, and hyperbola. In Algebra 2, students learn how to graph and analyze conic sections, as well as find their equations given certain properties.Students study the properties of conic sections, such as the focus, directrix, eccentricity, and asymptotes. They also explore the relationship between conic sections and their equations, and how to use this information to solve real-world problems. They study applications of conic sections in areas such as astronomy, engineering, and architecture.ConclusionAlgebra 2 is a challenging but rewarding branch of mathematics that builds upon the concepts learned in Algebra 1. In this article, we have provided a comprehensive summary of the key topics in Algebra 2, including linear equations and functions, inequalities and absolute value equations, polynomials and polynomial functions, rational expressions and rational functions, exponential and logarithmic functions, sequences and series, complex numbers, matrices and determinants, and conic sections.By mastering these topics, students will develop a deeper understanding of algebraic concepts and techniques, as well as their applications in various fields such as science, engineering, economics, and finance. Algebra 2 is an essential foundation for further study in mathematics and related disciplines, and it provides students with the analytical and problem-solving skills necessary for success in the modern world.。
基于E-DP和DLP一种无限非交换群上的密钥交换协议
2022年 5月 May 2022Digital Technology &Application 第40卷 第5期Vol.40 No.5数字技术与应用中图分类号:TP309 文献标识码:A 文章编号:1007-9416(2022)05-0228-03DOI:10.19695/12-1369.2022.05.70基于E-DP和DLP一种无限非交换群上的密钥交换协议东莞职业技术学院现代工业创新实践中心 张静首先,本文提出与分解问题等价的一个困难问题:等价分解问题。
其次,基于等价分解问题(E-DP)和离散对数问题(DLP),提出了一种无限非交换群上的密钥交换协议。
在协议中,通过半直积的运算法则,使共享密钥同时包含两个困难问题。
这两个困难问题共同保证了密钥交换协议的抗攻击性。
最后利用代数攻击和暴力攻击进行分析,证明了协议具有较高的安全性。
Sidelnikov等人提出在无限非交换群和半群上建立公钥密码系统的思想[1]。
非交换群上的公钥密码系统主要是应用困难问题隐藏因子,公开的困难问题有共轭搜索问题、分解问题、子群元素搜索问题、离散对数问题、同态搜索问题等。
许多研究已经提出了一些非交换代数结构上基于困难问题的密钥交换协议。
在文献[2]中,作者提出了无限非交换群上基于分解问题的密钥交换协议[2]。
在文献[3]中,作者提出了辫群上基于共轭搜索问题的一种新的密码系统[3],其中辫群是一种无限非交换群,并具有很好的密码特征。
随着量子算法和分解算法的发展[4],只应用一个困难问题已经不能保证密码系统的安全性。
而且单独应用共轭搜索问题构建的密码系统也已经被证明对于安全性是不充分的[5]。
为了提高安全性需要同时使用几个困难问题,2007年,Eligijus等人同时使用共轭搜索问题和离散对数问题在非交换群上构建了一种密码协议,并阐明了同时使用两个困难问题足够保证密码交换协议的安全性[6]。
2013年,Maggie Habeeb等人第一次将群的半直积用到密码系统中,并提出了一种基于半直积运算的密码交换协议[7]。
法国数学家拉格朗日著作《解析函数论》英文名
法国数学家拉格朗日著作《解析函数论》英文名全文共3篇示例,供读者参考篇1Title: French Mathematician Lagrange's Work "Analytical Function Theory"Introduction:Lagrange's "Analytical Function Theory" is a seminal work by the French mathematician Joseph-Louis Lagrange, also known as the Lagrange interpolation or Lagrange polynomial. In this work, Lagrange presents a detailed analysis of functions and their properties, laying the foundation for modern function theory. The book delves into topics such as series, limits, derivatives, and integrals of functions, providing a comprehensive study of mathematical functions.Chapter 1: Historical BackgroundJoseph-Louis Lagrange was born in Turin, Italy, in 1736 and later moved to Paris, where he made significant contributions to mathematics, mechanics, and astronomy. Lagrange's work in function theory was influenced by earlier mathematicians such as Euler, d'Alembert, and Legendre. His innovative approach toanalyzing functions set him apart as a pioneering figure in the field of mathematics.Chapter 2: Analytical Function TheoryIn "Analytical Function Theory," Lagrange explores the properties of functions through the use of calculus and algebraic techniques. He introduces the concept of series as a way to represent functions as infinite sums of terms, allowing for a more precise analysis of their behavior. Lagrange also discusses the importance of limits in determining the behavior of functions at particular points, laying the groundwork for modern calculus.Chapter 3: Applications and ImpactLagrange's work on function theory has had a lasting impact on mathematics, with his ideas forming the basis for modern theories in analysis and calculus. The concept of the Lagrange interpolation polynomial, named in his honor, is still widely used in numerical analysis and approximation techniques. His work has inspired generations of mathematicians to further explore the depths of function theory and its applications in various fields.Conclusion:In conclusion, Joseph-Louis Lagrange's work "Analytical Function Theory" stands as a testament to his brilliance and innovative contributions to the field of mathematics. Through his meticulous analysis of functions and their properties, Lagrange paved the way for future developments in function theory and calculus. His work remains a cornerstone of modern mathematics, continuing to inspire mathematicians worldwide to push the boundaries of knowledge in this dynamic field.篇2Title: French Mathematician Lagrange's Work "Analytic Functions Theory"IntroductionLagrange's work on Analytic Functions Theory is a significant contribution to the field of mathematics. This book, also known as "Théorie des Fonctions Analytiques" in French, was published in the year 1797 by the renowned French mathematician Joseph Louis Lagrange. In this seminal work, Lagrange established the foundation for the study of analytic functions and laid the groundwork for the development of complex analysis.Background of LagrangeJoseph Louis Lagrange, born in Turin, Italy in 1736, was a prominent mathematician who made groundbreaking contributions to various fields of mathematics, such as number theory, calculus, and celestial mechanics. He is widely regarded as one of the greatest mathematicians of all time and his work continues to influence modern mathematics.Content of the BookIn "Analytic Functions Theory", Lagrange delves into the study of functions that can be represented by a power series expansion. He introduces key concepts and theorems related to complex analysis, such as Cauchy's integral theorem, the residue theorem, and the fundamental theorem of algebra. Lagrange's work on the properties and behavior of analytic functions revolutionized the field of mathematics and paved the way for further developments in the study of complex numbers.Significance of the WorkLagrange's book is considered a seminal work in the field of mathematics and remains a cornerstone of complex analysis. His contributions to analytic functions theory have had a lasting impact on the field of mathematics and continue to influence contemporary research in areas such as number theory, physics,and engineering. The book has been widely studied and referenced by mathematicians and scientists around the world.ConclusionIn conclusion, Lagrange's work on Analytic Functions Theory stands as a testament to his brilliance and innovation in the field of mathematics. His insights and discoveries continue to shape our understanding of complex analysis and pave the way for new advancements in the field. The book remains a timeless classic in the realm of mathematics and serves as a source of inspiration for generations of mathematicians to come.篇3Title: The Analytic Function Theory by French Mathematician LagrangeIntroduction:Joseph-Louis Lagrange, a renowned mathematician from France, made significant contributions to the field of mathematics during the 18th century. One of his most influential works is the book "Analytic Function Theory," where he laid down the foundations for the study of complex functions. In this article, we will delve into the contents of this seminal work and discuss its impact on the development of mathematics.Overview of the Book:Lagrange's "Analytic Function Theory" is a comprehensive treatise on the analysis of complex functions, which play a crucial role in a variety of mathematical disciplines including calculus, differential equations, and number theory. The book is divided into several sections, each covering different aspects of the theory of analytic functions. Lagrange begins by introducing the basic concepts of complex numbers and functions, before delving into more advanced topics such as power series, contour integration, and the Cauchy-Riemann equations.Key Concepts and Theorems:One of the key contributions of Lagrange in this work is the development of the Cauchy Integral Formula, which provides a powerful method for calculating complex integrals over closed curves. This formula has important applications in the study of harmonic functions and the theory of residues. Lagrange also proved several important theorems in the book, including the Maximum Modulus Principle and the Riemann Mapping Theorem, which have been instrumental in the development of complex analysis.Impact on Mathematics:Lagrange's "Analytic Function Theory" is considered a seminal work in the field of complex analysis and has had a lasting impact on the development of mathematics. The insights and techniques introduced by Lagrange in this book have been instrumental in solving many mathematical problems in diverse areas such as physics, engineering, and computer science. The book continues to be studied and referenced by mathematicians and researchers around the world, highlighting the enduring legacy of Lagrange's contributions to the field.Conclusion:In conclusion, Joseph-Louis Lagrange's "Analytic Function Theory" stands as a cornerstone in the field of complex analysis, providing a solid foundation for the study of analytic functions and their applications. The insights and theorems introduced by Lagrange in this book have had a profound impact on the development of mathematics, shaping the way we understand and solve complex mathematical problems. As we continue to push the boundaries of mathematical research, Lagrange's work remains as relevant and influential as ever.。
THE PRINCIPLE OF THE LARGE SIEVE
is that of a “small” sieve. The simplest such case is the detection of primes with Ωp = {0}. If, on the other hand, the size of Ωp increases, the situation is that of a “large” sieve. The first such sieve was devised by Linnik to investigate the question of Vinogradov of the size of the smallest quadratic non-residue modulo a prime. There have already been a number of works extending “small” sieves to more general situations, where the objects being sifted are not necessarily integers. Among these, one might quote the vector sieve of Br¨ udern and Fouvry [BF], with applications to Lagrange’s theorem with almost prime variables, the “crible ´ etrange” of Fouvry and Michel [FM], with applications to sign changes of Kloosterman sums, and Poonen’s striking sieve procedure for finding smooth hypersurfaces of large degree over finite fields [Po]. Similarly, the large sieve has been extended in some ways, in particular (quite early on) to deal with sieves in Zd , d 1, or in number fields (see e.g. [G]). Interesting applications have been found, e.g. Duke’s theorem on elliptic curves over Q with “maximal” p-torsion fields for all p [D]. All these were much of the same flavor however, and in particular depended only on the character theory of finite abelian groups as far as the underlying harmonic analysis was concerned1. In [Ko1], we have introduced a new large sieve type inequality for the average distribution of Frobenius conjugacy classes in the monodromy groups of a family (Fℓ ) of Fℓ -adic sheaves on a variety over a finite field. Although the spirit of the large sieve is clearly recognizable, the setting is very different, and the harmonic analysis involves both non-abelian finite groups, and the deep results of Deligne on the Riemann Hypothesis over finite fields. Our first application of this new sieve was related to the “generic” arithmetic behavior of the numerator of the zeta function of a smooth projective curve in a family with large monodromy, improving significantly a result of Chavdarov [Ch]. Motivated by this first paper, the present one is interested with foundational issues related to the large sieve. We are able to describe a very general abstract framework which we call “the principle of the large sieve”, with a sieve statement that may in particular be specialized to either the classical forms of the large sieve, or to a strengthening of [Ko1]. Roughly speaking, we deal with a set X that can be mapped to finite sets Xℓ (for instance, integers can be reduced modulo primes) and we show how an estimate for the number of those x ∈ X which have “reductions” outside Ωℓ ⊂ Xℓ for all or some ℓ may be reduced to a bilinear form estimate of a certain kind. The form of the sieve statement we obtain is similar to Montgomery’s formulation of the large sieve (see e.g. [Mo], [B], [IK, 7.4]). It should be mentioned that our “axioms” for the sieve may admit other variations. In fact, Zywina [Z] has developed a somewhat similar framework, and some of the flexibility we allow was first suggested by his presentation. There remains the problem of estimating the bilinear form. The classical idea of duality and exponential sums is one tool in this direction, and we describe it also somewhat abstractly. We then find a convincing relation with the classical sieve axioms, related to equidistribution in the finite sets Xℓ . The bilinear form inequality also seemingly depends on the choice of an orthonormal basis of certain finite-dimensional Hilbert spaces. It turns out that in many applications, the sieve setting is related to the existence of a group G such that Xℓ is the set of conjugacy classes in a finite quotient Gℓ of G and the reduction X → Xℓ factors through G. In that case, the bilinear form inequality can be stated with a distinguished basis arising from the representation theory (or harmonic analysis) of the finite groups Gℓ . This abstract sieving framework has many incarnations. As we already stated, we can recover the classical large sieve and the “sieve for Frobenius” of [Ko1], but furthermore, we are led to
On the power structure over the Grothendieck ring of varieties and its applications
(1 − u k t)−pk ,
2
4. (A more geometric example.) Let R be the K -functor K (X ) of the space X , i.e. the Grothendieck ring of (say, real or complex) vector bundles over X . For a vector bundle E over X , let Λk E be the k -th exterior power of the bundle E . The series λE (t) = 1 + [E ]t + [Λ2 E ]t2 + [Λ3 E ]t3 + . . . defines a pre-λ structure on the ring K (X ). To a pre-λ structure on a ring R one can associate a power structure over R: a notion introduced in [8]. Definition: A power structure over a (semi)ring R with a unit is a map (1 + t · R[[t]]) × R → 1 + t · R[[t]]: (A(t), m) → (A(t))m , which possesses the following properties: 1) (A(t))0 = 1, 2) (A(t))1 = A(t), 3) (A(t) · B (t))m = (A(t))m · (B (t))m , 4) (A(t))m+n = (A(t))m · (A(t))n , 5) (A(t))mn = ((A(t))n ) , 6) (1 + t)m = 1 + mt+ terms of higher degree, 7) A(tk )
学校社团英语作文
School clubs are an integral part of the educational experience,offering students a chance to explore their interests,develop new skills,and foster a sense of community. Heres a detailed look at the various aspects of school clubs and their impact on students.Introduction to School ClubsSchool clubs are organized groups that focus on a specific interest or activity.They can range from academic to recreational,and are often run by students with the guidance of a faculty advisor.These clubs provide a platform for students to engage in activities they are passionate about,outside the regular curriculum.Types of School Clubs1.Academic Clubs:These include Math clubs,Science Olympiad teams,Debate clubs, and Language learning groups.They cater to students who wish to delve deeper into their academic interests.2.Arts and Literature Clubs:Drama clubs,Creative Writing groups,and Photography clubs are popular among students who have a flair for the arts.3.Sports Clubs:From traditional sports like football and basketball to more niche activities like chess or martial arts,sports clubs encourage physical fitness and teamwork.4.Social and Community Service Clubs:These clubs focus on giving back to the community,such as volunteering at local shelters or organizing charity events.5.Special Interest Clubs:Clubs like Robotics,Astronomy,or Environmental clubs cater to students with unique interests.Benefits of School Clubs1.Skill Development:Clubs provide an opportunity for students to develop and hone specific skills,whether its public speaking,leadership,or technical skills in a particular field.2.Personal Growth:Participation in clubs can boost selfconfidence,as students take on responsibilities and see the results of their efforts.working:Clubs are a great way to meet likeminded peers and form lasting friendships.4.Leadership Opportunities:Many clubs offer leadership roles,such as club president or treasurer,which can be valuable experience for future career paths.5.College Applications:Involvement in extracurricular activities,including clubs,can make a students college application stand out.Challenges of School Clubs1.Time Management:Balancing club activities with academic responsibilities can be challenging,requiring good time management skills.2.Funding:Some clubs may struggle with securing enough funding for resources orevents,which can limit their activities.3.Member Engagement:Keeping members actively involved and interested can be a challenge,especially as students interests and priorities change.How to Start a School Club1.Identify a Need or Interest:Find a gap or a shared interest among students that isnt currently being addressed by existing clubs.2.Gather Support:Rally a group of interested students to join as founding members.3.Find a Faculty Advisor:A teacher or staff member must support and guide the club.4.Write a Club Constitution:This document outlines the clubs purpose,structure,and rules.5.Apply for Recognition:Submit an application to the school administration for official recognition as a school club.ConclusionSchool clubs are a vibrant part of student life,offering a wealth of opportunities for learning,growth,and enjoyment.They enrich the educational experience by providing a space for students to pursue their passions and interests in a supportive and structured environment.Whether youre a student looking to join a club or someone interested in starting one,theres a world of possibilities waiting to be explored.。
英语作文一个名人
英语作文一个名人When it comes to writing an essay about a famous person its crucial to choose someone who has made a significant impact in their field or on society as a whole. For this example lets consider writing about Sir Isaac Newton one of the most influential scientists in history.Title The Life and Legacy of Sir Isaac NewtonIntroductionIn the realm of scientific discovery few figures loom as large as Sir Isaac Newton. Born in 1642 in Woolsthorpe England Newtons contributions to mathematics physics and astronomy have shaped the modern world. This essay will explore his early life major discoveries and the lasting impact of his work.Early LifeIsaac Newton was born prematurely and his survival was considered unlikely. His family was not wealthy and his education was initially limited. However his intelligence and curiosity were evident from a young age. He attended The Kings School Grantham where he showed an aptitude for building mechanical devices.Education and Early CareerNewtons academic journey took a significant turn when he was admitted to Trinity College Cambridge in 1661. There he was exposed to the works of René Descartes and other philosophers and mathematicians. His studies in mathematics optics and natural philosophy laid the groundwork for his future discoveries.Major Discoveries1. Calculus Newton developed the mathematical framework of calculus a system for understanding change and motion which he called fluxions. This work was foundational for modern physics and engineering.2. Laws of Motion His three laws of motion are the cornerstone of classical physics. They describe the relationship between a body and the forces acting upon it and its motion in response to those forces.3. Universal Gravitation Newtons law of universal gravitation states that every particle attracts every other particle in the universe with a force that is directly proportional to the product of their masses and inversely proportional to the square of the distance between their centers.OpticsNewtons work in optics was equally groundbreaking. He conducted experiments with prisms and concluded that white light is composed of a spectrum of colors. His development of the reflecting telescope helped to improve the quality of astronomical observations.Personal Life and Later YearsNewton was not only a scientist but also a complex individual with interests in alchemy and theology. He held the position of Lucasian Professor of Mathematics at the University of Cambridge and later served as the president of the Royal Society. His work as the Warden and Master of the Royal Mint demonstrated his administrative skills and contributed to the standardization of British currency.LegacySir Isaac Newtons legacy extends far beyond his lifetime. His laws of motion and universal gravitation remain the basis for understanding the physical world. His work in optics influenced the development of modern telescopes and the understanding of light. Newtons methods and principles continue to inspire scientists and thinkers to this day. ConclusionIn conclusion Sir Isaac Newtons life was a testament to the power of curiosity intellect and dedication. His discoveries and theories have had a profound and lasting impact on science mathematics and our understanding of the universe. As we continue to explore the cosmos and delve into the intricacies of nature Newtons work remains a guiding light in our quest for knowledge.ReflectionReflecting on Newtons life and work one cannot help but be inspired by his relentless pursuit of understanding. His ability to see beyond the obvious and question the fundamental principles of the world around us is a lesson for all who seek to contribute to the advancement of human knowledge.。
四阶整数辛群中扭元的共轭类
Definition 1 The set of 2n × 2n unimodular matrices X in M2n (Z) such that X ′ JX = J, (1)
where X ′ is the transpose of X , is called the symplectic group of genus n over Z and is denoted by SP 2n (Z). Two symplectic matrices X , Y of SP 2n (Z) are said to be conjugate or similar, denoted by X ∼ Y , if there is a matrix Q ∈ SP 2n (Z) such that Y = Q−1 XQ. A complete set of non-conjugate classes of torsion in SP 4 (Z) will be given in this paper. Given a matrix X ∈ M2n (Z), we denote the characteristic polynomial of X by fX (x) = |xI − X |. If X ∈ SP 2n (Z), then fX (x) is “palindromic” and monic, that is,
Conjugacy classes of torsion in 4 × 4 integral symplectic group
179
m(x) = (x2 − x + 1)(x2 + x + 1), f (x) = (x2 − x + 1)(x2 + x + 1). When d = 8, m(x) = f (x) = x4 + 1. When d = 10, m(x) = f (x) = x4 − x3 + x2 − x + 1, When d = 12, m(x) = f (x) = (x4 − x2 + 1), m(x) = f (x) = (x2 + 1)(x2 + x + 1), m(x) = f (x) = (x2 + 1)(x2 − x + 1).
2024年数学进阶课程标准英文版
2024年数学进阶课程标准英文版2024 Mathematics Advanced Course StandardsIn the year 2024, the Mathematics Advanced Course Standards aim to provide a comprehensive framework for the advancement of mathematical knowledge and skills. These standards will cover a wide range of mathematical concepts and topics, ensuring that students are well-equipped to tackle complex problems and challenges in the field of mathematics. The standards will be designed to promote critical thinking, problem-solving, and mathematical reasoning, allowing students to develop a deep understanding of the subject.The 2024 Mathematics Advanced Course Standards will focus on key areas such as algebra, geometry, calculus, statistics, and probability. Students will be expected to demonstrate proficiency in these areas through a series of assessments and examinations. The standards will also emphasize the importance of communication and collaboration inmathematics, encouraging students to work together to solve problems and share their findings with others.Overall, the 2024 Mathematics Advanced Course Standards will set high expectations for students, challenging them to push the boundaries of their mathematical abilities and achieve excellence in the field. By providing a clear and rigorous framework for mathematical learning, these standards will help students develop the skills and knowledge they need to succeed in a competitive and rapidly changing world.。
关于高中选科的英语作文
关于高中选科的英语作文The Importance of Subject Selection in High SchoolAs students approach the end of their middle school years, they are faced with a pivotal decision that will significantly shape their academic and professional trajectories - the selection of subjects for high school. This choice holds immense significance as it not only determines the courses they will pursue but also lays the foundation for their future educational and career paths. In this essay, we will delve into the importance of subject selection in high school and the factors that students should consider when making this crucial decision.Firstly, the subjects chosen in high school serve as a gateway to higher education. Many universities and colleges have specific subject requirements for admission, and the courses taken in high school can greatly impact a student's eligibility for their desired programs. For instance, students aspiring to study engineering or the sciences may need to have a strong background in mathematics, physics, and chemistry, while those interested in the humanities orsocial sciences may need to demonstrate proficiency in subjects such as literature, history, and language. By carefully selecting their high school subjects, students can ensure that they meet the prerequisites for their chosen field of study, increasing their chances of gaining admission to their dream institutions.Moreover, subject selection in high school can shape a student's academic interests and future career aspirations. As students explore different subjects, they may discover a passion for a particular field, which can then guide their educational and professional choices. For example, a student who excels in biology and enjoys learning about the human body may be inspired to pursue a career in the medical field, such as becoming a doctor or a biomedical researcher. Conversely, a student who finds themselves captivated by the intricacies of computer programming may be drawn to a career in technology or software engineering. By selecting subjects that align with their interests and strengths, students can cultivate a deeper understanding of their academic inclinations and make informed decisions about their future.In addition to academic and career implications, the subjects chosen in high school can also have a significant impact on a student's personal growth and development. Different subjects often require distinct skill sets, such as critical thinking, problem-solving, communication, and creativity. By engaging in a diverse range ofsubjects, students can develop a well-rounded set of skills that will serve them well in various aspects of their lives, both academic and personal. For instance, a student who takes a course in public speaking may gain confidence in their ability to effectively communicate their ideas, while a student who explores the arts may cultivate their creative expression and appreciation for beauty.Furthermore, the selection of subjects in high school can open up a world of extracurricular opportunities for students. Many high schools offer clubs, teams, and activities that are closely tied to the subjects being taught. By choosing subjects that align with their interests, students can actively participate in these extracurricular pursuits, further developing their skills and building a well-rounded profile that can be valuable in the college admissions process and beyond.It is important to note that the process of subject selection in high school is not a one-size-fits-all approach. Each student's individual needs, interests, and goals should be taken into consideration when making this decision. It is recommended that students work closely with their parents, teachers, and school counselors to carefully evaluate their options and make an informed choice that aligns with their aspirations and strengths.In conclusion, the selection of subjects in high school is a crucialdecision that can have far-reaching consequences on a student's academic, professional, and personal development. By carefully considering their interests, strengths, and future goals, students can choose a course of study that will not only prepare them for higher education but also foster their personal growth and unlock a world of opportunities. As students embark on this pivotal journey, it is essential that they approach the subject selection process with thoughtfulness, diligence, and a clear vision for their future.。
选择类作文四级模板
选择类作文四级模板英文回答:Choice of Classes: A Reflection on the Value of Cross-Disciplinary Learning。
In the realm of education, students are often presented with a myriad of choices when it comes to selecting their courses. While some may opt for a specialized path, enrolling primarily in classes that align with their major, others may prefer a more holistic approach, embracing courses from a diverse array of disciplines. This essay explores the benefits of choosing classes across disciplines, arguing that such an approach fosters a well-rounded education and prepares students for the complexities of the modern world.One of the primary advantages of cross-disciplinary learning is its ability to expand one's intellectual horizons. By venturing outside of their comfort zones andexploring different fields of study, students expose themselves to new perspectives and ways of thinking. This not only broadens their knowledge base but also cultivates their critical thinking skills, as they learn to connect ideas and concepts from various disciplines. For example, a student who takes courses in history, sociology, and economics gains a more comprehensive understanding of the social and economic factors that have shaped our world.Furthermore, cross-disciplinary learning fosters creativity and innovation. By synthesizing knowledge from different disciplines, students can develop novel approaches to problem-solving and unlock potentialsolutions that may not be apparent through a specialized focus. This is particularly valuable in the workplace, where employees are often required to collaborate with individuals from diverse backgrounds and disciplines. For instance, an engineer who has a background in psychology may be better equipped to design products that are both functional and user-friendly.Additionally, choosing classes across disciplines helpsstudents develop essential life skills. By interacting with peers from different majors and backgrounds, they learn to communicate effectively with people from diverse perspectives. This enhances their interpersonal skills, which are crucial for success in both personal and professional life. Moreover, cross-disciplinary learning promotes adaptability and resilience, as students develop the ability to thrive in changing environments and embrace new challenges.It is important to note that choosing classes across disciplines does not imply neglecting one's major or areas of interest. Rather, it suggests a balanced approach that allows students to explore their passions while also expanding their knowledge and skills. By carefullyselecting courses that complement their major, students can create a curriculum that is both tailored to their aspirations and fosters their overall academic and personal growth.In conclusion, choosing classes across disciplines is a valuable strategy that enriches the educational experienceand prepares students for the demands of the 21st century. It expands intellectual horizons, fosters creativity and innovation, develops essential life skills, and promotes adaptability and resilience. Students who embrace cross-disciplinary learning not only acquire a well-rounded education but also cultivate the critical thinking skills, creativity, and adaptability that are essential for success in an ever-changing world.中文回答:选课之道,跨学科学习的价值。
上高中第一天英语作文
The first day of high school is a pivotal moment in a students life,marking the beginning of a new chapter filled with challenges and opportunities.Heres a detailed English composition about the experience of starting high school:As the morning sun cast its golden rays through my window,I awoke with a mixture of excitement and apprehension.Today was the first day of high school,a day I had been both looking forward to and dreading in equal measure.Preparations and AnticipationI had spent the previous evening meticulously organizing my new school supplies: notebooks with crisp,clean pages,pens that promised to deliver ink with precision,and a planner to keep track of my schedule.The night was filled with restless sleep,punctuated by dreams of navigating unfamiliar hallways and meeting new faces.The Journey to SchoolThe morning rush was a whirlwind of activity.My parents,equally as excited as I was, made sure I had everything I needed.The drive to school was filled with advice and wellwishes.As we pulled into the school parking lot,the sight of hundreds of students, each with their own stories and expectations,was both daunting and exhilarating.Orientation and First ImpressionsThe schools orientation was a crash course in navigating the sprawling campus.I was handed a map and a schedule,both of which seemed to be written in a foreign language. The schools layout was a maze of corridors and staircases,each leading to classrooms filled with the hum of anticipation.Meeting New PeopleThe first day was a blur of introductions.I met my classmates,each with their own unique personalities and stories.Some were outgoing and eager to make new friends, while others seemed as nervous as I was.The teachers,with their diverse teaching styles and expectations,were a new breed of authority figures,each with their own approach to education.Academic ChallengesThe classes themselves were a stark reminder of the academic rigor that lay ahead.The textbooks were heavier,the lectures more complex,and the assignments more demanding. It was clear that high school was not going to be a walk in the park.Extracurricular ActivitiesAfter school,I explored the various clubs and sports teams that the school had to offer. From the robotics club to the debate team,there was a plethora of opportunities to get involved and make the most of my high school experience.Reflections on the DayAs the day drew to a close,I felt a sense of accomplishment.Despite the initial nervousness,I had survived my first day of high school.I had made new friends,learned my way around the school,and even managed to understand some of the more complex concepts in my classes.Looking ForwardThe first day of high school was just the beginning.As I walked out of the school gates,I was filled with a renewed sense of purpose.The challenges of high school awaited,but so did the opportunities for growth,learning,and friendship.In conclusion,the first day of high school is a significant milestone,marking the transition from childhood to adolescence.It is a day filled with firsts,from the first class to the first homework assignment.It is a day that sets the tone for the years to come,a day that is both the end of one journey and the beginning of another.。
高考英语阅读理解预演解密训练(19)
2014高考英语阅读理解预演解密训练(19)及答案阅读理解-----C4[2012·北京卷]AThe Basics of Math—Made ClearBasic Math introduces students to the basic concepts of mathematics, as well as the fundamentals of more tricky areas. These 30 fantastic lectures are designed to provide students with an understanding of arithmetic and to prepare them for Algebra(代数)and beyond.The lessons in Basic Math cover every basic aspect of arithmetic. They also look into exponents(指数), the order of operations, and square roots. In addition to learning how to perform various mathematical operations, students discover why these operations work, how a particular mathematical topic relates to other branches of mathematics, and how these operations can be used practically.Basic Math starts from the relatively easier concepts and gradually moves on to the more troublesome ones, so as to allow for steady and sure understanding of the material by students. The lectures offer students the chance to “make sense” of mathematical knowledge that may have seemed so frightening. They also help students prepare for college mathematics and overcome their anxiety about this amazing—and completely understandable—field of study.By the conclusion of the course, students will have improved their understanding of basic math. They will be able to clear away the mystery(神秘性) of mathematics and face their studies with more confidence than they ever imagined. In addition, they will strengthen their ability to accept new and exciting mathematical challenges.Professor H. Siegel, hono red by Kentucky Educational Television as “the best math teacher in America”, is a devoted teacher and has a gift for explaining mathematical concepts in ways that make them seem clear and obvious. From the basic concrete ideas to the more abstract problems, he is a master in making math lectures learnerfriendlier and less scary.With a PhD in Mathematics Education from Georgia State University, Dr. Siegel teaches mathematics at Central Arizona College. His courses include various makeup classes and a number of lectures for future primary school teachers.If the course fails to provide complete satisfaction to you, you can easilyexchange it for any other course that we offer. Or you can get your money back.56.What does the course Basic Math mainly cover?A.Algebra.B.College Mathematics.C.Arithmetic.D.Mathematics Education.57.What benefits can students expect from Basic Math?A.Stronger imaginative ability.B.Additional presentation skills.C.More mathematical confidence.D.Greater chances of becoming teachers.58.What can we learn about Professor H.Siegel?A.He is a guest lecturer at Kentucky Educational Television.B.He is to deliver 30 lectures in Basic Math.C.He works in Georgia State University.D.He specializes in training teachers.59.Where is the passage most likely to have been taken from?A.A news report.B.A book review.C.A lesson plan.D.An advertisement.【要点综述】本文主要介绍了一个数学课程,从课程内容、功能用途、预期目标、主讲人等方面做了详细说明,是一则招生广告。
古典时代的转变
B. Astronomy
Astronomy
阿波罗尼奥斯
阿基米德
Development of mathematical astronomy
• Eudoxus (欧多克索斯): interconnected homocentric spheres • Pythagoreans(毕达哥拉斯学派):made the radical suggestion that the Earth moved. • Heraclides(赫拉克利德斯):the diurnal movement of the heavens was actually caused by the Earth’s rotating on its axis, and that Mercury and Venus, which always appeared close to the Sun, did so because they revolved about the Sun rather than the Earth. • Aristarchus(阿利斯塔克):the Earth and all the planets revolved around the Sun, and that the Sun like the outer sphere of stars, remained stationary.
Cosmopolitanism of the new civilization
The breakup of the old order
Constant political and social upheaval
Philosophical Schools in the Hellenistic Era
enriched by this new influx as were the non-Greek cultures by the Hellenic expansion. lost something of its earlier confident lucidity(洞察力) and bold originality.
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arXiv:math/0302203v1 [math.CO] 18 Feb 2003
V. Ivanov,
S. Kerov
1. Introduction. This article was originally published in Russian in ”Representation Theory, Dynamical Systems, Combinatorial and Algorithmical Methods III” (A. M. Vershik, ed.), Zapiski Nauchnyh Seminarov POMI 256 (1999), 95–120 (this text in Russian is available via http://www.pdmi.ras.ru/znsl/1999/v256.html). The main purpose of this note is to prove a convolution formula for conjugacy classes in symmetric groups suggested in [7] (formula (2.2), see also [8]). Given a partition ρ ⊢ r of a positive integer r , where r ≤ n, denote by ρ = ρ ∪ (1n−r ) the partition of n obtained from ρ by adding an appropriate number of unities. Let Cρ;n be the sum of permutations w ∈ Sn of cycle type ρ. We also define “normalized” classes Aρ;n = n − r + m1 (ρ) m1 (ρ) Cρ;n , (1.1)
Proof. Obviously, (2) implies (1). To prove that (1) implies (2), we use induction on the size k = |x| of the set x. If k = 0, we have ϕ∅ (b) = b∅,e0 e0 , and the statement is obvious. Let x ⊂ Pn and let v be a permutation of the set x. Denote by d the set of non-fixed points of the permutation v , and by v — the restriction of v on d. Partial permutations (d, w) with ϕx (d, w) = v are characterized by the following conditions: (1) d ⊂ d ⊂ x; (2) the restriction of w on d coincides with v ; (3) all points of d \ d are fixed for w. Thus the coefficient of v in the decomposition of ϕx (b) equals bd,w ,
defines a homomorphism of algebras Bn → C[Sx ]. This homomorphism is obviously surjective. Lemma 3.1. Let b=
k=0 |d|=k w ∈Sd n
bd,w (d, w)
be an element of the algebra Bn . Then the following conditions are equivalent: (1) ϕy (b) = 0 for all y ⊂ x; (2) bd,w = 0 for all d ⊂ x. 2
Partially supported by RFBR grants 98-01-00303 (the first author) and 99-01-00098 (the second author) Typeset by AMS-TEX
1
family with limit B∞ = ← lim − C[Pn ]. The group of finite permutations S∞ acts in B∞ by conjugations. Its orbits Aρ are indexed by all partitions of positive integers, S∞ ρ and form a basis in the algebra of invariants A∞ = B∞ . The numbers gσ,τ arise as the multiplication structure constants of the algebra A∞ in this basis. We show that the algebra A∞ is naturally isomorphic to the algebra of shifted symmetric functions Λ∗ introduced in [3]. This isomorphism plays the same role for convolution of central elements in the algebras C[Sn ] as the characteristic mapping ch plays for the multiplication — inducing of characters of symmetric groups, see [9, I.7]. We also give examples of filtrations on the algebra A∞ . 2. The semigroup of partial permutations. Denote by Pn = {1, . . . , n} a segment of positive integers, and by Sn — the group of all permutations of Pn . A partial permutation of the set Pn is a pair α = (d, w) consisting of an arbitrary subset d ⊂ Pn and an arbitrary bijection w : d → d of this subset. The set d will be referred to as the support of α. Denote by Pn the set of all partial permutations of the set Pn . Obviously, the number of elements in Pn equals
ρ ρ qσ,τ (n) Cρ;n ,
(1.3)
where σ, τ, ρ run only over partitions without unity summands, and the coefficients ρ qσ,τ (n) depend on n in a polynomial way. To prove (1.2), we introduce semigroups Pn of partial permutations of the set {1, 2, . . . , n}. The semigroup algebras C[Pn ] are semi-simple and form a projective
n
sn =
k=0
n k! = kn Nhomakorabea(n ⇂ k ),
k=0
(2.1)
where (n ⇂ k ) = n(n − 1) . . . (n − k + 1) is the falling factorial power. These numbers satisfy a recurrence relation sn = nsn−1 + 1. Several first values are s0 = 1, s1 = 2, s2 = 5, s3 = 16, s4 = 65. Given a partial permutation (d, w) ∈ Pn , denote by w the permutation of the whole set Pn coinciding with w on d and identical outside d. The permutation w is well defined on all subsets containing its support. This allows us to introduce a natural multiplication on the set of partial permutations. Given two partial permutations (d1 , w1 ), (d2 , w2 ), we define their product as the pair (d1 ∪ d2 , w1 w2 ). With this multiplication, Pn becomes a semigroup. The partial permutation (∅, e0 ), where e0 is the trivial permutation of the empty set ∅, is the unity in Pn , and it is a unique invertible element in the semigroup Pn . 3. The semigroup algebra. Denote by Bn = C[Pn ] the complex semigroup algebra of the semigroup Pn . Let us check that this algebra is semi-simple and find its irreducible representations. Fix a subset x ⊂ Pn of size |x| = k and denote by Sx the group of permutations of the subset x. It is easy to see that the formula ϕx (d, w) = w, 0 if d ⊂ x; otherwise (3.1)