Intertwining Operators of Double Affine Hecke Algebras

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单精度浮点算力 英文

单精度浮点算力 英文

单精度浮点算力英文Single-Precision Floating-Point ArithmeticThe field of computer science has witnessed remarkable advancements in the realm of numerical computation, with one of the most significant developments being the introduction of single-precision floating-point arithmetic. This form of numerical representation has become a cornerstone of modern computing, enabling efficient and accurate calculations across a wide range of applications, from scientific simulations to multimedia processing.At the heart of single-precision floating-point arithmetic lies the IEEE 754 standard, which defines the format and behavior of this numerical representation. The IEEE 754 standard specifies that a single-precision floating-point number is represented using 32 bits, with the first bit representing the sign, the next 8 bits representing the exponent, and the remaining 23 bits representing the mantissa or fraction.The sign bit determines whether the number is positive or negative, with a value of 0 indicating a positive number and a value of 1 indicating a negative number. The exponent field, which ranges from-126 to 127, represents the power to which the base (typically 2) is raised, allowing for the representation of a wide range of magnitudes. The mantissa, or fraction, represents the significant digits of the number, providing the necessary precision for accurate calculations.One of the key advantages of single-precision floating-point arithmetic is its efficiency in terms of memory usage and computational speed. By using a 32-bit representation, single-precision numbers require less storage space compared to their double-precision counterparts, which use 64 bits. This efficiency translates into faster data processing and reduced memory requirements, making single-precision arithmetic particularly well-suited for applications where computational resources are limited, such as embedded systems or mobile devices.However, the reduced bit-width of single-precision floating-point numbers comes with a trade-off in terms of precision. Compared to double-precision floating-point numbers, single-precision numbers have a smaller range of representable values and a lower level of precision, which can lead to rounding errors and loss of accuracy in certain calculations. This limitation is particularly relevant in fields that require high-precision numerical computations, such as scientific computing, financial modeling, or engineering simulations.Despite this limitation, single-precision floating-point arithmeticremains a powerful tool in many areas of computer science and engineering. Its efficiency and performance characteristics make it an attractive choice for a wide range of applications, from real-time signal processing and computer graphics to machine learning and data analysis.In the realm of real-time signal processing, single-precision floating-point arithmetic is often employed in the implementation of digital filters, audio processing algorithms, and image/video processing pipelines. The speed and memory efficiency of single-precision calculations allow for the processing of large amounts of data inreal-time, enabling applications such as speech recognition, noise cancellation, and video encoding/decoding.Similarly, in the field of computer graphics, single-precision floating-point arithmetic plays a crucial role in rendering and animation. The representation of 3D coordinates, texture coordinates, and color values using single-precision numbers allows for efficient memory usage and fast computations, enabling the creation of complex and visually stunning graphics in real-time.The rise of machine learning and deep neural networks has also highlighted the importance of single-precision floating-point arithmetic. Many machine learning models and algorithms can be effectively trained and deployed using single-precision computations,leveraging the performance benefits without significant loss of accuracy. This has led to the widespread adoption of single-precision floating-point arithmetic in the development of AI-powered applications, from image recognition and natural language processing to autonomous systems and robotics.In the field of scientific computing, the use of single-precision floating-point arithmetic is more nuanced. While it can be suitable for certain types of simulations and numerical calculations, the potential for rounding errors and loss of precision may necessitate the use of higher-precision representations, such as double-precision floating-point numbers, in applications where accuracy is of paramount importance. Researchers and scientists often carefully evaluate the trade-offs between computational efficiency and numerical precision when choosing the appropriate floating-point representation for their specific needs.Despite its limitations, single-precision floating-point arithmetic remains a crucial component of modern computing, enabling efficient and high-performance numerical calculations across a wide range of applications. As technology continues to evolve, it is likely that we will see further advancements in the representation and handling of floating-point numbers, potentially addressing the challenges posed by the trade-offs between precision and computational efficiency.In conclusion, single-precision floating-point arithmetic is a powerful and versatile tool in the realm of computer science, offering a balance between memory usage, computational speed, and numerical representation. Its widespread adoption across various domains, from real-time signal processing to machine learning, highlights the pivotal role it plays in shaping the future of computing and technology.。

More on the order of prolongations and restrictions

More on the order of prolongations and restrictions

2
Transformation to Fourier space
As is well-known, the Fourier transform (F u)(ξ ) := (2π )−d/2 u(j )e−ij·ξ
j ∈Zd
defines isomorphism between ℓ2 (Zd ) and L2 (Td ), where T = R/2π Z. Its adjoint F ∗ = F −1 is given by (F ∗ v )(j ) = (2π )−d/2 We will need the following lemma: Lemma 2.1 e
β∈Zd /AZd iβ·A−T 2π α
=
iβ·A−T 2π α β∈[0,M )d ∩Zd e lim . M →∞ #[0, M )d ∩ Zd / #Zd /AZd
(1)
There exists an m ∈ {1, . . . , d} with (A−T α)m ∈ Z. On the other hand, there exists a 0 = q ∈ N with q (A−T α)m ∈ Z. We conclude that for any M ∈ q N, the numerator at the right hand side of (1) is zero, and thus that iβ·A−T 2π α = 0. 2 β∈Zd /AZd e As the Fourier transform is a bijection between the rapidly decreasing functions and C ∞ (T), the symbols p ˆ(ξ ) :=

半导体器件双语词汇

半导体器件双语词汇

Doping profile(掺杂分布)Step junction(突变结)One-side Step junction(单边突变结)Diffussion(扩散)Graded junction (缓变结)Gradient(梯度)Net charge(净电荷)Depletion(耗尽层)Space charge region(空间电荷区)Potential barrier region(势垒区)Electric field(电场)Built-in potential(内建电场)Space charge region width(空间电荷区宽度)Quantative calculation(定量的)Qualitative(定性的)Substrate (衬底的)Forward bias(正偏)Reverse bias(反偏)Non-uniform doping(非均匀掺杂)Linearly graded junction(线性缓变结)Ideal-diode equation (理想二极管方程)Ideal pn junction model(理想pn结模型)Using boltgmann approximation(波尔兹曼近似)No generation and recombination inside the deletion layer(耗尽区内没有产生与复合)Low injection(小注入)Step junction with abrupt depletion layer approximation(突变结耗尽层近似)Mathmatical model(数学模型)Reverse saturation current(反向饱和电流)High junction(大注入)Small-signal model of pn junction(小信号)pn(结模型)Diffusion capacitance(扩散电容)Depletion layer capacitance(势垒电容)Junction capacitance(结电容)Breakdown voltage of pn junction pn(结击穿电压) Avalanche Breakdown (雪崩击穿)Tunnel Breakdown(隧道击穿)Transient of pn junction pn(结瞬态特性)Model and model parameters of pn junction diode (二极管模型和模型参数)Base width modulation and early voltage(基区宽变效应和厄利电压)Cutoff frequency(截止频率)JFET (junction field effect transistor)MESFET(metal semiconductor)Enhancement(增强型)Depletion (耗尽型)Flat band voltage(平带电压)11111。

微积分专有名词中英文对照

微积分专有名词中英文对照

微积分专有名词中英文对照微积分专有名词中英文对照absolutely convergent 绝对收敛absolute value 绝对值algebraic function 代数函数analytic geometry 解析几何antiderivative 不定积分approximate integration 近似积分approximation 近似法、逼近法arbitrary constant 任意常数arithmetic series/progression (AP)算数级数asymptotes (vertical and horizontal)(垂直/水平)渐近线average rate of change 平均变化率base 基数binomial theorem 二项式定理,二项展开式Cartesian coordinates 笛卡儿坐标(一般指直角坐标) Cartesian coordinates system 笛卡儿坐标系Cauch’s Mean Value Theorem 柯西均值定理chain rule 链式求导法则calculus 微积分学closed interval integral 闭区间积分coefficient 系数composite function 复合函数conchoid 蚌线continuity (函数的)连续性concavity (函数的)凹凸性conditionally convergent 有条件收敛continuity 连续性critical point 临界点cubic function 三次函数cylindrical coordinates 圆柱坐标decreasing function 递减函数decreasing sequence 递减数列definite integral 定积分derivative 导数determinant 行列式differential coefficient 微分系数differential equation 微分方程directional derivative 方向导数discontinuity 不连续性discriminant (二次函数)判别式disk method 圆盘法divergence 散度divergent 发散的domain 定义域dot product 点积double integral 二重积分ellipse 椭圆ellipsoid 椭圆体epicycloid 外摆线Euler's method (BC)欧拉法expected valued 期望值exponential function 指数函数extreme value heorem 极值定理factorial 阶乘finite series 有限级数fundamental theorem of calculus 微积分基本定理geometric series/progression (GP)几何级数gradient 梯度Green formula 格林公式half-angle formulas 半角公式harmonic series 调和级数helix 螺旋线higher derivative 高阶导数horizontal asymptote 水平渐近线horizontal line 水平线hyperbola 双曲线hyper boloid 双曲面implicit differentiation 隐函数求导implicit function 隐函数improper integral 广义积分、瑕积分increment 增量increasing function 增函数indefinite integral 不定积分independent variable 自变数inequality 不等式ndeterminate form 不定型infinite point 无穷极限infinite series 无穷级数infinite series 无限级数inflection point (POI) 拐点initial condition 初始条件instantaneous rate of change 瞬时变化率integrable 可积的integral 积分integrand 被积分式integration 积分integration by part 分部积分法intercept 截距intermediate value of Theorem :中间值定理inverse function 反函数irrational function 无理函数iterated integral 逐次积分Laplace transform 拉普拉斯变换law of cosines 余弦定理least upper bound 最小上界left-hand derivative 左导数left-hand limit 左极限L'Hospital's rule 洛必达法则limacon 蚶线linear approximation 线性近似法linear equation 线性方程式linear function 线性函数linearity 线性linearization 线性化local maximum 极大值local minimum 极小值logarithmic function 对数函数MacLaurin series 麦克劳林级数maximum 最大值mean value theorem (MVT)中值定理minimum 最小值method of lagrange multipliers 拉格朗日乘数法modulus 绝对值multiple integral 多重积分multiple 倍数multiplier 乘子octant 卦限open interval integral 开区间积分optimization 优化法,极值法origin 原点orthogonal 正交parametric equation (BC)参数方程partial derivative 偏导数partial differential equation 偏微分方程partial fractions 部分分式piece-wise function 分段函数parabola 抛物线parabolic cylinder 抛物柱面paraboloid :抛物面parallelepiped 平行六面体parallel lines 并行线parameter :参数partial integration 部分积分partiton :分割period :周期periodic function 周期函数perpendicular lines 垂直线piecewise defined function 分段定义函数plane 平面point of inflection 反曲点point-slope form 点斜式polar axis 极轴polar coordinates 极坐标polar equation 极坐标方程pole 极点polynomial 多项式power series 幂级数product rule 积的求导法则quadrant 象限quadratic functions 二次函数quotient rule 商的求导法则radical 根式radius of convergence 收敛半径range 值域(related) rate of change with time (时间)变化率rational function 有理函数reciprocal 倒数remainder theorem 余数定理Riemann sum 黎曼和Riemannian geometry 黎曼几何right-hand limit 右极限Rolle's theorem 罗尔(中值)定理root 根rotation 旋转secant line 割线second derivative 二阶导数second derivative test 二阶导数试验法second partial derivative 二阶偏导数series 级数shell method (积分)圆筒法sine function 正弦函数singularity 奇点slant 母线slant asymptote 斜渐近线slope 斜率slope-intercept equation of a line 直线的斜截式smooth curve 平滑曲线smooth surface 平滑曲面solid of revolution 旋转体symmetry 对称性substitution 代入法、变量代换tangent function 正切函数tangent line 切线tangent plane 切(平)面tangent vector 切矢量taylor's series 泰勒级数three-dimensional analytic geometry 空间解析几何total differentiation 全微分trapezoid rule 梯形(积分)法则。

Twisted vertex representations via spin groups and the McKay correspondence

Twisted vertex representations via spin groups and the McKay correspondence
1991 Mathematics Subject Classification. Primary: 17B, 20. Key words and phrases. twisted vertex operators, double cover of wreath product, spin characters. Research of Frenkel is supported by NSF grant DMS-9700765; research of Jing is supported by NSF grant DMS159v2 [math.QA] 27 Jul 2000
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 .

dSCFT Correspondence in Two Dimensions

dSCFT Correspondence in Two Dimensions
Here we discuss the case of two-dimensional de Sitter space. The asymptotic boundary I−
is a circle, which upon a Wick rotation turns into time. rmal quantum mechanical model. We shall explicitly construct this model for the case of a scalar particle, obtain the generators of the conformal group, calculate the eigenvalues of the
then comment on what changes need to be made to turn φ periodic (finite temperature).
Consider a scalar field Φ of mass m. It obeys the wave equation in de Sitter space
(14)
which differs from [12] by a phase. The Green function for the modes Φ+k can be obtained from
G+(q, φ; q′, φ′) =
dk k
Φ+k (q,
−φ)Φ+k (q′
,
φ′).
(15)
After some algebra, we arrive at
The two-dimensional de Sitter space (dS2) may be parametrized as

Generalized aggregation operators for intuitionistic fuzzy sets

Generalized aggregation operators for intuitionistic fuzzy sets

Generalized Aggregation Operators for Intuitionistic Fuzzy SetsHua Zhao,1,2Zeshui Xu,2∗Mingfang Ni,1Shousheng Liu21Institute of Communications Engineering,PLA University of Science and Technology,Nanjing210007,People’s Republic of China2Institute of Sciences,PLA University of Science and Technology,Nanjing 210007,People’s Republic of ChinaThe generalized ordered weighted averaging(GOW A)operators are a new class of operators, which were introduced by Yager(Fuzzy Optim Decision Making2004;3:93–107).However,it seems that there is no investigation on these aggregation operators to deal with intuitionistic fuzzy or interval-valued intuitionistic fuzzy information.In this paper,wefirst develop some new general-ized aggregation operators,such as generalized intuitionistic fuzzy weighted averaging operator, generalized intuitionistic fuzzy ordered weighted averaging operator,generalized intuitionistic fuzzy hybrid averaging operator,generalized interval-valued intuitionistic fuzzy weighted averag-ing operator,generalized interval-valued intuitionistic fuzzy ordered weighted averaging operator, generalized interval-valued intuitionistic fuzzy hybrid average operator,which extend the GOW A operators to accommodate the environment in which the given arguments are both intuitionistic fuzzy sets that are characterized by a membership function and a nonmembership function,and interval-valued intuitionistic fuzzy sets,whose fundamental characteristic is that the values of its membership function and nonmembership function are intervals rather than exact numbers,and study their properties.Then,we apply them to multiple attribute decision making with intuitionistic fuzzy or interval-valued intuitionistic fuzzy information.C 2009Wiley Periodicals,Inc.1.INTRODUCTIONSince its appearance in1965,1the fuzzy set theory has been widely used in manyfields in our modern society.Atanassov2generalized fuzzy set to intuitionistic fuzzy set(IFS),which is a powerful tool to deal with vagueness.3A prominent characteristic of IFS is that it assigns to each element a membership degree and a nonmembership degree.Gau and Buehrer4introduced the concept of vague set.Chen and Tan5and Hong and Choi6presented some techniques for handling multicriteria fuzzy decision-making problems based on vague sets.But Bustince and Burillo7 showed that vague sets are intuitionistic fuzzy sets.In the past two decades,many authors have paid attention to the IFS theory.For example,Atanassov and Gargov8∗Author to whom all correspondence should be addressed:e-mail:xu zeshui@ INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS,VOL.25,1–30(2010)C 2009Wiley Periodicals,Inc.Published online in Wiley InterScience().•DOI10.1002/int.203862ZHAO ET AL.defined the notion of interval-valued intuitionistic fuzzy set,which is characterized by a membership function and a nonmembership function whose values are inter-vals rather than exact numbers.Interval-valued intuitionistic fuzzy set(IVIFS)is a generalization of the notion of IFS in the spirit of interval-valued fuzzy set.9They also showed that IFSs are equivalent to interval-valued fuzzy sets.Up to now,the research on IFSs and IVIFSs is only about their basic theory and applications,but there is little research on the aggregation method of intuitionistic fuzzy or interval-valued intuitionistic fuzzy information.10,11So it is necessary to investigate such questions.The research on aggregation operators is an interesting topic,which has received increasing attention in a number of research papers12–14and also in other papers.Yager15extended the ordered weighted averaging(OWA)operator,16which has been used in many applications to provide a new class of operators called the generalized OWA(GOWA)operators.These operators add to the OWA operator an additional parameter controlling the power to which the argument values are raised. At the same time,he proved that the GOWA operators are mean operators.Yet it is worthy of pointing out that the GOWA operators have not been extended to ac-commodate intuitionistic fuzzy or interval-valued intuitionistic fuzzy environment. However,in many real-life problems,we need to aggregate the given intuitionistic fuzzy or interval-valued intuitionistic fuzzy arguments into a single one.In such cases,information fusion techniques are necessary.In this paper,based on the GOWA operators we will introduce some new in-tuitionistic fuzzy aggregation operators,such as generalized intuitionistic fuzzy weighted averaging(GIFWA)operator,generalized intuitionistic fuzzy ordered weighted average(GIFOWA)operator,and generalized intuitionistic fuzzy hybrid average(GIFHA)operator.Then,we will extend them to the interval-valued intu-itionistic fuzzy environments and study the properties of all the above-mentioned aggregation operators.Furthermore,we apply them to multiple attribute decision making with intuitionistic fuzzy or interval-valued intuitionistic fuzzy information.2.PRELIMINARIESAtanassov2generalized the concept of fuzzy set1and defined the concept of IFS as follows:Let a set X befixed.An IFS A in X is an object having the form:A={ x,μA(x),νA(x) |x∈X}(1)where the functionsμA:X→[0,1]and v A:X→[0,1]define the degree of membership and the degree of nonmembership of the element x∈X to A,respec-tively,and for every x∈X:0≤μA(x)+νA(x)≤1(2)For each IFS A in X,ifπA(x)=1−μA(x)−νA(x),for all x∈X(3)thenπA(x)is called the degree of indeterminacy of x to A.International Journal of Intelligent Systems DOI10.1002/intAGGREGATION OPERATORS FOR INTUITIONISTIC FUZZY SETS3For computational convenience,Xu 10called α=(μα,να)an intuitionistic fuzzy value (IFV).The IFV α=(μα,να)has a physical interpretation,for ex-ample,if (μα,να)=(0.3,0.2),then it can be interpreted as “the vote for resolution is 3in favor,2against,and 5abstentions”.4D EFINITION 1.10,11Let α=(μα,να),α1=(μα1,να1),and α2=(μα2,να2)be three IFVs,then the following operational laws are valid:1.α1⊕α2=(μα1+μα2−μα1μα2,να1να2);2.α1⊗α2=(μα1μα2,να1+να2−να1να2);3.λα=(1−(1−μα)λ,νλα),λ>0;4.αλ=(μλα,1−(1−να)λ),λ>0.T HEOREM 1.10,11Let α=(μα,να),α1=(μα1,να1),and α2=(μα2,να2)be threeIFVs,and let ˙α1=α1⊕α2,˙α2=α1⊗α2,˙α3=λα,˙α4=αλ,λ>0,then all ˙αi (i =1,2,3,4)are IFVs.By the operational laws in Definition 1,we haveT HEOREM 2.10,11Let α=(μα,να),α1=(μα1,να1),α2=(μα2,να2),and α3=(μα3,να3)be four IFVs,λ,λ1,λ2>0then1.λ1α⊕λ2α=(λ1+λ2)α;2.(α1⊕α2)⊕α3=α1⊕(α2⊕α3);3.((α)λ1)λ2=(α)λ1λ2.Based on the IFVs,Chen and Tan 5introduced a score function s to evaluate the degree of suitability that an alternative satisfies a decision maker’s requirement.Let α=(μα,να)be an IFV ,whereμα∈[0,1],να∈[0,1],μα+να≤1(4)The score of αcan be evaluated by the score function s shown ass (α)=μα−να(5)where s (α)∈[−1,1].The function s is used to measure the score of an IFV .From (5),we know that the score of αis directly related to the deviation between μαand να,i.e.,the higher the degree of deviation between μαand να,the bigger the score of α,thus,the larger the IFV α.On the basis of the minimum and maximum operations,Chen and Tan 5utilized the score function to develop a technique for handling multiple attribute decision-making problems in which the characteristics of alternatives are represented by ter,Hong and Choi 6defined an accuracy function to evaluate the degree ofInternational Journal of Intelligent SystemsDOI 10.1002/int4ZHAO ET AL.accuracy of the IFV α=(μα,να)ash (α)=μα+να(6)where h (α)∈[0,1].The larger the value of h (α),the higher the degree of accuracy of the degree of membership of the IFV α.Then,Hong and Choi 6utilized the score function,the accuracy function,and the minimum and maximum operations 5to develop another technique for handling multiple attribute decision-making problems based on intuitionistic fuzzy information.As presented above,the score function s and the accuracy function h are,respectively,defined as the difference and the sum of the membership function μand the nonmembership function ν.Hong and Choi 6showed that the relation between the score function s and the accuracy function h is similar to the relation between mean and variance in statistics.On the basis of the score function s and the accuracy function h ,in the following,Xu and Yager 11gave an order relation between two IFVs,which is defined as follows:D EFINITION 2.11Let α=(μα,να)and β=(μβ,νβ)be two IFVs,s (α)=μα−ναand s (β)=μβ−νβbe the scores of αand β,respectively,and h (α)=μα+ναand h (β)=μβ+νβbe the accuracy degrees of αand β,respectively,then1.If s (α)<s (β),then αis smaller than β,denoted by α<β;2.If s (α)=s (β),theni.If h (α)=h (β),then αand βrepresent the same information,denoted by α=β;ii.If h (α)<h (β),then αis smaller than β,denoted by α<β.On the basis of the GOWA operator and Definitions 1and 2,we have introduced some new aggregation operators.3.THE GIFWA,GIFOWA,AND GIFHA OPERATORS3.1.The GWA and GOWA OperatorsD EFINITION 3.A generalized weighted averaging (GWA)operator of dimension n is a mapping GWA:(R +)n →R +,which has the following form:GWA (a 1,a 2,...,a n )=⎛⎝n j =1w j a λj⎞⎠1/λ(7)where λ>0,w =(w 1,w 2,...,w n )T is the weight vector of the arguments a j (j =1,2,...,n ),with w j ≥0,j =1,2,...,n ,and n j =1w j =1,and R +is the set of all nonnegative real numbers.Another aggregation operator called the GOWA operators is the generalization of the OWA operator.International Journal of Intelligent SystemsDOI 10.1002/intAGGREGATION OPERATORS FOR INTUITIONISTIC FUZZY SETS5D EFINITION 4.15A generalized ordered weighted averaging (GOWA)operator of dimension n is a mapping GOWA:I n →I ,which has the following form:GOWA (a 1,a 2,...,a n )=⎛⎝n j =1w j b λj⎞⎠1/λ(8)where λ>0,w =(w 1,w 2,...,w n )T is the weight vector of (a 1,a 2,...,a n ),w j ≥0,j =1,2,...,n ,and n j =1w j =1,b j is the jth largest of a i ,I =[0,1].When we use different choices of the parameters λand w ,we will get some special cases.Some of the special operators have been used in situations where the input arguments are IFVs,such as the weighted averaging (WA)operator,the ordered weighted averaging (OWA)operator,10the weighted geometric (WG)operator,the ordered weighted geometric (OWG)operator.11But there are still a large number of special operators that have not been extended to the situations where the input arguments are intuitionistic fuzzy or interval-valued intuitionistic fuzzy ones.In the following section,we will extend the GWA and GOWA operators to accommodate the situations where the input arguments are intuitionistic fuzzy or interval-valued intuitionistic fuzzy ones.3.2.The GIFWA OperatorFor convenience,let V be the set of all IFVs.D EFINITION 5.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs and GIFWA:V n →V ,ifGIFWA w (α1,α2,...,αn )=w 1αλ1⊕w 2αλ2⊕···⊕w n αλn1/λ(9)then the function GIFWA is called a GIFWA operator,where λ>0,w =(w 1,w 2,...,w n )T is a weight vector associated with the GIFWA operator,with w j ≥0,j =1,2,...,n ,and nj =1w j =1.T HEOREM 3.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,then their aggregated value by using the GIFWA operator is also an IFV ,andGIFWA w (α1,α2,...,αn )=⎛⎜⎝⎛⎝1−n j =11−μλαjw j⎞⎠1/λ,1−⎛⎝1−n j =11−(1−ναj )λ w j ⎞⎠1/λ⎞⎟⎠(10)International Journal of Intelligent Systems DOI 10.1002/int6ZHAO ET AL.where λ>0,w =(w 1,w 2,...,w n )T is a weight vector associated with the GIFWA operator,with w j ≥0,j =1,2,...,n ,and n j =1w j =1.Proof.The first result follows quickly from Definition 3and Theorem 1.In the following,we first provew 1αλ1⊕w 2αλ2⊕···⊕w n αλn=⎛⎝1−n j =11−μλαjw j,n j =11−(1−ναj )λ wj ⎞⎠(11)by using mathematical induction on n :1.For n =2:sinceαλ1= μλα1,1−(1−να1)λ ,αλ2= μλα2,1−(1−να2)λ thenw 1αλ1⊕w 2αλ2=⎛⎝1−2 j =11−μλαjw j ,2 j =11−(1−ναj )λ w j⎞⎠2.If Equation 11holds for n =k ,that isw 1αλ1⊕w 2αλ2⊕···⊕w k αλk =⎛⎝1−k j =11−μλαjw j ,k j =11−(1−ναj )λ w j⎞⎠then,when n =k +1,by the operational laws (1),(2),and (4)in Definition 1,we havew 1αλ1⊕w 2αλ2⊕···⊕w k +1αλk +1=⎛⎝1−k j =11−μλαjw j ,k j =11−(1−ναj )λ w j ⎞⎠⊕ 1− 1−μλαk +1w k +1, 1−(1−ναk +1)λ w k +1 =⎛⎝1−k +1 j =11−μλαjw j ,k +1 j =11−(1−ναj )λ wj ⎞⎠International Journal of Intelligent Systems DOI 10.1002/intAGGREGATION OPERATORS FOR INTUITIONISTIC FUZZY SETS 7i.e.Equation 11holds for n =k +1.Thus,Equation 11holds for all n .ThenGIFW A w (α1,α2,...,αn )=⎛⎝1−n j =11−μλαjw j ,n j =11−(1−ναj )λ w j⎞⎠1/λ=⎛⎝⎛⎝1−n j =11−μλαjw j ⎞⎠1/λ,1−⎛⎝1−nj =11−(1−ναj )λ w j ⎞⎠1/λ⎞⎠.Example 1.Let α1=(0.1,0.7),α2=(0.4,0.3),α3=(0.6,0.1),and α4=(0.2,0.5)be four IFVs,w =(0.2,0.3,0.1,0.4)T be the weight vector of αj (j =1,2,3,4),and be λ=2,thenμα1=0.1,μα2=0.4,μα3=0.6,μα4=0.2να1=0.7,να2=0.3,να3=0.1,να4=0.5ThusGIFWA w (α1,α2,α3,α4)=(0.3381,0.3717).On the basis of Theorem 2,we have the following properties of the GIFWA operators:T HEOREM 4.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,λ>0,and w =(w 1,w 2,...,w n )T be the weight vector associated with the GIFWA op-erator,with w j ≥0,j =1,2,...,n ,and n j =1w j =1.If all αj (j =1,2,...,n )are equal,i.e.αj =α,for all j ,thenGIFWA w (α1,α2,...,αn )=α.Proof.By Theorem 2,we haveGIFWA w (α1,α2,...,αn )=(w 1αλ1⊕w 2αλ2⊕···⊕w n αλn )1/λ=(w 1αλ⊕w 2αλ⊕···⊕w n αλ)1/λ=((w 1+w 2+···+w n )αλ)1/λ=(αλ)1/λ=α.T HEOREM 5.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,λ>0,and w =(w 1,w 2,...,w n )T be the weight vector related to the GIFWA operator,International Journal of Intelligent SystemsDOI 10.1002/int8ZHAO ET AL.with w j ≥0,j =1,2,...,n,n j =1w j =1,and letα−= min j(μαj ),max j(ναj ) ,α+= max j(μαj ),min j(ναj )Thenα−≤GIFWA w (α1,α2,...,αn )≤α+.(12)Proof.Since min j(μαj )≤μαj ≤max j(μαj )and min j(ναj )≤ναj ≤max j(ναj ),for all j ,thennj =1(1−μλαj )w j≥n j =11−(max j(μαj ))λw j=1−(max j(μαj ))λand then⎛⎝1−n j =11−μλαjw j⎞⎠1/λ≤max j(μαj )(13)Similarly,we have⎛⎝1−n j =1 1−μλαjw j⎞⎠1/λ≥min j(μαj )(14)n j =11−(1−ναj )λ wj ≤n j =11− 1−max j(ναj )λ w j =1− 1−max j(ναj ) λ1−n j =11−(1−ναj )λ wj ≥ 1−max j(ναj )λ⎛⎝1−n j =11−(1−ναj )λ wj ⎞⎠1/λ≥1−max(jναj )1−⎛⎝1−n j =11−(1−ναj )λ wj ⎞⎠1/λ≤max j(ναj ).(15)International Journal of Intelligent Systems DOI 10.1002/intAGGREGATION OPERATORS FOR INTUITIONISTIC FUZZY SETS9Similarly,we have1−⎛⎝1−n j =11−(1−ναj )λ wj ⎞⎠1/λ≥min j(ναj ).(16)Let GIFWA w (α1,α2,...,αn )=α=(μα,να),thens (α)=μα−να≤max j(μαj )−min j(ναj )=s (α+)s (α)=μα−να≥min j(μαj )−max j(ναj )=s (α−).If s (α)<s (α+)and s (α)>s (α−),then by Definition 2,we haveα−<GIFWA w (α1,α2,...,αn )<α+.(17)If s (α)=s (α+),i.e.μα−να=max j(μαj )−min j(ναj ),then by (13)and (16),we haveμα=max j(μαj ),να=min j(ναj ).Soh (α)=μα+να=max j(μαj )+min j(ναj )=h (α+).Then by Definition 2,we haveGIFWA w (α1,α2,...,αn )=α+.(18)If s (α)=s (α−),i.e.μα−να=min j(μαj )−max j(ναj ),then by (14)and (15),we haveμα=min j(μαj ),να=max j(ναj ).Soh (α)=μα+να=min j(μαj )+max j(ναj )=h (α−).Thus,from Definition 2,it follows thatGIFWA w (α1,α2,...,αn )=α−(19)and then from Equations 17–19,we know that Equation.12always holds.International Journal of Intelligent SystemsDOI 10.1002/int10ZHAO ET AL.T HEOREM 6.Let αj =(μαj ,ναj )(j =1,2,...,n )and α∗j =(μα∗j ,να∗j )(j =1,2,...,n )be two collections of IFVs and w =(w 1,w 2,...,w n )T be the weight vector related to the GIFWA operator,where w j ≥0,j =1,2,...,n ,and nj =1w j =1,λ>0,if μαj ≤μα∗j and ναj ≥να∗j ,for all j ,thenGIFWA w (α1,α2,...,αn )≤GIFWA w (α∗1,α∗2,...,α∗n ).(20)Proof.Since μαj ≤μα∗j and ναj ≥να∗j ,for all j ,thenn j =11−μλαj w j ≥n j =11−μλα∗j w j1−n j =11−μλαj w j≤1−n j =11−μλα∗jw j ⎛⎝1−n j =11−μλαjw j⎞⎠1/λ≤⎛⎝1−n j =11−μλα∗jw j⎞⎠1/λn j =11−(1−ναj )λ wj ≥n j =11−(1−να∗j )λ w j 1−n j =11−(1−ναj )λ w j ≤1−n j =11−(1−να∗j )λ w j ⎛⎝1−n j =11−(1−ναj )λ w j ⎞⎠1/λ≤⎛⎝1−n j =11−(1−να∗j )λ wj ⎞⎠1/λ1−⎛⎝1−n j =11−(1−ναj )λ wj ⎞⎠1/λ≥1−⎛⎝1−n j =11−(1−να∗j )λ wj ⎞⎠1/λInternational Journal of Intelligent Systems DOI 10.1002/intAGGREGATION OPERATORS FOR INTUITIONISTIC FUZZY SETS11⎛⎝1−nj=11−μλαjwj⎞⎠1/λ−⎛⎜⎝1−⎛⎝1−nj=11−(1−ναj)λwj⎞⎠1/λ⎞⎟⎠≤⎛⎝1−nj=11−μλα∗jwj⎞⎠1/λ−⎛⎜⎝1−⎛⎝1−nj=11−(1−να∗j)λwj⎞⎠1/λ⎞⎟⎠.(21) Letα=GIFWA w(α1,α2,...,αn),α∗=GIFWA w(α∗1,α∗2,...,α∗n),then byEquation21,we haves(α)≤s(α∗).If s(α)<s(α∗),then by Definition2,we haveGIFWA w(α1,α2,...,αn)<GIFWA w(α∗1,α∗2,...,α∗n)(22) If s(α)=s(α∗),then⎛⎝1−nj=11−μλαjwj⎞⎠1/λ−⎛⎜⎝1−⎛⎝1−nj=11−(1−ναj)λwj⎞⎠1/λ⎞⎟⎠=⎛⎝1−nj=11−μλα∗jwj⎞⎠1/λ−⎛⎜⎝1−⎛⎝1−nj=11−(1−να∗j)λwj⎞⎠1/λ⎞⎟⎠.Sinceμαj ≤μα∗jandναj≥να∗j,for all j,then we have⎛⎝1−nj=11−μλαjwj⎞⎠1/λ=⎛⎝1−nj=11−μλα∗jwj⎞⎠1/λ1−⎛⎝1−nj=11−(1−ναj)λwj⎞⎠1/λ=1−⎛⎝1−nj=11−(1−να∗j)λwj⎞⎠1/λ.Henceh(α)=⎛⎝1−nj=11−μλαjwj⎞⎠1/λ+⎛⎜⎝1−⎛⎝1−nj=11−(1−ναj)λwj⎞⎠1/λ⎞⎟⎠International Journal of Intelligent Systems DOI10.1002/int12ZHAO ET AL.=⎛⎝1−n j =11−μλα∗jw j⎞⎠1/λ+⎛⎜⎝1−⎛⎝1−n j =11−(1−να∗j )λ w j ⎞⎠1/λ⎞⎟⎠=h (α∗)thus,by Definition 2,we haveGIFWA w (α1,α2,...,αn )=GIFWA w (α∗1,α∗2,...,α∗n ).(23)From Equations 22and 23,we know that Equation 20always holds.We now look at some special cases obtained by using different choices of theparameters w and λ.T HEOREM 7.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,λ>0,and w =(w 1,w 2,...,w n )T be the weight vector related to the GIFWA operator with w j ≥0(j =1,2,...,n ),and n j =1w j =1,then1.If λ=1,then the GIFWA operator (9)is reduced to the following :IFW A w (α1,α2,...,αn )=w 1α1⊕w 2α2⊕···⊕w n αn ,which is called an intuitionistic fuzzy weighted average operator .102.If λ→0,then the GIFWA operator (9)is reduced to the following :IFWG w (α1,α2,...,αn )=αw 11⊗αw 22⊗···⊗αw nn ,which is called an intuitionistic fuzzy weighted geometric operator .113.If λ→+∞,then the GIFWA operator (9)is reduced to the following :IFMAX w (α1,α2,...,αn )=max j(αj ),which is called an intuitionistic fuzzy maximum operator .54.If w =(1/n,1/n,...,1/n )T and λ=1,then the GIFWA operator (9)is reduced to the following :IFA w (α1,α2,...,αn )=1n(α1⊕α2⊕···⊕αn ),which is called an intuitionistic fuzzy average operator .105.If w =(1/n,1/n,...,1/n )T and λ→0,then the GIFWA operator (9)is reduced to the following :IFG w (α1,α2,...,αn )=(α1⊗α2⊗···⊗αn )1/n ,which is called an intuitionistic fuzzy geometric operator .11International Journal of Intelligent SystemsDOI 10.1002/intAGGREGATION OPERATORS FOR INTUITIONISTIC FUZZY SETS133.3.The GIFOWA OperatorD EFINITION 6.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,and let GIFOWA:V n →V ,ifGIFOWA w (α1,α2,...,αn )= w 1αλσ(1)⊕w 2αλσ(2)⊕···⊕w n αλσ(n ) 1/λ(24)where λ>0,w =(w 1,w 2,···,w n )T is an associated weight vector such that w j ≥0,j =1,2,...,n ,and n j =1w j =1,ασ(j )is the j th largest of αj ,then the function GIFOWA is called a GIFOWA operator.The GIFOWA operator has some properties similar to those of the GIFWA operator.T HEOREM 8.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,then their aggregated value by using the GIFOWA operator is also an IFV ,and GIFOWA w (α1,α2,...,αn )=⎛⎜⎝⎛⎝1−n j =11−μλασ(j ) w j ⎞⎠1/λ,1−⎛⎝1−n j =11−(1−νασ(j ))λ w j ⎞⎠1/λ⎞⎟⎠(25)where λ>0,w =(w 1,w 2,···,w n )T is an weight vector related to the GIFOWA operator such that w j ≥0,j =1,2,...,n ,and n j =1w j =1,ασ(j )is the j th largest of αj .Example 2.Let α1=(0.3,0.6),α2=(0.4,0.5),α3=(0.6,0.3),α4=(0.7,0.1),and α5=(0.1,0.6)be five IFVs,and w =(0.1117,0.2365,0.3036,0.2365,0.1117)T be the weight vector of αj (j =1,2,3,4,5).Let λ=2,thenμα1=0.3,μα2=0.4,μα3=0.6,μα4=0.7,μα5=0.1να1=0.6,να2=0.5,να3=0.3,να4=0.1,να5=0.6.Let us calculate the scores of αj (j =1,2,3,4,5):s (α1)=0.3−0.6=−0.3,s (α2)=0.4−0.5=−0.1,s (α3)=0.6−0.3=0.3s (α4)=0.7−0.1=0.6,s (α5)=0.1−0.6=−0.5.Sinces (α4)>s (α3)>s (α2)>s (α1)>s (α5)International Journal of Intelligent SystemsDOI 10.1002/int14ZHAO ET AL.thenασ(1)=(0.7,0.1),ασ(2)=(0.6,0.3),ασ(3)=(0.4,0.5)ασ(4)=(0.3,0.6)ασ(5)=(0.1,0.6)and thus,by Equation 25,we haveGIFOWA w (α1,α2,α3,α4,α5)=(0.4762,0.3762).T HEOREM 9.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,andw =(w 1,w 2,...,w n )T be the weight vector related to the GIFOWA operator,with w j ≥0,j =1,2,...,n ,andn j =1w j =1.If all αj (j =1,2,...,n )are equal,i.e.αj =α,for all j ,thenGIFOWA w (α1,α2...,αn )=α.T HEOREM 10.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,andw =(w 1,w 2,...,w n )T be the weight vector related to the GIFOWA operator,with w j ≥0,j =1,2,...,n ,andn j =1w j =1,and letα−=(min j(μαj ),max j(ναj )),α+=(max j(μαj ),min j(ναj ))thenα−≤GIFOWA w (α1,α2...,αn )≤α+.T HEOREM 11.Let αj =(μαj ,ναj )(j =1,2,...,n )and α∗j =(μα∗j ,να∗j )(j =1,2,...,n )be two collections of IFVs and w =(w 1,w 2,...,w n )T be the weight vector related to the GIFOWA operator,with w j ≥0,j =1,2,...,n ,and nj =1w j =1.If μαj ≤μα∗j and ναj ≥να∗j ,for all j ,thenGIFOWA w (α1,α2...,αn )≤GIFOWA w (α∗1,α∗2...,α∗n ).T HEOREM 12.Let αj =(μαj ,ναj )(j =1,2,...,n )and αj =(μα j ,να j )(j =1,2,...,n )be two collections of IFVs,λ>0,and w =(w 1,w 2,...,w n )T be the weight vector related to the GIFOWA operator,with w j ≥0,j =1,2,...,n ,and nj =1w j =1,thenGIFOWA w (α1,α2...,αn )=GIFOWA w (α 1,α 2...,α n )(26)where (α 1,α 2...,α n )Tis any permutation of (α1,α2...,αn )T .International Journal of Intelligent Systems DOI 10.1002/intAGGREGATION OPERATORS FOR INTUITIONISTIC FUZZY SETS15Proof.LetGIFOWA w (α1,α2...,αn )= w 1αλσ(1)⊕w 2αλσ(2)⊕···⊕w n αλσ(n )1/λGIFOWA w (α 1,α 2...,α n )= w 1(α σ(1))λ⊕w 2(α σ(2))λ⊕···⊕w n (α σ(n ))λ 1/λ.Since (α 1,α 2...,α n )T is any permutation of (α1,α2...,αn )T ,thenασ(j )=ασ(j ),j =1,2,...,nthen Equation 26holds.From (26),we know that the GIFOWA operator has commutativity propertythat we desire.It is worth noting that the GIFWA operator does not have this property.We now look at some special cases obtained by using different choices of the parameters w and λ.T HEOREM 13.Let αj =(μαj ,ναj )(j =1,2,...,n )be a collection of IFVs,λ>0and w =(w 1,w 2,...,w n )T be the weight vector related to the GIFOWA operator,with w j ≥0,j =1,2,...,n,n j =1w j =1,then1.If λ=1,then the GIFOWA operator (24)is reduced to the following :IFOW A w (α1,α2,...,αn )=w 1ασ(1)⊕w 2ασ(2)⊕···⊕w n ασ(n ),which is called an intuitionistic fuzzy ordered weighted average operator .102.If λ→0,then the GIFOWA operator (24)is reduced to the following :IFOWG w (α1,α2,...,αn )=αw 1σ(1)⊗αw 2σ(2)⊗···⊗αw nσ(n ),which is called an intuitionistic fuzzy ordered weighted geometric operator .113.If λ→+∞,then the GIFOWA operator (24)is reduced to the following :IFMAX w (α1,α2,...,αn )=max j(αj ),which is called an intuitionistic fuzzy maximum operator .54.If w =(1/n,1/n,...,1/n )T and λ=1,then the GIFOWA operator (24)is reduced to the following :IFA w (α1,α2,...,αn )=1n(α1⊕α2⊕···⊕αn ),which is called an intuitionistic fuzzy average operator .10International Journal of Intelligent SystemsDOI 10.1002/int16ZHAO ET AL.5.If w =(1/n,1/n,...,1/n )T and λ→0,then the GIFOWA operator (24)is reduced to the following :IFG w (α1,α2,...,αn )=(α1⊗α2⊗···⊗αn )1/n ,which is called an intuitionistic fuzzy geometric operator .116.If w =(1,0,...,0)T ,then the GIFOWA operator (24)is reduced to the following :IFMAX w (α1,α2,...,αn )=max j(αj ),which is called an intuitionistic fuzzy maximum operator .57.If w =(0,0,...,1)T ,then the GIFOWA operator (24)is reduced to the following :IFMIN w (α1,α2,...,αn )=min j(αj ),which is called an intuitionistic fuzzy minimum operator .53.4.The GIFHA OperatorConsider that the GIFWA operator weighs only the IFVs,whereas the GIFOWA operator weighs only the ordered positions of the IFVs instead of weighing the IFVs themselves.To overcome this limitation,motivated by the idea of combining the WA and OWA operators,14,17in what follows,we developed a generalized intuitionistic fuzzy hybrid aggregation (GIFHA)operator,which weighs both the given IFV and its ordered position.D EFINITION 7.A GIFHA operator of dimension n is a mapping GIFHA:V n →V ,which has an associated vector w =(w 1,w 2,···,w n )T ,with w j ≥0,j =1,2,...,n ,and nj =1w j =1,such thatGIFHA w,ω(α1,α2...,αn )=(w 1(˙ασ(1))λ⊕w 2(˙ασ(2))λ⊕···⊕w n (˙ασ(n ))λ)1/λ(27)where λ>0,˙ασ(j )is the j th largest of the weighted IFVs ˙αj (˙αj =nωj αj ,j =1,2,...,n ),ω=(ω1,ω2,...,ωn )Tis the weight vector of αj (j =1,2,...,n )with ωj ≥0,and n j =1ωj =1,and n is the balancing coefficient,which plays a role of balance (in such a case,if the vector (ω1,ω2,...,ωn )T approaches (1/n,1/n,...,1/n )T ,then the vector (nω1α1,nω2α2,...,nωn αn )T approaches (α1,α2,...,αn )T ).Let ˙ασ(j )=(μ˙ασ(j ),ν˙ασ(j )),then,similar to Theorem 3,we have GIFHA w,ω(α1,α2,...,αn )=⎛⎜⎝⎛⎝1−n j =11−μλ˙ασ(j )w j ⎞⎠1/λ,1−⎛⎝1−n j =11−(1−ν˙ασ(j ))λ w j ⎞⎠1/λ⎞⎟⎠,(28)International Journal of Intelligent Systems DOI 10.1002/intAGGREGATION OPERATORS FOR INTUITIONISTIC FUZZY SETS17 and the aggregated value derived by using the GIFHA operator is also an IFV. Especially,ifλ=1,then(28)is reduced to the following form:IFHA w,ω(α1,α2,...,αn)=⎛⎝1−nj=1(1−μ˙ασ(j))w j,nj=1νw j˙ασ(j)⎞⎠,which is called an intuitionistic fuzzy hybrid-averaging(IFHA)operator.10T HEOREM14.The GIFOWA operator is a special case of the GIFHA operator. Proof.Letω=(1/n,1/n,...,1/n)T,then˙αj=αj(j=1,2,...,n),so we have GIFHA w,ω(α1,α2,...,αn)=(w1(˙ασ(1))λ⊕w2(˙ασ(2))λ⊕···⊕w n(˙ασ(n))λ)1/λ=(w1αλσ(1)⊕w2αλσ(2)⊕···⊕w nαλσ(n))1/λ=GIFOWA w(α1,α2,...,αn).This completes the proof of Theorem14.Example3.Letα1=(0.2,0.5),α2=(0.4,0.2),α3=(0.5,0.4),α4=(0.3,0.3), andα5=(0.7,0.1)befive IFVs,and letω=(0.25,0.20,0.15,0.18,0.22)T be the weight vector ofαj(j=1,2,3,4,5),then by the operational law(3)in Definition1, we get the weighted intuitionistic fuzzy values as˙α1=(0.234,0.42),˙α2=(0.4,0.2),˙α3=(0.405,0.503),˙α4=(0.275,0.338),˙α5=(0.734,0.079).By Equation5,we calculate the scores of˙αj(j=1,2,3,4,5):s(˙α1)=−0.177,s(˙α2)=0.2,s(˙α3)=−0.098,s(˙α4)=−0.063,s(˙α5)=0.655.Sinces(˙α5)>s(˙α2)>s(˙α4)>s(˙α3)>s(˙α1)then˙ασ(1)=(0.734,0.079),˙ασ(2)=(0.4,0.2),˙ασ(3)=(0.275,0.338)˙ασ(4)=(0.405,0.503),˙ασ(5)=(0.234,0.42).International Journal of Intelligent Systems DOI10.1002/int。

q-difference intertwining operators for $U_q(sl(n))$ general setting and the case $n=3$

q-difference intertwining operators for $U_q(sl(n))$ general setting and the case $n=3$
ASI-TPA/10/93 (October 1993), hepth/9405150; Published in: J. Phys. A: Math. Gen. 27 (1994) 4841-4857; Note Added published in: J. Phys. A: Math. Gen. 27 (1994) 6633-6634.
Introduction Invariant differential equations I f = 0 play a very important role in the description
of physical symmetries - recall, e.g., the examples of Dirac, Maxwell equations, (for more examples cf., e.g., [1]). It is an important and yet unsolved problem to find such equations for the setting of quantum groups, where they are expected as q -difference equations, especially, in the case of non-commuting variables. The approach to this problem used here relies on the following. In the classical situation the invariant differential operators I giving the equations above may be described as operators intertwining representations of complex and real semisimple Lie groups [2], [3], [4], [5]. There are many ways to find such operators, cf., e.g., [1], however, most of these rely on constructions which are not available for quantum groups. Here we shall apply a procedure [5] which is rather algebraic and can be generalized almost straightforwardly to quantum groups. According to this procedure one first needs to know these constructions for the complex semisimple Lie groups since the consideration of a real semisimple Lie group involves also its complexification. That is why we start here with the case of Uq (sl(n)) (we write sl(n) instead of sl(n, C I )). For the procedure one needs q -difference realizations of the representations in terms of functions of non-commuting variables. Until now such a realization of the representations and of the intertwining operators was found only for a Lorentz quantum algebra (dual to the matrix Lorentz quantum group of [6]) in [7]. The construction in [7] (also applying the procedure of [5]) involves two q -commuting variables η η ¯ = qη ¯η and uses the complexification Uq (sl(2)) ⊗ Uq (sl(2)) of the Lorentz quantum algebra. In the present paper following the mentioned procedure we construct representations π ˆr ¯ = {r1 , . . . , rn−1 } and acting ¯ of Uq (sl (n)) labelled by n − 1 complex numbers r in the spaces of formal power series of n(n − 1)/2 non-commuting (for n > 2) variables Yij , 1 ≤ j < i ≤ n. These variables generate a flag manifold of the matrix quantum group SLq (n) which is dual to Uq (sl(n)) . For generic ri ∈ C I the representations π ˆr ¯ are irreducible. We give the values of ri when the representations π ˆr ¯ are reducible. It is in the latter cases that there arise various partial equivalences among these representations. These partial equivalences are realized by q - difference intertwining operators for which 2

美国“数学大联盟杯赛”常用英文词汇

美国“数学大联盟杯赛”常用英文词汇

美国“数学大联盟杯赛”(中国赛区)初赛常用英文词汇$美元符号Aacute 锐角的add 计算…总和/加,做加法addition 加,加法adjacent angle 邻角adjacent 邻近的altitude (尤指海拔)高度A.M. 上午amount 数量angle 角arc 弧,弓形area 范围,区域,面积arithmetic 算术,算法arithmetic sequence 等差数列arrangement 排列assume 假定average 平均,平均数/平均的Bbag 袋子base 底billion 十亿/十亿的bisector 二等分线,平分线blond 白肤金发碧眼的Ccalculate 计算calculation 计算capacity 容量cent 美分center 中心/中央的centimeter 厘米circular 圆形的circle 圆周,圆circumference 圆周column 列common 共通的, 公约的congruent 全等的constant 常数/不变的coordinate 坐标corner 角count 数,计算/计数,计算cousin 堂[表]兄弟,堂[表]姊妹crate 箱子cross 交叉的cube 立方体,立方cubic 立方体的,立方的cylindrical 圆柱的Ddecimal 十进制的,小数的/小数define 定义degree 度数denominator 分母determine 确定diagonal 对角线的,对角线diagram 图表diameter 直径diamond 菱形difference 差额digit 阿拉伯数字dime (美元)十美分dimension 尺寸divide 除division 除法divisor 除数,约数dollar (符号为$) 美元double 两倍/使加倍Eeight 八,第八eighteen 十八的,十八个的equal 相等的/等于equation 方程式,等式equilateral 等边的/等边形equivalent 相等的,相当的/相等estimate 估计evaluate 估计,求…的值even 偶数的/偶数example 例子,例题expansion 展开express 表达,表示expression 式,表达式,符号exterior 外部的Fface 表面factor因子,因数female 女的,雌性的fifteen 十五fifth 第五的figure 圆形find 得到first 首先,第一/第一的five 五,五个formula 公式forklift 铲车four 四,四个fraction 分数function 函数Ggeometrical 几何学的,几何的geometric sequence 等比数列graph 图表greatest common divisor 最大公约数,最大公因子Hhalf 一半/一半的hectare 公顷(等于1万平方米) height 高度,海拔hexagon 六角形,六边形horizontal 水平的how 多少,多么hundred 百,百个hyperbola 双曲线hypotenuse 直角三角形之斜边Iinequality 不等式infinite 无限的,无数的inscribe 使内切integer 整数interior 内部的intersect 相交,交叉intersection 交集,交叉点isosceles等腰三角形Kkilometer 千米,公里Lleast common multiple 最小公倍数length 长度less 少的,小的lift 举起,使升起,提起,抬起line segment 线段line 直线liter 公升Mmale 男的,雄性的map 地图,图mark 记号,符号,标记mass 质量mathematics 数学maximum 最大量/最大极限的mean 平均的/平均数measure 测量meter 米,公尺midpoint 中点,正中央million 百万,百万个minimum 最小的,最低的mixed number 带分数multiply 乘Nnatural number 自然数negative 负数/负的nickel (美元)五美分nine 九,九个ninety 九十number 数,数字numerator 分子numerical 数字的,用数表示的Ooctagon 八边形,八角形odd 奇数的one 一,一个operation 运算Pparabola 抛物线parallel 平行的parallelogram 平行四边形penny 一美分pentagon 五角形,五边形per 每一percent 百分比,百分数percentage 百分比,百分数,百分率perfect cube 完全立方perfect square 完全平方perimeter 周长,周界perpendicular 垂直的,正交的plus 加上P.M. 下午point 点,分数polygon 多变形,多角形polynomial 多项式positive 正的prime 质数prism 棱柱probability 概率product 乘积proportion 比例pyramid 角锥,棱锥Qquadrilateral 四边形quarter 四分之一,二十五(美分) quotient 商Rradius半径ratio 比,比率real number 实数reciprocal 倒数,倒数的rectangle长方形,矩形rectangular矩形的,成直角的region 区域regular 等边的remainder 余数rhombus 菱形,斜方形right 直角的root根rotation 旋转,轮转,循环row 行Ssatisfy 满足scale 比例second 秒/第二sector 扇形segment 段semi 半sequence 数学sequence 数列,序列series 连续,系列,级数seven 七,七个seventh 第七shape 外形side 边sign 符号simplify 简化six 六,六个size 大小,尺寸slope 斜率solid 立体solution 解答,解决sphere 球,球体,范围square root 平方根square 正方形straight 直的subtract 减去,减subtraction 减少sum 总和suppose 假设surface 表面surface area 表面积symmetric 对称性的Tten 十,十个tenth 第十,十分之一term 项third 第三,三分之一thousand 一千,一千个three 三time 次,度,回,倍trapezoid 梯形triangle 三角形tub 桶twelve 十二twenty 二十,二十个two 二,两个tangent 切线,相切的than 与…相比较total 总数/总的triple 三倍数twice 两次,两倍Vvalue 值variable 变数/变量的vertex 顶点vertical 垂直的volume 体积Wwidth 宽度Zzero 零点,零。

A theory of tensor products for vertex operator algebra satsifying C_2-cofiniteness

A theory of tensor products for vertex operator algebra satsifying C_2-cofiniteness

Abstract The recent researchs show that C2 -cofiniteness is a natural conditition to consider a vertex operator algebra with finitely many simple modules. Therefore, we extended the tensor product theory of vertex operator algebras developed by Huang and Lepowsky without assuming the compatibility condition nor the semisimplicity of grading operator so that we could apply it to all vertex operator algebras satisfying only C2 -cofiniteness. We also showed that the tensor product theory develops naturally if we include not only ordinary modules, but also weak modules with a composition series of finite length (we call it an Artin module). Actually, a C2 -cofiniteness on V is enough to show that a tensor product of two Artin modules is again an Arting module and we have natural commutativity and associativity of tensor products. Namely, the category of Artin modules becomes a braided tensor category. Our main purpose is an application of the tensor product theory under C2 cofiniteness. We determined the representation theory of orbifold models. For example, if a vertex operator algebra V has a finite automorphism group G and the fixed point vertex operator subalgebra V G is C2 -cofinite, then for g ∈ G and any irreducible V g -module W , there is an element h ∈ g such that W is contained in some h-twisted V -module. Furthermore, if V G is rational, then V g is also rational for any g ∈ G.

高等数学中定义定理的英文表达

高等数学中定义定理的英文表达

高等数学中定义定理的英文表达Value of function :函数值Variable :变数Vector :向量Velocity :速度Vertical asymptote :垂直渐近线Volume :体积X-axis :x轴x-coordinate :x坐标x-intercept :x截距Zero vector :函数的零点Zeros of a polynomial :多项式的零点TTangent function :正切函数Tangent line :切线Tangent plane :切平面Tangent vector :切向量Total differential :全微分Trigonometric function :三角函数Trigonometric integrals :三角积分Trigonometric substitutions :三角代换法Tripe integrals :三重积分SSaddle point :鞍点Scalar :纯量Secant line :割线Second derivative :二阶导数Second Derivative Test :二阶导数试验法Second partial derivative :二阶偏导数Sector :扇形Sequence :数列Series :级数Set :集合Shell method :剥壳法Sine function :正弦函数Singularity :奇点Slant asymptote :斜渐近线Slope :斜率Slope-intercept equation of a line :直线的斜截式Smooth curve :平滑曲线Smooth surface :平滑曲面Solid of revolution :旋转体Space :空间Speed :速率Spherical coordinates :球面坐标Squeeze Theorem :夹挤定理Step function :阶梯函数Strictly decreasing :严格递减Strictly increasing :严格递增Sum :和Surface :曲面Surface integral :面积分Surface of revolution :旋转曲面Symmetry :对称RRadius of convergence :收敛半径Range of a function :函数的值域Rate of change :变化率Rational function :有理函数Rationalizing substitution :有理代换法Rational number :有理数Real number :实数Rectangular coordinates :直角坐标Rectangular coordinate system :直角坐标系Relative maximum and minimum :相对极大值与极小值Revenue function :收入函数Revolution , solid of :旋转体Revolution , surface of :旋转曲面Riemann Sum :黎曼和Riemannian geometry :黎曼几何Right-hand derivative :右导数Right-hand limit :右极限Root :根P、QParabola :拋物线Parabolic cylinder :抛物柱面Paraboloid :抛物面Parallelepiped :平行六面体Parallel lines :并行线Parameter :参数Partial derivative :偏导数Partial differential equation :偏微分方程Partial fractions :部分分式Partial integration :部分积分Partiton :分割Period :周期Periodic function :周期函数Perpendicular lines :垂直线Piecewise defined function :分段定义函数Plane :平面Point of inflection :反曲点Polar axis :极轴Polar coordinate :极坐标Polar equation :极方程式Pole :极点Polynomial :多项式Positive angle :正角Point-slope form :点斜式Power function :幂函数Product :积Quadrant :象限Quotient Law of limit :极限的商定律Quotient Rule :商定律M、N、OMaximum and minimum values :极大与极小值Mean Value Theorem :均值定理Multiple integrals :重积分Multiplier :乘子Natural exponential function :自然指数函数Natural logarithm function :自然对数函数Natural number :自然数Normal line :法线Normal vector :法向量Number :数Octant :卦限Odd function :奇函数One-sided limit :单边极限Open interval :开区间Optimization problems :最佳化问题Order :阶Ordinary differential equation :常微分方程Origin :原点Orthogonal :正交的LLaplace transform :Leplace 变换Law of Cosines :余弦定理Least upper bound :最小上界Left-hand derivative :左导数Left-hand limit :左极限Lemniscate :双钮线Length :长度Level curve :等高线L'Hospital's rule :洛必达法则Limacon :蚶线Limit :极限Linear approximation:线性近似Linear equation :线性方程式Linear function :线性函数Linearity :线性Linearization :线性化Line in the plane :平面上之直线Line in space :空间之直线Lobachevski geometry :罗巴切夫斯基几何Local extremum :局部极值Local maximum and minimum :局部极大值与极小值Logarithm :对数Logarithmic function :对数函数IImplicit differentiation :隐求导法Implicit function :隐函数Improper integral :瑕积分Increasing/Decreasing Test :递增或递减试验法Increment :增量Increasing Function :增函数Indefinite integral :不定积分Independent variable :自变数Indeterminate from :不定型Inequality :不等式Infinite point :无穷极限Infinite series :无穷级数Inflection point :反曲点Instantaneous velocity :瞬时速度Integer :整数Integral :积分Integrand :被积分式Integration :积分Integration by part :分部积分法Intercepts :截距Intermediate value of Theorem :中间值定理Interval :区间Inverse function :反函数Inverse trigonometric function :反三角函数Iterated integral :逐次积分HHigher mathematics 高等数学/高数E、F、G、HEllipse :椭圆Ellipsoid :椭圆体Epicycloid :外摆线Equation :方程式Even function :偶函数Expected Valued :期望值Exponential Function :指数函数Exponents , laws of :指数率Extreme value :极值Extreme Value Theorem :极值定理Factorial :阶乘First Derivative Test :一阶导数试验法First octant :第一卦限Focus :焦点Fractions :分式Function :函数Fundamental Theorem of Calculus :微积分基本定理Geometric series :几何级数Gradient :梯度Graph :图形Green Formula :格林公式Half-angle formulas :半角公式Harmonic series :调和级数Helix :螺旋线Higher Derivative :高阶导数Horizontal asymptote :水平渐近线Horizontal line :水平线Hyperbola :双曲线Hyper boloid :双曲面DDecreasing function :递减函数Decreasing sequence :递减数列Definite integral :定积分Degree of a polynomial :多项式之次数Density :密度Derivative :导数of a composite function :复合函数之导数of a constant function :常数函数之导数directional :方向导数domain of :导数之定义域of exponential function :指数函数之导数higher :高阶导数partial :偏导数of a power function :幂函数之导数of a power series :羃级数之导数of a product :积之导数of a quotient :商之导数as a rate of change :导数当作变率right-hand :右导数second :二阶导数as the slope of a tangent :导数看成切线之斜率Determinant :行列式Differentiable function :可导函数Differential :微分Differential equation :微分方程partial :偏微分方程Differentiation :求导法implicit :隐求导法partial :偏微分法term by term :逐项求导法Directional derivatives :方向导数Discontinuity :不连续性Disk method :圆盘法Distance :距离Divergence :发散Domain :定义域Dot product :点积Double integral :二重积分change of variable in :二重积分之变数变换in polar coordinates :极坐标二重积分CCalculus :微积分differential :微分学integral :积分学Cartesian coordinates :笛卡儿坐标图片一般指直角坐标Cartesian coordinates system :笛卡儿坐标系Cauch’s Mean Value Theorem :柯西均值定理Chain Rule :连锁律Change of variables :变数变换Circle :圆Circular cylinder :圆柱Closed interval :封闭区间Coefficient :系数Composition of function :函数之合成Compound interest :复利Concavity :凹性Conchoid :蚌线Cone :圆锥Constant function :常数函数Constant of integration :积分常数Continuity :连续性at a point :在一点处之连续性of a function :函数之连续性on an interval :在区间之连续性from the left :左连续from the right :右连续Continuous function :连续函数Convergence :收敛interval of :收敛区间radius of :收敛半径Convergent sequence :收敛数列series :收敛级数Coordinate:s:坐标Cartesian :笛卡儿坐标cylindrical :柱面坐标polar :极坐标rectangular :直角坐标spherical :球面坐标Coordinate axes :坐标轴Coordinate planes :坐标平面Cosine function :余弦函数Critical point :临界点Cubic function :三次函数Curve :曲线Cylinder:圆柱Cylindrical Coordinates :圆柱坐标A、BAbsolute convergence :绝对收敛Absolute extreme values :绝对极值Absolute maximum and minimum :绝对极大与极小Absolute value :绝对值Absolute value function :绝对值函数Acceleration :加速度Antiderivative :反导数Approximate integration :近似积分Approximation :逼近法by differentials :用微分逼近linear :线性逼近法by Simpson’s Rule :Simpson法则逼近法by the Trapezoidal Rule :梯形法则逼近法Arbitrary constant :任意常数Arc length :弧长Area :面积under a curve :曲线下方之面积between curves :曲线间之面积in polar coordinates :极坐标表示之面积of a sector of a circle :扇形之面积of a surface of a revolution :旋转曲面之面积Asymptote :渐近线horizontal :水平渐近线slant :斜渐近线vertical :垂直渐近线Average speed :平均速率Average velocity :平均速度Axes, coordinate :坐标轴Axes of ellipse :椭圆之轴Binomial series :二项级数。

金融数学英语词汇

金融数学英语词汇

i nteger 整数even 偶数odd 奇数divisor 除数,约数real number 实数positive whole number 正整数negative whole number 负整数consecutive integer 连续的整数quotient 商multiple 倍数remainder 余数prime number 质数,素数prime factor 质因子,质因数composite number 合数numerator 分子denominator 分母divisor 因子,除数greatest common divisor 最大公约数least commom multiple 最小公倍数common multiple 公倍数common factor 公因子reciprocal 倒数inverse 倒数mixed number 带分数improper fraction 假分数proper fraction 真分数vulgar fraction 普通分数common fraction 普通分数simple fraction 简分数complex fraction 繁分数decimal system 十进制digit 位units digit 个位数tens digit 十位数tenths unit 十分位3-digit number 三位数decimal point 小数点decimal fraction 純小数infinite decimal 无穷小数recurring decimal 循环小数absolute value 绝对值nonzero number 非零数natural number 自然数positive number 正数negative number 负数nonnegative 非负的rational 有理数irrational 无理数common ration 公比direct proportion 正比percent 百分比base 底数power 指数square root 平方根cube root 立方根common logarithm 常用对数radical sign 根号root sign 根号cardinal 基数ordinal 序数subset 子集union 合集,并集intersection 交集proper subset 真子集solution set 解集average 平均数median 中数mode 众数arithmetic mean 算术平均数weighted average 加权平均数geometric mean 几何平均数maximun 最大值minimum 最小值range 值域dispersion 差量,离差standard dispersion 标准方差frequency distribution 频数分布normal distribution 正态分布factorial notation 阶乘permutations 排列combination 组合add 加plus 加subtract 减minus 减multiple 乘times 乘divide 除difference 差sum 和total 总数;总计division 除;部分divisible 可被整除的divided evenly 被整除dividend 被除数coefficient 系数numercial coefficient 数字系数literal coefficient 字母系数term 项constant term 常数项quadratic 二次方程equivalent equation 同解方程,等价方程linear equation 线性方程solution 方程的解inequality 不等式expression 表达式linear 一次的,线性的factorization 因数分解function 函数trigonometric function 三角函数inverse function 反函数complementary function 余函数variable 变量domain 定义域sequence 数列arithmetic progression 等差数列geometric progression 等比数列a line segment 线段endpoint 端点midpoint 中点a right angle 直角perpendicular 垂线perpendicular lines 垂直线perpendicular bisector 垂直平分线parallel lines 平分线bisect 平分vertical angle 对顶角a straight line 直线acute angle 锐角obtuse angle 钝角vertex angle 顶角round angle 周角straight angle 平角included angle 夹角alternate angle 内错角interior angle 内角central angle 圆心角exterior angle 外角supplementary angles 补角complementary angles 余角adjacent angle 领角angle bisector 角平分线diagonal 对角线intersect 相交quadrilateral 四边形pentagon 五边形hexagon 六边形heptagon 七边形octagon 八边形nonagon 九边形decagon 十边形polugon 多边形multilateral 多边的parallelogram 平行四边形equilateral 等边形square 正方形rectangle 长方形regular polygon 正多边形rhombus 菱形trapezoid 梯形congruent 全等的isosceles triangle 等腰三角形equilateral triangle 等边三角形scalene triangle 不等边三角形right triangle 直角三角形oblique 斜三角形inscribed triangle 内接三角形hypotenuse 斜边leg 直角边included side 夹边arm 直角三角形的股median of a triangle 三角形的中线opposite 直角三角形的对边altitude 三角形的高vertex 顶点base 底circle 圆形semicircle 半圆concentric circle 同心圆cross section 横截面center of a circle 圆心chord 弦diameter 直径radius 半径circumference 圆周长arc 弧surface area 表面积radian 弧度segment of a circle 弧形point of tangency 切点tangent 正切inscribe 内切,内接circumscribe 外切,外接edge 边cube 立方体rectangular solid 长方体length 长width 宽altitude 高depth 深度regular solid 正多面体regular polyhedron 正多面体cylinder 圆柱体cone 圆锥sphere 球体pyramid 角锥volume 体积dimension 维数coordinate plane 坐标表面abscissa 横坐标ordinate 纵坐标number line 横轴coordinate system 坐标系rectangular coordinate 直角坐标系x-axis x轴origin 原点quadrant 象限slope 斜率intercept 截距a unique solution 唯一解no solution 无解parabola 抛物线。

两浮点数相等的精度 英文

两浮点数相等的精度 英文

两浮点数相等的精度英文The Precision of Comparing Two Floating-Point Numbers for Equality.In the realm of computer programming, comparing two floating-point numbers for equality can often be a challenging task. This is due to the inherent limitations of floating-point representations, which can lead to slight imprecisions even when two numbers appear to be identical. Understanding these limitations and implementing appropriate strategies for comparing floating-point numbers are crucial for ensuring the accuracy and reliability of numerical computations.1. The Nature of Floating-Point Numbers.Floating-point numbers are representations used in computers to approximate real numbers. They consist of a sign, an exponent, and a mantissa (or fraction). While this representation allows for a wide range of numbers to berepresented, it also introduces approximations and rounding errors.For example, the decimal number 0.1 cannot be represented exactly in binary floating-point format. Instead, it is approximated with a nearby binary fraction. This approximation can lead to slight differences when comparing two floating-point numbers that should be equalin theory.2. The Issue of Precision.When comparing two floating-point numbers for equality, the issue of precision arises. Due to rounding errors and approximations, two numbers that are mathematically equal may not be considered equal when represented as floating-point values. For instance, the result of a computation may be slightly off by a very small amount, which can lead to incorrect decisions or unexpected behavior.3. Strategies for Comparing Floating-Point Numbers.To address the issue of precision, several strategies can be employed when comparing floating-point numbers:3.1 Absolute Tolerance.One approach is to use an absolute tolerance, which isa fixed value that defines the maximum allowable difference between two numbers for them to be considered equal. If the absolute difference between the two numbers is less than or equal to the tolerance, they are considered equal.3.2 Relative Tolerance.Another approach is to use a relative tolerance, whichis based on the magnitude of the numbers being compared.The relative tolerance is typically expressed as a fraction or percentage of the larger number. If the absolute difference between the two numbers is less than or equal to the product of the relative tolerance and the larger number, they are considered equal.3.3 Ultra-precise Comparisons.In some scenarios, such as financial calculations,ultra-precise comparisons may be required. In these cases, specialized libraries or data types can be used thatprovide higher precision floating-point representations and comparison functions.4. The Importance of Understanding Precision.Understanding the limitations of floating-pointprecision is crucial for writing accurate and reliable code. Failing to consider precision can lead to errors in computations, incorrect decisions, and unexpected behavior. By employing appropriate comparison strategies, developers can mitigate these issues and ensure the accuracy of their numerical computations.5. Conclusion.In summary, comparing two floating-point numbers for equality requires a careful consideration of precision limitations. By understanding the nature of floating-pointnumbers and employing appropriate comparison strategies, developers can ensure the accuracy and reliability of their numerical computations. This understanding is essential for writing robust and dependable software that handlesfloating-point numbers effectively.。

复变函数与积分变换中的英文单词和短语讲解

复变函数与积分变换中的英文单词和短语讲解

复变函数与积分变换Functions of ComplexVariable and IntegralTransforms第一章复数与复变函数Chapter 1 Complex Numbers and Functions of Complex Varialble 复数complex number实部real number虚部imaginary unit纯虚数pure imaginary number共轭复数complex conjugate number运算operation减法subtraction乘法multiplication除法division复平面complex plane分配律distribute rule交换律exchange rule复合函数complex function复数的三角形式trigonometrical form of complexnumber模modulus辐角argument乘方power开方extraction开集open set闭集closed set邻域neighborhood充分必要条件sufficient and necessary condition 边界点boundary point 有界集bounded set区域domain简单闭曲线simple closed curve连通区域connected region分段光滑piecewise smooth无穷远点point at infinity复变函数function of complex variable 单值函数single-valued function 多值函数multi-valued function连续continuity不等式inequality第二章解析函数Chapter 2 Analytic Functions微分differential奇点singularity解析函数analytic function导数derivative柯西-黎曼方程Cauchy-Riemann equation 调和函数harmonic function 指数函数exponential function对数函数logarithm function三角函数trigonometric function双曲函数hyperbolic function幂函数power function高阶导数higher order derivative求导法则derivation rule链式法则chain rule定义域domain导函数derivative function反函数inverse function复变函数与积分变换中的英文单词和短语第三章复变函数的积分Chapter 3 Integrals of functions of complex variable 柯西积分公式Cauchy integral formula柯西不等式Cauchy inequality第四章解析函数的级数表示Chapter 4 Series Expressions of Analytic Functions 复函数序列sequences of complex function级数series幂级数power series函数项级数series of functions收敛性convergence收敛半径radius of convergence泰勒级数Taylor series洛朗级数Laurent series发散divergence麦克劳林级数Maclaurin series泰勒级数展开Taylor series expansion绝对收敛absolutely convergent一致收敛uniform convergence部分和partial sum第五章留数及其应用Chapter 5 Residues and their Applications 留数residue 孤立奇点isolated singularity可去奇点removable singularity本性奇点essential singularity极点polem阶极点pole of order m当且仅当if and only if亚纯函数meromorphic function第六章共形映射Chapter 6Conformal Mappings从A到B的转角oriented angle from a to b保角映射angle-preserving mapping自映射self-mapping不动点fixed point分式线性变换linear fractional transformation 多边形polygon第七章傅里叶变换Chapter 7Fourier Transforms傅里叶变换Fourier transform傅里叶积分Fourier integral卷积convolution线性性linearity对称性symmetry延迟性time shifting积分变换integral transform反演公式inversion formula共轭傅里叶积分conjugate Fourier integral广义傅里叶积分generalized Fourier integral傅里叶逆变换inverse Fourier transform傅里叶反演公式Fourier inversion formula傅里叶正弦变换Fourier sine transform傅里叶余弦变换Fourier cosine transform第八章拉普拉斯变换Chapter 8Laplace Transforms 拉普拉斯变换Laplace transform像image。

国际高中生必读39国际高中AP微积分必考单词汇总

国际高中生必读39国际高中AP微积分必考单词汇总

国际高中生必读39国际高中AP微积分必考单词汇总1. Derivative (导数)2. Integral (积分)3. Limits (极限)4. Continuous (连续)5. Differentiation (微分)6. Integration (积分)7. Function (函数)8. Polynomial (多项式)9. Trigonometry (三角函数)10. Exponential (指数)11. Logarithm (对数)12. Rational (有理数)13. Irrational (无理数)14. Variable (变量)15. Equation (方程)16. Inequality (不等式)17. Convergence (收敛)18. Divergence (发散)19. Differentiable (可微)20. Tangent (切线)21. Derivative chain rule (导数链式法则)22. Implicit differentiation (隐式微分法)23. Critical point (临界点)24. Critical value (临界值)25. Relative maximum (相对最大值)26. Relative minimum (相对最小值)27. Concave up (向上凹)28. Concave down (向下凹)29. Inflection point (拐点)30. Riemann sum (黎曼和)31. Fundamental theorem of calculus (微积分基本定理)32. Mean value theorem (极值定理)33. Antiderivative (原函数)34. Improper integral (不定积分)35. Series (级数)36. Taylor series (泰勒级数)37. Power series (幂级数)38. Maclaurin series (麦克劳林级数)。

Full field algebras, operads and tensor categories

Full field algebras, operads and tensor categories

a r X i v :m a t h /0603065v 3 [m a t h .Q A ] 16 O c t 2006Full field algebras,operads and tensor categories Liang Kong Abstract We study the operadic and categorical formulations of (conformal)full field algebras.In particular,we show that a grading-restricted R ×R -graded full field algebra is equivalent to an algebra over a partial operad constructed from spheres with punctures and local coordinates.This result is general-ized to conformal full field algebras over V L ⊗V R ,where V L and V R are two vertex operator algebras satisfying certain finiteness and reductivity conditions.We also study the geometry interpretation of conformal full field algebras over V L ⊗V R equipped with a nondegenerate invariant bi-linear form.By assuming slightly stronger conditions on V L and V R ,we show that a conformal full field algebra over V L ⊗V R equipped with a non-degenerate invariant bilinear form exactly corresponds to a commutative Frobenius algebra with a trivial twist in the category of V L ⊗V R -modules.The so-called diagonal constructions [HK2]of conformal full field algebras are given in tensor-categorical language.0Introduction In [HK2],Huang and the author introduced the notion of conformal full field algebra and some variants of this notion.We also studied their basic properties andgave constructions.We explained briefly without giving details in the introduction of [HK2]that our goal is to construct conformal field theories [BPZ][MS].It is one of the purpose of this work to explain the connection between conformal full field algebras and genus-zero conformal field theories.[HK2]and this work are actually a part of Huang’s program ([H1]-[H13])of constructing rigorously conformal field theories in the sense of Kontsevich and Segal [S1][S2].Around 1986,I.Frenkel initiated a program of using vertex operator algebras to construct,in a suitable sense,geometric conformal field theories,the precise mathematical definition of which was actually given independently by Kontsevich1and Segal[S1][S2]in1987.According to Kontsevich and Segal,a conformalfield theory is a projective tensor functor from a category consisting offinite many ordered copies of S1as objects and the equivalent classes of Riemann surfaces with parametrized boundaries as morphisms to the category of Hilbert spaces.This beautiful and compact definition of conformalfield theory encloses enormously rich structures of conformalfield theory.In order to construct such theories,it is more fruitful to look at some substructures of conformalfield theories atfirst.In the first category,the set of morphisms which have arbitrary number of copies of S1in their domains and only one copy of S1in their codomain has a structure of operad [Ma],which is induced by gluing surfaces along their parametrized boundaries.We denoted this operad as K H.Let H,a Hilbert space,be the image object of S1. The projective tensor functor in the definition of conformalfield theory endows H with a structure of algebra over an operad,which is a C-extension of the operad K H[H3].It is very difficult to study this algebra-over-operad structure on H directly.It was suggested by Huang[H12][H13]that one shouldfirst look at a dense subset of H,which carries a structure of an algebra over a partial operad˜K c⊗2-power of the determine line bundle over thepartial operad K.The restriction of the line bundle˜K c on K H,denoted as˜K c H, is also a suboperad.˜K c⊗˜Kproducing modular invariant genus-one correlation functions when c L=c R.Weshow in Section1that the grading-restricted R×R-graded fullfield algebras are exactly smooth algebras over K,which is partial suboperad of K,and confor-mal fullfield algebra over V L⊗V R are exactly smooth algebras over˜K c L⊗c R.The modular invariance property of conformal fullfield algebras will be studied in [HK3].In order to cover the entire genus-zero conformalfield theories,one still needsto consider the Riemann surfaces with more than one copy of S1in the codomain. In chiral theory,it was studied by Hubbard in the framework of so-called vertex operator coalgebras[Hub1][Hub2].In a theory including both chiral and antichiral parts,it amounts to have a conformal fullfield algebra equipped with a nondegen-erate invariant bilinear form[HK2].Conversely,a conformal fullfield algebra with a nondegenerate invariant bilinear form gives a complete set of data needed for a genus-zero conformalfield theory(nonunitary).In particular,we show in Section 2that such conformal fullfield algebras are just algebraic representations of the sewing operations among spheres with arbitary number of negatively oriented and positively oriented punctures as long as the resulting surfaces after sewing are still of genus-zero.The invariant property of bilinear form used in this work is slightly different from that in[HK2].Both definitions have clear geometric meanings.But we need the new definition for a reason which is explained later.Although the notion of conformal fullfield algebras has the advantage of being a pure algebraic formulation of a part of genus-zero conformalfield theories,its axioms are still very hard to check directly.The theory of the tensor products of the modules of vertex operator algebras is developed by Huang and Lepowsky [HL1]-[HL4][H2][H7].The following Theorem proved by Huang in[H7]is very crucial for our constructions of conformal fullfield algebras.Theorem0.1.Let V be a vertex operator algebra satisfying the following condi-tions:1.Every C-graded generalized V-module is a direct sum of C-graded irreducibleV-modules,2.There are onlyfinitely many inequivalent C-graded irreducible V-modules,3.Every R-graded irreducible V-module satisfies the C1-cofiniteness condition. Then the direct sum of all(in-equivalent)irreducible V-modules has a natural structure of intertwining operator algebra and the category of V-modules,denoted as C V has a natural structure of vertex tensor category.In particular,C V has natural structure of braided tensor category.3Assumption0.2.All the vertex operator algebras appeared in this work,V,V L and V R are all assumed to satisfy the conditions in Theorem0.1without further announcement.Sometimes we even assume stronger conditions on them,as we will do explicitly in Section4and Section5.In[HK2],we have studied in detail the properties of conformal fullfield algebras over V L⊗V R.In particular,an equivalent definition of conformal fullfield algebra over V L⊗V R is also given.We recalled this result in Theorem3.2.The axiom in this definition are much easier to verify than those in the original definition of conformal fullfield algebra.Also by Theorem0.1,the categories of V L-modules, V R-modules and V L⊗V R-modules,denoted as C V L,C V L and C V L⊗V R respectively, all have the structures of braided tensor category[H7][HK2].In this work,the braiding structure in C V L⊗V R is chosen to be different from the one obtained from ing Theorem3.2and this new braiding structure on C V L⊗V R,we can show,without much effort,that a conformal fullfield algebra over V L⊗V R is equivalent to a commutative associative algebra in C V L⊗V R with a trivial twist.We would also like to give a categorical formulation of conformal fullfield algebra over V L⊗V R equipped with a nondegenerate invariant bilinear form, where V L and V R are assumed to satisfy the conditions in Theorem4.5,which are slightly stronger than those in Theorem0.1.It turns out that the way we define the invariant property of bilinear form of conformal fullfield algebra in[HK2]is not easy to work with categorically.This is the reason why a slightly modified notion of invariant bilinear form is introduced in Section2.This modification leads us to consider on the graded dual space of a module over a vertex operator algebra a module structure which is different from(but equivalent to)the usual contragredient module structure[FHL].Because of this,we redefine the duality maps[H9][H11]in this new convention and prove the rigidity(in appendix).Then we show in detail,in Section4,that a conformal fullfield algebra over V L⊗V R equipped with a nondegenerate invariant bilinear form in the new sense exactly amounts to a commutative Frobenius algebra with a trivial twist in C V L⊗V R.Once the categorical formulation is known.We can give a categorical con-struction of conformal fullfield algebras equipped with a nondegenerate invariant bilinear form.This construction was previously given by Huang and the author in [HK2]by using intertwining operator algebras,and was also known to physicists as diagonal construction(see for example[FFFS]and references therein).Recently,Fuchs,Runkel,Schweigert and Fjelstad have proposed a very gen-eral construction of all correlation functions of boundary conformal conformalfield theories using3-dimensional topologicalfield theories in a series of papers[FRS1]-[FRS4][FjFRS][RFFS][SFR].In particular,a construction of commutative asso-ciative algebras in C V⊗V is explicitly given in[RFFS].Our approach is somewhat4complementary to their approach(see[RFFS]for comments on the relation of two approachs).We hope that two approachs can be combined to obtain a rather complete picture of conformalfield theory in the near future.The layout of this paper is as follow.In Section1,we study the operadic formulation of grading-restricted R×R-graded fullfield algebra and its variants, following the work of Huang[H3].In Section2,we give a the geometric description of a conformal fullfield algebra over V L⊗V R equipped with a nondegenerate invariant bilinear form.In Section3,we give a categorical formulation of conformal fullfield algebra over V L⊗V R.In Section4,we give a categorical formulation of conformal fullfield algebra over V L⊗V R with a nondegenerate invariant bilinear form for V L and V R satisfying the conditions in Theorem4.5.In Section5,we give a categorical construction of conformal fullfield algebras over V L⊗V R and prove that such obtained conformal fullfield algebras over V L⊗V R are naturally equipped with a nondegenerate invariant bilinear form.For the convenience of readers,the materials in Section3,4,5are completely independent of those in Section1,2.For those who is only interested in categorical formulation of conformal fullfield algebras over V L⊗V R,it is harmless to start from Section3directly.Convention of notations:N,R,R+,C,H,ˆC,ˆH denote the set of natural num-bers,real numbers,positive real numbers and complex numbers,and upper half plane,one point compactification of C and H∪R,respectively.We also use I F to denote the identity map on a vector space F.Note.After this paper appeared online in math arxiv,the author noticed that the categorical construction of commutative associative algebra in C V⊗V given in this work is nothing but a basis independent version of that in[FrFRS]which appeared earlier.There is another natural point of view of this construction in terms of adjoint functors.It will be discussed elsewhere.Acknowledgment This work grows from a chapter in author’s thesis.I want to thank my advisor Yi-Zhi Huang for his constant support and many important suggestions.I also want to thank him for spending incredible amount of time in helping me to improve the writting of my thesis and this work.I thank J.Lepowsky and C.Schweigert for many inspiring conversations related to this work.1Operadic formulations of fullfield alegbrasIn this section,we study the operadic formulation of fullfield algebra.In section 1.1,we recall the notion of sphere partial operad K and its partial suboperad K. We introduce the notion of smooth function on K.In section1.2,we recall the5notions of determinant line bundle over K and the C-extensions of K,such as˜K c and˜K c L⊗c R for c,c L,c R∈C.Section1.1and1.2are mainly taken from[H3].The readers who is interested in knowing more on this subject should consult with [H3]for details.In section1.3,we recall the notion of algebra over partial operad [H3],and explain what it means for an algebra over K and˜K c L⊗c R to be smooth. Then we give two isomorphism theorems.Thefirst one says that the category ofgrading-restricted R×R-graded fullfield algebras is isomorphic to the category of smooth K-algebras.The second one says that the category of conformal fullfield algebras over V L⊗V R is isomorphic to the category of smooth˜K c L⊗c R-algebras over V L⊗V R.We give a selfcontent proof of thefirst isomorphism theorem.The proof of the second isomorphism theorem is technical,and heavily depends on the results in[H3].1.1Sphere partial operad KA sphere with tubes of type(n−,n+)is a sphere S with n−ordered punctures p i,i=1,...,n−and n+ordered punctures q j,j=1,...,n+,together with a negatively oriented local chart(U i,ϕi)around each p i and a positively oriented local chart(V j,ψj)around each q i,where U i and V j are neighborhood of p i and q j respectively and the local coordinate mapsϕi:U i→C andψj:V j→C are conformal maps so thatϕ(p i)=ψj(q j)=0.The conformal equivalence of sphere with tubes is defined to be the conformal maps between two spheres so that the germs of local coordinate mapϕi andψj are preserved.We then obtain a moduli space of sphere with tubes of type(n−,n+). In this section,We are only interested in spheres with tubes of type(1,n).For this type of spheres with tubes,we label the only negative oriented puncture as the0-th puncture.We denote the moduli space of sphere with tubes of type(1,n) as K(n).Using automorphisms of sphere,we can select a canonical representative from each conformal equivalence class in K(n)for all n>0byfixing the n-th puncture at0∈C,the0-th puncture at∞,andψ0,the local coordinate map at∞,to be so thatwψ0(w)=−1.(1.1)limw→∞As a consequence,the moduli space K(n),n∈Z+can be identified withK(n)=M n−1×H×(C××H)nwhereM n−1={(z1,...,z n−1)|z i∈C×,z i=z j,for i=j}6andH={A=(A1,A2,...)∈∞i=1C|A i∈C,e ∞j=1A j x j+1ddx x x=1dw w,∀i=1,...,n.(1.4)Let P∈K(m)and Q∈K(n).Let¯B r be the closed ball in C centered at0 with radius r,ϕi the germs of local coordinate map at i-th puncture p i of P,and ψ0the germs of local coordinate map at0-th puncture q0of Q.Then we say that the i-th tube of P can be sewn with0-th tube of Q if there is a r∈R+such that p i and q0are the only punctures inϕ−1i(¯B r)andψ−10(¯B1/r)respectively.A new sphere with tubes in K(m+n−1),denoted as P i∞0Q,can be obtained by cutting outϕ−1i(¯B r)andψ−10(¯B1/r)from P and Q respectively,and then identifying the boundary circle via the mapψ−1◦JˆH◦ϕiwhere JˆH:w→−1wis an automorphism of upper hand plane.7Therefore,we have sewing operations:i∞0:K(m)×K(n)→K(m+n−1)partially defined on the entire K between two spheres with tubes along two oppo-sitely oriented tubes.Remark1.2.Our definition of sewing operation is defined differently from that:w→1defined in[H3],where JˆCof K (1)together with the sewing operation 1∞0is a group isomorphic to C ×.There is also an obvious action of permutation group S n on K (n ).The following result is proved in [H3].Proposition 1.5.The collection of setsK ={K (n )}n ∈Ntogether with I K ,sewing operations,the actions of S n on K (n )and the group (1.5),is a C ×-rescalable partial operad.Let A (a ;i )={A j |A i =a,A j =0,j ∈Z +,j =i }.For simplicity,we will also use A (a ;i )to denote the element in K (0)such that the local coordinate map at ∞is given by −exp a 1d 1w=−exp −aw −i +1d w .Let K(n )be the subset of K (n )consisting of elements of the form (z 1,...,z n −1;A (a ;1),(a (1)0,0),...,(a (n )0,0)).(1.6)Then K={ K (n )}n ∈N is a partial suboperad of K [H3].We use “overline”to denote complex conjugation.A function f on K (n ),n ∈N is called smooth if there is a N ∈N such that f can be written asN k =1g k (A (0),a (1)0,A (1),...,a (n )0,A (n );a (1)0,a (n )0,A (i )j ,for i =0,...,n,j ∈Z +and linear combination of n i =1(a (i )0)r i ∂ǫ ǫ=0f (P (z )1∞0A (ǫ;2)),¯L I (¯z )f :=∂Proposition 1.6.L I (z )=z −2∂∂A (i )j I ,¯L I (¯z )=¯z −2∂a (1) I +1 i =0∞ j =1¯z −(2i −1)j −2∂A (i )j I .(1.9)Proof.Let P =P (z )1∞0A (ǫ,2)with its coordinates in moduli space given by (z ;A (0),(a (1)0,A (1)),(a (2)0,A (2))).It is shown in [H3]thatz ,A (0)j ,a (1)0,A (1)j ,a (2)0and A (2)j ,j ∈Z +are holomorphic functions of ǫ.Hence their complex conjugation ¯z ,a (1)0,a (2)0and1.2Determinant line bundle over KThe determinant line bundle over K and the C -extensions of K are studied in[H3].For each n ∈N ,the determinant line bundle Det(n )over K (n )is a trivial bundle over K (n ).We denote the fiber at Q ∈K (n )as Det Q .There is a canonical section of Det(n ),denoted by ψn ,for each n ∈N .For any element Q ∈K (n ),let µn (Q )be the element of the fiber over Q given byψn (Q )=(Q,µn (Q )).Then there is a λQ for each element ˜Qof Det Q such that ˜Q =(Q,λQ )and λQ =αµn (Q )for some α∈C .Consider the following two general elements in K (m )and K (n ).P =(z 1,...,z m ;A (0),(a (1)0,A (1)),...,(a (m )0,A (m )))Q =(ξ1,...,ξn ;B (0),(b (1)0,B (1)),...,(b (n )0,B (n )))(1.10)If P i ∞0Q exists,then there is a canonical isomorphism:l i P,Q :Det P ⊗Det Q →Det P i ∞0Q ,given as:l i P,Q(a 1µm (P )⊗a 2µn (Q ))=a 1a 2e 2Γ(A (i ),B (0),a (i )0)µm +n −1(P i ∞0Q ),(1.11)10whereΓis a C-valued analytic function of complex variables A(i)j,B(0)k ,a(i)0,j,k∈N.If we expandΓas formal series,we haveΓ(A(i),B(0),α)∈Q[α,α−1][[A(i),B(0)]].For a detailed discussion ofΓ,see chapter4in[H3].In particular,we haveA(i),a(i)0).(1.12) For(P,λP)∈Det(m)and(Q,λQ)∈Det(n)such that P i∞0Q exists,then we define a partially defined mapi ∞20:Det(m)×Det(n)→Det(m+n−1)by(P,λP)i ∞20(Q,λQ)=(P i∞0Q,l i P,Q(λP⊗λQ)).Using this partial operation,one obtain a C×-rescalable partial operad structure on Det={Det(n)}n∈N.For c∈C,the so-called vertex partial operad of central charge c,denoted as ˜K c,is the c˜K¯c of holomorphic line bundle˜K¯c also has a natural structure of partial operad.The section ofψon˜K¯c canonically gives a section¯ψonDet¯c P⊗Det¯c Pi∞0Q,for any pair of P,Q∈K so that P i∞0Q exists,can be written as¯l iP,Q(λ1⊗λ2)=λ1λ2eΓ(B(0),˜K¯c=In this work,we are also interested in the tensor product bundle˜K c L⊗c R for c L,c R∈C.It is clear that it is a C×-rescalable partial operad as well.The natural section induced from˜K c L and c R is simplyψ⊗¯ψ.We will denote the sewing operation on˜K c L⊗c R simply as ∞without making its dependents on c L,c R explicit.A function on˜K c or˜K c L⊗c R is called smooth if it is smooth on the base space K and linear onfiber.1.3Two isomorphism theoremsIn this subsection we discuss the operadic formulations of grading-restricted R×R-graded fullfield algebras and conformal fullfield algebras over V.We apologize for not recalling the definitions of these two notions here.They can be found in [HK2].Wefirst recall the definition of algebra over partial operad.Let G be a group and U a complete reducible G-module and W a G-submodule of U.We will useU such that image of W⊗n is in1Here,νn for n∈N is simply the restriction ofνon P(n).12If P is rescalable[H3],we call a P-pseudo-algebra a P-algebra.In this work,we are interested in studying K-algebras and˜K c L⊗c R-algebras, both of which are C×-rescalable partial operads.Definition1.8.A K-algebra(or˜K c L⊗c R-algebra)(F,W,ν)is called smooth if it satisfies the following conditions:1.F(m,n)=0if the real part of m or n is sufficiently small.2.For any n∈N,w′∈F′,w1,...,w n+1∈F,an element Q in K(n)(or˜K c L⊗c R(n)),the functionQ→ w′,ν(Q)(w1⊗···⊗w n+1)is smooth on K(n)(or on˜K c L⊗c R(n)).We choose the branch cut of logarithm as followlog z=log|z|+Arg z,0≤Arg z<2π.(1.15) We define the power functions,z m and¯z n for m,n∈R,to be e m log z and e nbe so that ˜ρ(0)=0.Therefore k =0.˜ρis actually a linear map from C →C .Namely,˜ρcan be written as˜ρ: x y→ a b c d x y (1.17)where x,y ∈R are the real part and the imaginary part of a complex number inC .Moreover,the group homomorphism preserves the identity,i.e.ρ:1→1.It implies that ˜ρ(2πi )=l 2πi for some l ∈Z .Applying this result to (1.17),we obtain that b =0and d =l ∈Z .Conversely,it is easy to see that every ˜ρof form (1.17)with b =0and d ∈Z gives arise to a group homomorphism ρ:C ×→C ×of the following form:z =e x +iy →e ax +i (cx +dy )=e (a +ic )x e diy =|z |a +ic z 2−d 2+d Now we study the basic properties of a smooth K -algebras.We fix a smooth K -algebras (F,W,ν).The set I :={(m,n )∈C ×C |m −n ∈Z }together with the usual addition operation gives an abelian group.By Lemma 1.9any K -algebras must be I ly,F = (m,n )∈I F (m,n ).Since ν1((0,(a,0)))for a ∈C ×gives the representation of C ×on F by the definition of algebra over operad,we must have ν1((0,a ))u =a −m ¯a −n u for u ∈F (m,n ).Let d L and d R be the grading operators such that d L u =mu and d R u =nu for u ∈F (m,n ).We call m the left weight of u ∈F (m,n )and n the right weight of u ,and denote them as wt L u and wt R u respectively.We also define wt u :=wt L u +wt R u which is called total weight.These two grading operators can also be obtained from ν1((0,(a,0)))as follow:d L =∂∂¯a a =1ν1((0,(a,0))).(1.19)Conversely,using d L and d R ,we can also express the action of ν1((0,(a,0)))on F as ν1((0,(a,0)))=a −d L ¯a −d R .(1.20)14By the definition of smooth function on K,the correlation functions are linear combination of i(a(i)0)r ily,1:=ν0((0)).(1.21) We call1the vacuum state.We have(0,(a,0))1∞0(0)=(0)for all a∈C×.This implies1∈F(0,0).Since K(0)={(0)},W is just C1.Let P(z)=(z;0,(1,0),(1,0))∈ K(2).We denote the linear mapν2(P(z)):F⊗F→Proof.First,for u,v∈F,we haveν2((z;0,(a1,0),(a2,0))(u⊗v)=ν2((P(z)1∞0(0,(a1,0)))2∞0(0,(a2,0)))(u⊗v)=(ν2(P(z))1∗0ν1((0,(a1,0))))2∗0ν1((0,(a2,0)))(u⊗v)=Y(a−d L1¯a−d R1u;z,¯z)a−d L2¯a−d R2v.(1.25)On the other hand,we also have(0,(a−1,0))1∞0P(z)=(az;0,(a−1,0),(a−1,0)).(1.26) Using(1.25),the image of(1.26)under the morphismνgivesa d L¯a d R Y(u;z,¯z)=Y(a d L¯a d R u;az,¯a¯z)a d L¯a d R,which implies(1.24).∂z Y(u;z,¯z)+Y(d L u;z,¯z)(1.27)d R,Y(u;z,¯z) =¯z∂∂s|s=0and∂We further define two operators D L,D R∈Hom(F,∂a a=0ν1((A(a;1),(1,0)),D R:=−∂It implies the following identity:w′,(ν1((A(a;1),(1,0)))1∗0ν1((0,(a1,0)))1∗0(ν1((A(b;1),(1,0)))1∗0ν1((0,(b1,0)))(w)= w′,ν1((A(a+b/a1;1),(1,0)))1∗0ν1((0,(a1b1,0)))(w) (1.30) for all w∈F,w′∈F′.Apply−∂∂b b=0,a=0,b1=1− −∂∂b1 b=0,a1=1,b1=1to both sides of equation(1.30).The left hand side of(1.30)gives(m,n)∈I w′,(d L P(m,n)D L−D L d L)w ,while the right hand of(1.30)gives−∂∂b b=0 w′,ν1((A(b/a1;1),(1,0)))a−d L1¯a−d R1w− −∂∂b1 b1=1 w′,ν1((A(a;1),(1,0)))b−d L1¯b−d R1w= −∂a1=1 −∂∂a a=0 −∂∂¯a1a1=1 w′,D L1∂a1Compare above two equations.It is clear that[d R,D L]=0.Combining above two results,we conclude that D L∈End V and has weight (1,0).Similarly,we can show[d L,D R]=0and[d R,D R]=D R.Therefore,D R is in End V as well and has weight(0,1).Next we show that[D L,D R]=0.The identity(A(a+b;1),(1,0))=(A(a;1),(1,0))1∞0(A(b;1),(1,0))=(A(b;1),(1,0))1∞0(A(a;1),(1,0))(1.32) in K implies that for w′,w∈F,w′,ν1((A(a;1),(1,0)))1∗0ν1((A(b;1),(1,0)))w= w′,ν1((A(b;1),(1,0)))1∗0ν1((A(a;1),(1,0)))w .(1.33) Apply −∂∂¯bb=0to both sides of(1.33).We obtain[D L,D R]=0.∂z Y(u;z,¯z),(1.34)D R,Y(u;z,¯z) =Y(D R u;z,¯z)=∂∂z z=0ν2(P(a)1∞0(A(−z;1),(1,0))),(1.37)and∂∂z z=0ν2(P(z+a)).(1.38) Hence it is clear thatY(D L u,z,¯z)=∂Similarly,we can show that the D L-bracket property follows from the following sewing identity:(A(−z;1),(1,0))1∞0(P(a)2∞0(A(z;1),(1,0)))=P(z+a).We omit the detail.The proof of D R-bracket and D R-derivative properties is similar.For the convergence property of R×R-graded fullfield algebra,we use the weaker version of convergence property discussed in the remark1.2in[HK2].Then it is clear that this weaker version of convergence property is automatically true by the definition of algebra over partial operad.The permutation axiom of full field algebra follows automatically from that of partial operad.The single-valuedness property follows from Lemma1.9.The rest of axioms follows from(1.24),(1.27),(1.28),(1.34)and(1.35).z1+a,...,z n+a,z1+a,...,z n+a,Theorem1.17.The category of grading-restricted R×R-graded fullfield algebras is isomorphic to the category of smooth K-algebras.Proof.The proof is similar to that of Theorem5.4.5in[H3].Our case is much simpler.Given a grading-restricted R×R-graded fullfield algebra(F,m,1,d L,d R,D L,D R).20We define a mapνfrom K to H C×F C1as follow.We defineν0((0)):=1.(1.48) For n>0,u i∈F,a,z i∈C,i=1,...,n and Q∈ K(n)as(1.6),we define ν(Q)(u1⊗···⊗u n):=e−aD L−¯a D R m n((a(1)0)−d L(a(n)0)−d R u n;z1,z n−1,0,0).(1.49) In particular,ν1((0,(a,0))=m1((a(1)0)−d L(a(1)0)−d R u1.(1.50) This gives the representation of rescaling group C×according to the R×R-grading of F.The R×R-grading,together with the single-valuedness property,guarantees that the grading is in the set{(m,n)|m,n∈R,m−n∈Z}as required by the ax-ioms of smooth K-algebra.The grading restriction conditions and the smoothness of all correlation functions are all automatically satisfied.Let P∈ K(m)and Q∈ K(n)given as follow:P=(z1,...,z m−1;A(a;1),(a(1)0,0),...,(a(m),0))Q=(ξ1,...,ξn−1;A(b;1),(b(1)0,0),...,(b(n)0,0)).(1.51) We assume that P i∞0Q exists.Then we haveP i∞0Q=(z1,...,z i−1,ξ1−aa(i)0+z i,z i+1,...,z n;A(a;1),(a(1)0,0),...,(a(i−1)0,0),(a(i)0b(1)0,0),...,(a(i)0b(m),0),(a(i−1),0),...,(a(n)0,0)).(1.52) 21By(1.46),we haveνm(P)i∗0νn(Q)= k,l∈R e−aD L−¯a D R m m((a(1)0)−d L(a(i)0)−d R P k,l m n((b(1)0)−d L(b(n)0)−d R v n;ξ1−b,ξm−b),...,(a(m))−d L(a(1)0)−d R u1,...,P k,l m n((a(i)0b(1)0)−d L(a(i)0b(n)0)−d R v n;(ξ1−b)/a(i)0,(ξm−b)/a(i)0),...,(a(m))−d L(a(1)0)−d R u1,...,(a(i)0b(1)0)−d L(b(n)0)−d R v n,...,(a(m))−d L(a(i)0+z i,a(i)0+z i,...,ξm−bξm−bBy construction(1.41)and(1.42),for z i=0,i=1,...,n,we have˜m n(u1,...u n;z1,¯z1,...,z n,¯z n)=νn+1((z1,...,z n;0,(1,0),...,(1,0)))(u1⊗u n⊗1)=m n+1(u1,...,u n,1;z1,¯z1,...,z n,¯z n,0,0)=m n(u1,...,u n;z1,¯z1,...,z n,¯z n).(1.53) The cases when z i=0for some i=1,...,n follows from smoothness.Therefore ˜m=m.By1.29,we also have˜D L=−∂∂a a=0e−aD L−¯a D R=D L,˜D R=−∂∂a a=0e−aD L−¯a D R=D R.(1.54) The coincidence of two gradings is also obvious.Therefore,we have proved that one way of composing two functors gives the identity functor on the category of grading restricted R×R-graded fullfield algebra.Similarly,one can show that the opposite way of composing these two functors also gives the identity functor on the category of smooth K-algebras.˜K˜K˜K˜Kto denote this function.For the simplicity of notation,we will not distinguish L L(n)with L L(n)⊗1 and L R(n)with1⊗L R(n)in this work.Proposition1.18.A conformal fullfield algebra over V L⊗V R,(F,m,ρ),has a canonical structure of smooth˜K c L⊗c R-algebras over V L⊗V R.Proof.Wefirst define a mapνn:˜K c L⊗c R(n)→Hom(F⊗n,˜K˜KA(0))mn (e−L L+(A(1))−L R+(a(1)0−L R(0)u1,...,e−L L+(A(n))−L R+(a(1)0−L R(0)u n;z1,¯z1,...,z n−1,¯z n−1,z n,¯z n),(1.57)whereL L±(A)=∞j=1A j L L(±j),L R±(A)=∞ j=1A j L R(±j)for A∈ n∈N C.24。

双内圈角接触球轴承轴向和径向游隙的选配_钟华

双内圈角接触球轴承轴向和径向游隙的选配_钟华

1前言双内圈内、外沟道都带锁口的角接触球轴承,因合套后不可随便拆套,要求组装前必须选配好套圈,计算好游隙,使配套的成品零件一次组装成合格的产品。

双内圈角接触球轴承成品既要求径向游隙又要求轴向游隙,比通常的角接触球轴承控制项目多。

如某试制产品,该产品是双内圈大接触角的角接触球轴承,其球与沟道的公称接触角40°,要求配套径向游隙0.415~0.465mm 、轴向游隙0.08~0.16mm ,需计算和测量多项尺寸相匹配才能保证成品要求。

我们是用下列方法进行计算和选配达到成品要求的。

2游隙计算与选择2.1径向游隙J 的计算与选择2.1.1径向游隙J 与接触角β的关系角接触球轴承选配径向游隙的目的是为了保证成品接触角β(图1中β=40°),径向游隙J 与β的关系式如下:由cos β=1-J /2(R e +R i -d W ),推导出β=cos -1[1-J /2(R e +R i -d W )](1)式中:R e —外圈沟曲率半径,R i —内圈沟曲率半径,d W —钢球直径。

图1内外圈钢球组装图以某球轴承为例:设R e =11.668~11.724mm ,R i =11.446~11.502mm ,d W =7/8″,双内圈角接触球轴承轴向和径向游隙的选配钟华1,崔任贤2(1.哈尔滨轴承集团公司专用产品制造公司,黑龙江哈尔滨150036;2.哈尔滨轴承集团公司技工学校,黑龙江哈尔滨150036)摘要:双内圈大接触角双列角接触球轴承,合套后不可随便拆套。

介绍组装前如何选配套圈,计算游隙和修磨内圈小端面,使配套的成品零件一次组装成合格的产品。

关键词:轴向游隙;径向游隙;游隙计算;修磨量中图分类号:TH133.33;TH161+7文献标识码:B文章编号:1672-4852(2009)01-0028-02Selection and fit of compound clearance of angular contactball bearing with double inner ringsZhong Hua 1,Cui Renxian 2(1.Special Product Division,Harbin Bearing Group Corporation,Harbin 150036,China;2.Vestibule School,Harbin Bearing Group Corporation,Harbin 150036,China)Abstract:The double row angular contact ball beaings with double inner rings and relatively larger contact angles,after assemblage,cannot be disassembled unless necessary.This thesis introduces the selection and fit of rings,the calculation of clearance,and the grinding of the lesser end surface of inner rings,all this done prior to assemblage,to each time assure the qualified assemblage of the components of the bearings.Key words:axial clearance;radial clearance;the calculation of clearance;value of grinding收稿日期:作者简介:2008-04-07.钟华(1971-),女,助理工程师.哈尔滨轴承Vol.30No.1M ar.2009第30卷第1期2009年3月JOURNAL OF HARBIN BEARING则相应的(R e+R i-d W)=0.889~1.001mm。

双精浮点运算

双精浮点运算

双精浮点运算Double-Precision Floating-Point ArithmeticDouble-precision floating-point arithmetic refers to the representation and manipulation of numbers using a double-precision floating-point format. This format provides a higher level of precision and range compared to single-precision floating-point numbers.In double-precision floating-point representation, a number is typically divided into three parts: the sign, the exponent, and the mantissa. The sign indicates whether the number is positive or negative. The exponent represents the scale or magnitude of the number, while the mantissa provides the detailed fractional part of the number.Double-precision floating-point arithmetic is widely used in scientific computing, engineering applications, and other fields that require high precision and accuracy. It allows for more accurate calculations and reduced rounding errors compared to single-precision floating-point arithmetic.双精浮点运算双精浮点运算是指使用双精浮点格式来表示和操纵数字的过程。

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a rXiv:q -alg/96514v511J u l1996June (1996),1–36Dedicated to Yuri I.Manin on the occasion of his 60birthdayIntertwining operatorsof double affine Hecke algebras By Ivan Cherednik*Continuing [C3,C4],we study the intertwining operators of double affine Hecke algebras H .They appeared in several papers (especially in [C2,C4,C6]).However for the first time here we apply them systematically to create the non-symmetric [M3,C4]and symmetric [M2]Macdonald polynomials for arbitrary root systems and to start the theory of induced and co-spherical H -modules.The importance of this technique was clearly demonstrated in recent pa-pers by F.Knop and S.Sahi [Kn],[KS],[S].Using the intertwiners of the double affine Hecke algebras in the case of GL (dual to those considered in [C1,C2])they proved the q,t -integrality conjecture by I.Macdonald [M1]and managed to establish the positivity of the coefficients of the Macdonald polynomials in the differential case.As to the integrality,we mention another approach based on the so-called Vinet operators (see [LV]and a recent work by Kirillov,Noumi),and the results by Garsia,Remmel,and Tesler.We do not try in this paper to get the best possible estimates for the denominators of the Macdonald polynomials (generally speaking,the problem looks more complicated than in the stable GL -case).However even rather straightforward analysis of the intertwiners gives a lot.For instance,it is enough to ensure the existence of the restricted Macdonald polynomials at roots of unity from [C3,C4],where we used less convenient methods based directly on the definition or on the recurrence relations.The technique of intertwiners combined with the (projective)action of GL (2,Z )from [C3]gives another proof of the norm and the evaluation formulas (see [C4]).Here the H -embedding of the space of nonsymmetricpolynomialsinto the space of functions on the affine Weyl group ˜W ([C4],Proposition 5.2)plays a key role.The latter representation when restricted to the affine Hecke subalgebra turns into the classical one from [IM]as t is a power of p and q →0(˜W is identified with the set of double cosets of the corresponding p -adic group with respect to the Iwahori subroup).2IV AN CHEREDNIKAnother important application is a calculation of the Fourier transforms of the Macdonald polynomials in the sense of[C3,C4].For instance,it gives a canonical identification of the polynomial representation of the affine Hecke algebra with the representation in functions on the weight lattice(which col-lapses in the p-adic limit).We introduce a proper discretization of theµ-function(the truncated theta-function making Macdonald’s polynomials pairwise orthogonal)and the corresponding discrete inner product on Funct(˜W).It readily gives the pro-portionality of the norms of the Macdonald polynomials[M2,C2,M3,C4]and those defined for the Jackson integral taken instead of the constant term in the inner product.The coefficient of proportionality is described by the Aomoto conjecture(see[A,Ito])recently proved by Macdonald(to calculate it one can also follow[C2],replacing the shift operators by their discretizations).We note that the Macdonald polynomials considered as functions on˜W are square integrable forfinitely many weights only.Here|q|=1and the real partℜ(k)for t=q k is to be negative(otherwise we have none).The program is to describe all integrable and non-integrable eigenfunctions of the discrete Dunkl operators in this representation and to study the corresponding Fourier transform.In contrast to the classical p-adic harmonic analysis(see e.g.[HO])the Plancherel measure coincides with the discretization ofµ(the Fourier transform is self-dual).More generally,we consider the action of the double affine Hecke algebra in the same space Funct(˜W)depending on an arbitrary given weight.Its sub-module generated by the delta-functions is induced(from a character of the standard polynomial subalgebra)and co-spherical.Mainly following[C5],we find out when arbitrary induced representations(in the same sense)are irre-ducible and co-spherical using the technique of intertwiners.The answer is a natural”affinization”of the well-known statements in the p-adic case(see e.g.[KL],[C5]).The classification of co-spherical representations is impor-tant for the harmonic analysis and plays the key role in the theory of affine Knizhnik-Zamolodchikov equations(see[C6,C7,C8]).We also induce up irre-ducible representations of affine Hecke subalgebras([C6]is devoted to appli-cations of such representations).If q is sufficiently general the H-modules we get are irreducible,so one can use the classification of[KL].Thus in this paper we begin a systematic study of the representations of double affine Hecke algebras and related harmonic analysis.The polyno-mial representation considered in the series of papers[C2-4]devoted to the Macdonald conjectures is remarkable,but still just an example.The paper was started during my stay at RIMS(Kyoto University),con-tinued at CRM in Montreal,and completed at the University of Nijmegen.I am grateful to T.Miwa,L.Vinet,G.Heckman and my colleagues at theseINTERTWINERS OF DOUBLE HECKE ALGEBRAS3 institutes for the kind invitations and the hospitality.The author thanks E. Frenkel,G.Heckman,D.Kazhdan,I.Macdonald,and E.Opdam for useful discussions.1.Affine Weyl groupsLet R={α}⊂R n be a root system of type A,B,...,F,G with respect to a euclidean form(z,z′)on R n∋z,z′,normalized by the standard condition that(α,α)=2for longα.Let usfix the set R+of positive roots(R−=−R+),the corresponding simple rootsα1,...,αn,and their dual counterparts a1,...,a n,a i=α∨i,whereα∨=2α/(α,α).The dual fundamental weights b1,...,b n are determined from the relations(b i,αj)=δj i for the Kronecker delta.We will also use the dual root system R∨={α∨,α∈R},R∨+,and the latticesA=⊕n i=1Z a i⊂B=⊕n i=1Z b i,A±,B±for Z±={m∈Z,±m≥0}instead of Z.(In the standard notations, A=Q∨,B=P∨-see[B].)Later on,να=να∨=(α,α),νi=ναi,νR={να,α∈R}⊂{2,1,2/3}.(1.1)ρν=(1/2) να=να=(ν/2)νi=νb i,forα∈R+.The vectors˜α=[α,k]∈R n×R⊂R n+1forα∈R,k∈Z form the affine root system R a⊃R(z∈R n are identified with[z,0]).We addα0def=[−θ,1] to the simple roots for the maximal rootθ∈R.The corresponding set R a+of positive roots coincides with R+∪{[α,k],α∈R,k>0}.We denote the Dynkin diagram and its affine completion with{αj,0≤j≤n}as the vertices byΓandΓa(m ij=2,3,4,6ifαi andαj are joined by0,1,2,3laces respectively).The set of the indices of the images ofα0by all the automorphisms ofΓa will be denoted by O(O={0}for E8,F4,G2). Let O∗=r∈O,r=0.The elements b r for r∈O∗are the so-called minuscule weights((b r,α)≤1forα∈R+).Given˜α=[α,k]∈R a,b∈B,lets˜α(˜z)=˜z−(z,α∨)˜α,b′(˜z)=[z,ζ−(z,b)](1.2)for˜z=[z,ζ]∈R n+1.The affine Weyl group W a is generated by all s˜α(simple reflections s j= sαjfor0≤j≤n are enough).It is the semi-direct product W⋉A,where the non-affine Weyl group W is the span of sα,α∈R+.Here and futher we identify b∈B with the corresponding translations.For instance,a=sαs[α,1]=s[−α,1]sαfor a=α∨,α∈R.(1.3)4IV AN CHEREDNIKThe extended Weyl group W b generated by W and B is isomorphic to W⋉B:(wb)([z,ζ])=[w(z),ζ−(z,b)]for w∈W,b∈B.(1.4)Given b+∈B+,letωb+=w0w+0∈W,πb+=b+(ωb+)−1∈W b,ωi=ωbi,πi=πbi,(1.5)where w0(respectively,w+0)is the longest element in W(respectively,in W b+ generated by s i preserving b+)relative to the set of generators{s i}for i>0.The elementsπr def=πbr,r∈O leaveΓa invariant and form a group denoted byΠ,which is isomorphic to B/A by the natural projection{b r→πr}.As to{ωr},they preserve the set{−θ,αi,i>0}.The relationsπr(α0)=αr= (ωr)−1(−θ)distinguish the indices r∈O∗.Moreover(see e.g.[C2]): W b=Π⋉W a,whereπr s iπ−1r=s j ifπr(αi)=αj,0≤j≤n. (1.6)Givenν∈νR,r∈O∗,˜w∈W a,and a reduced decomposition˜w=s jl ...s j2s j1with respect to{s j,0≤j≤n},we call l=l(ˆw)the length ofˆw=πr˜w∈W b.Setting(1.7)λ(ˆw)={˜α1=αj1,˜α2=s j1(αj2),˜α3=s j1s j2(αj3),......,˜αl=˜w−1s jl(αjl)},one can represent(1.8)l=|λ(ˆw)|= νlν,for lν=lν(ˆw)=|λν(ˆw)|,λν(ˆw)={˜αm,ν(˜αm)=ν(˜αjm)=ν},1≤m≤l, where||denotes the number of elements,ν([α,k])def=να.Let us introduce the following affine action of W b on z∈R n:(1.9)(wb) z =w(b+z),w∈W,b∈B,s˜α z =z−((z,α)+k)α∨,˜α=[α,k]∈R a,and the pairing([z,ζ],z′+d)def=(z,z′)+ζ,where we treat d formally(see e.g. [K]).The connection with(1.2,1.3)is as follows:(1.10)(ˆw([z,ζ]),ˆw z′ +d)=([z,ζ],z′+d)forˆw∈W b.Using the affine Weyl chamberC a=nj=0Lαj,L˜α={z∈R n,(z,α)+k>0},INTERTWINERS OF DOUBLE HECKE ALGEBRAS5(1.11)λν(ˆw)={˜α∈R a+, C a ⊂ˆw L˜α ,ν(˜α)=ν} ={˜α∈R a+,lν(ˆws˜α)<lν(ˆw)}.It coincides with(1.8)due to the relations(1.12)λν(ˆwˆu)=λν(ˆu)∪ˆu−1(λν(ˆw)),λν(ˆw−1)=−ˆw(λν(ˆw)) if lν(ˆwˆu)=lν(ˆw)+lν(ˆu).The following proposition is from[C4].Proposition1.1.Given b∈B,the decomposition b=πbωb,ωb∈W can be uniquely determined from the following equivalent conditionsi)l(πb)+l(ωb)=l(b)and l(ωb)is the biggest possible,ii)ωb(b)=b−∈B−and l(ωb)is the smallest possible,iii)πb 0 =b andλ(πb)∩R=∅.We will also use thatλ(b)={˜α,(b,α)>k≥0ifα∈R+,(1.13)(b,α)≥k>0ifα∈R−},λ(πb)={˜α,α∈R−,(b−,α)>k>0if(α,b)<0,(1.14)(b−,α)≥k>0if(α,b)>0},andλ(π−1b)={˜α,−(b,α)>k≥0}for˜α=[α,k]∈R a+.(1.15)Convexity.Let us introduce two orderings on B.Here and further b±are the unique elements from B±which belong to the orbit W(b).Namely, b−=ωbπb=ωb(b),b+=w0(b−)=ω−b(b).So the equality c−=b−(or c+=b+)means that b,c belong to the same orbit.Setb≤c,c≥b for b,c∈B if c−b∈A+,(1.16)b c,c b if b−<c−or b−=c−and b≤c.(1.17)We use<,>,≺,≻respectively if b=c.For instance,c≻b+⇔b+>W(c)>b−,c b−⇔c∈W(b−)or c≻b+.The following sets(1.18)σ(b)def={c∈B,c b},σ∗(b)def={c∈B,c≻b},σ+(b)def={c∈B,c−>b−}=σ∗(b+).are convex.Moreoverσ+is W-invariant.By convex,we mean that if c,d= c+rα∨∈σforα∈R+,r∈Z+,then{c,c+α∨,...,c+(r−1)α∨,d}⊂σ.(1.19)6IV AN CHEREDNIKThe elements fromσ(b)strictly between c and d(i.e.c+qα,0<q<r) belong toσ+(b).πb,where i p are from any se-Proposition 1.2.a)Letˆu=s˜αi m...s˜αi1quence1≤i1<i2<...<i m≤l=l(b)in a reduced decomposition of ˆw=π−1b(see(1.7)).In other words,ˆu is obtained by crossing out any number of{s j}from a reduced decomposition ofπb.Then c def=ˆu 0 ∈σ∗(b).More-over,c∈σ+(b)if and only if at least one of˜αi p=[α,k]for1≤p≤m has k>0.b)If c,b belong to the same W-orbit then the converse is ly, settingωbc def=πbπ−1c,the following relations are equivalent:(i)c≻b(which means that c>b),(ii)(α,c)>0for allα∈λ(ωbc),(iii)l(πb)=l(ωbc)+l(πc),It also results from(i)thatωbc is the smallest possible element w∈W such that b=w(c).Proof.Assertion a)is a variant of Proposition1.2from[C4].For the sake of completeness we will outline the proof of b).Taking u(c)≤b<c,we will check(ii),(iii)by induction supposing that{u′(c)≤b′<c}⇒{(ii),(iii)}for all b′,u′such that l(u′)<l(u),which is obvious when l(u′)=0.Settingβ=u(α)forα∈λ(u),u(sα(c))=u(c)−(α,c)β∨andβ∈R−(see the definition ofλ(α)).One can assume that(α,c)>0for all suchα. Otherwise usα(c)≤u(c)≤c and we can argue by induction.Applying(1.12) and(1.13),we see that l(uc)=l(u)+l(c).Indeed,the intersection ofλ(c)andc−1(λ(u))={[α,(c,α)],α∈λ(u)}is empty.Hence the product uπc is reduced(i.e.l(uπc)=l(u)+l(πc))and λ(uπc)=ωc c−1(λ(u))∪λ(πc)contains no roots from R+.Finally,Proposition 1.1leads to(iii)(and the uniqueness of u of the minimal possible length).This reasoning gives the equivalence of(ii)and(iii)as well.Assertion(i)readily results from(ii).We will also use(cf.Proposition5.2,[C4])the relationsπb=πrπc for b=πr c and any c∈B,r∈O and the equivalence of the following three conditions:(1.20)(αj,c+d)>0⇔αj∈λ(π−1c)⇔{s jπc=πb,c≻b}for0≤j≤n.When j>0it is a particular case of Proposition1.2b). Assuming that(α0,c+d)=1−(θ,c)>0,b=s0 c =c+(α0,c+d)θ>c>c−θ=sθ(b).INTERTWINERS OF DOUBLE HECKE ALGEBRAS7 Hence c∈σ+(b).If the product s0πc is reducible then we can apply statement a)to come to a contradiction.Therefore s0πc=πb,since s0is simple.The remaining implications are obvious.2.Intertwining operatorsWe put m=2for D2k and C2k+1,m=1for C2k,B k,otherwise m=|Π|.Let us sett˜α=tν(˜α),t j=tαj,where˜α∈R a,0≤j≤n,X˜b =ni=1X k i i q k if˜b=[b,k],(2.1)for b=ni=1k i b i∈B,k∈18IV AN CHEREDNIKdoes not depend on the choice of the reduced decomposition(because{T} satisfy the same“braid”relations as{s}do).Moreover,Tˆv Tˆw=Tˆvˆw whenever l(ˆvˆw)=l(ˆv)+l(ˆw)forˆv,ˆw∈W b.(2.3)In particular,we arrive at the pairwise commutative elementsY b=ni=1Y k i i if b=ni=1k i b i∈B,where Y i def=T bi,(2.4)satisfying the relations(2.5)T−1iY b T−1i=Y b Y−1a iif(b,αi)=1,T i Y b=Y b T i if(b,αi)=0,1≤i≤n.The following maps can be extended to involutions of H(see[C1,C3]):ε:X i→Y i,Y i→X i,T i→T−1i ,(2.6)tν→t−1ν,q→q−1,τ:X b→X b,Y r→X r Y r q−(b r,b r)/2,Yθ→X−10T−20Yθ,(2.7)T i→T i,tν→tν,q→q,1≤i≤n,r∈O∗,X0=qX−1θ.Let us give some explicit formulas:(2.8)ε(T0)=XθT−1Yθ=XθT sθ,ε(πr)=X r Tω−1r,τ(T0)=X−10T−1,τ(πr)=q−(b r,b r)/2X rπr=q(b r,b r)/2πr X−1r∗,πr X r∗π−1r=q(b r,b r)X−1r,X r∗TωrX r=T−1ωr∗.Theorem2.3from[C3]says that the map(2.9) 0−1−10 →ε, 1101→τcan be extended to a homomorphism of GL2(Z)up to conjugations by the central elements from the group generated by T1,...,T n.The involutionη=τ−1ετcorresponding to the matrix −1011 will play an important role in the paper:η:X r→q(b r,b r)/2X−1r Y r=πr X r∗Tωr ,(2.10)Y r→q(b r,b r)/2X−1r Y r X r=πr T−1ωr∗,Yθ→T−10T−1sθ,T j→T−1j(0≤j≤n),πr→πr(r∈O∗),tν→t−1ν,q→q−1.INTERTWINERS OF DOUBLE HECKE ALGEBRAS9 We note thatεandηcommute with the main anti-involution∗from[C2]:(2.11)X∗i=X−1i,Y∗i=Y−1i,T∗i=T−1i,tν→t−1ν,q→q−1,0≤i≤n,(AB)∗=B∗A∗.The X-intertwiners(see e.g.[C2,C5,C6])are introduced as follows:Φj=T j+(t1/2j −t−1/2j)(X aj−1)−1,G j=Φj(φj)−1,˜G j=(φj)−1Φj,(2.12)φj=t1/2j +(t1/2j−t−1/2j)(X aj−1)−1,for0≤j≤n.They belong to the extension of H by thefield C q,t(X)of rational functions in{X}.The elements G j and G′j satisfy the same relations as{s j,πr}do,{Φj}satisfy the relations for{T j}(i.e.the homogeneous Coxeter relations and those withπr).Hence the elements(2.13)Gˆw=πr G jl ···G j1,whereˆw=πr s jl···s j1∈W b,are well-defined and G is a homomorphism of W b.The same holds for˜G.AstoΦ,the decomposition ofˆw should be reduced.The simplest way to see this is to use the following property of{Φ}which fixes them uniquely up to left or right multiplications by functions of X:Φˆw X b=Xˆw(b)Φˆw,ˆw∈W b.(2.14)Onefirst checks(2.14)for s j andπr,then observes thatΦfrom(2.13)satisfy (2.14)for any choice of the reduced decomposition,and uses the normalizing conditions to see that they are uniquely determined from the intertwining relations(2.14).We note thatΦj,φj are self-adjoint with respect to the anti-involution (2.11).HenceΦ∗ˆw=Φˆw−1,G∗ˆw=˜Gˆw−1,ˆw∈W b.(2.15)It follows from the quadratic relations for T.To define the Y-intertwiners we apply the involutionεtoΦˆw and to G,˜G. The formulas can be easily calculated using(2.8).In the case of GL n one getsthe intertwiners from[Kn].For w∈W,we just need to replace X b by Y−1b and conjugate q,t(cf.[C4]).However it will be more convenient to consider η(Φ)instead ofε(Φ)to create the Macdonald polynomials.Both constructions gives the intertwiners satisfying the∗-relations from(2.15).3.Standard representationsIt was observed in[C4],Section5that there is a natural passage from the representation of H in polynomials to a representation in functions on10IV AN CHEREDNIKW b.We will continue this line,beginning with the construction of the basic representaions of level0,1.Settingx˜b =ni=1x k i i q k if˜b=[b,k],b=ni=1k i b i∈B,k∈1representation V0is induced from the character{T j→t j,πr→1}.Namely, the imageˆH is uniquely determined from the following condition:(3.7)ˆH(f(x))=g(x)for H∈H if Hf(X)−g(X)∈ni=0H(T i−t i)+ r∈O∗H(πr−1).To make the statement about V1quite obvious let us introduce the Gauss-ianγ=Const qΣn i=1z i zαi/2,where formallyx b=q z b,z a+b=z a+z b,z i=z bi,(wa)(z b)=z w(b)−(a,b),a,b∈R n. More exactly,it is a W-invariant solution of the following difference equations:(3.8)b j(γ)=Const q(1/2)Σn i=1(z i−(b j,b i))(zαi−δj i)=q−z j+(b j,b j)/2γ=q(b j,b j)/2x−1jγfor1≤j≤n.The Gaussian commutes with T j for1≤j≤n because it is W-invariant.A straightforward calculation gives that(3.9)γ(X)T0γ(X)−1=X−10T−1=τ(T0),γ(X)Y rγ(X)−1=q−(b r,b r)/2X r Y r=τ(Y r),r∈O.Hence the conjugation byγinducesτ.We can put in the following way.There is a formal H-homomorphism:(3.10)V0∋v→ˆv def=vγ−1∈V1.One has to complete V0,1to make this map well-defined(see the discrete rep-resentations below).We will later need an extended version of Proposition3.6from[C2].Proposition3.2.a)The operators{Y i,1≤i≤n}acting in V0preserve Σ(b)def=⊕c∈σ(b)C q,t x c andΣ∗(b)(defined forσ∗(b))for arbitrary b∈B.b)The operators{T j,0≤j≤n}acting in V0preserveΣ+(b)=Σ∗(b+):(3.11)ˆTj(x b)modΣ+(b)=t1/2jx b if(b,αj)=0,=t1/2js j(x b)+(t1/2j−t−1/2j)x b if(b,αj)<0,=t−1/2js j(x b)if(b,αj)>0.c)Coming to V1,if(αj,b+d)>0(0≤j≤n)then(3.12)ˆT j x b modΣ+(s j b )=t−1/2js j x b .Otherwise,(αj ,b +d )≤0and(3.13)ˆTj x b ∈Σ(b )for (αj ,b +d )≤0,ˆT j x b =t 1/2jx b if (αj ,b +d )=0.Proof.Due to Proposition 3.3from [C4]it suffices to check c)for j =0.The first inequality,the definition of ˆT 0 x b = c ∈B u bc x c ,and (1.20)readily give that (for nonzero u )c =b +rθ(r ∈Z )and(3.14)s θ(b ′)=b −θ<b <c ≤b +(α0,b +d )θ=s 0 b def =b ′.Hence c ∈σ+(b ′)if c =b ′.The coefficient u bb ′equals t −1/20.Let (α0,b +d )≤0.Then(3.15)s θ(b )=b −(b,θ)θ<c ≤b and c ∈{Σ+(b )∪b }∈Σ(b )(cf.Proposition 1.2,a)).Discretization.We go to the lattice version of the functions and opera-tors.Let ξbe a ”generic”character of C [x ]:x a (ξ)def =n i =1ξk i i ,a =n i =1k i b i ∈B,for independent parameters ξi .The discretizations of functions g (x )in x ∈C n and the operators from the algebra A def =⊕ˆu ∈W b C q,t (X )ˆu ,are described by the formulas:δx a (bw )=x a (q b w (ξ))=q (a,b )x w −1(a )(ξ),(δˆu (δg ))(bw )=δg (ˆu −1bw ).(3.16)For instance,(δX a (δg ))(bw )=x a (bw )g (bw )(we will sometimes omitδand put g (ˆw )instead of δg (ˆw )).The image of g ∈C q,t (x )belongs to the space F ξdef=Funct(W b ,C ξ)of C ξ-valued functions on W b ,where C ξdef =C q,t (ξ1,...,ξn ).Considering the discretizations of operators ˆHfor H ∈H we come to the functional representation of H in F ξ.Similarly,introducing the group algebra C ξ[W b ]=⊕ˆw ∈W b C ξδˆwfor (for-mal)delta-functions ,we can consider the dual anti-action on the indices:(3.17)δ(g (x )ˆu )( ˆw ∈W b c ˆw δˆw )= ˆw ∈W bc ˆw g (ˆw )δˆu −1ˆw ,c ˆw ∈C ξ.Composing it with the anti-involution of H(3.18)T ⋄j =T j (0≤j ≤n ),π⋄r =π−1r (r ∈O ),X ⋄i =X i (0≤i ≤n ),sending q,t to q,t(and AB to B⋄A⋄),we get the delta-representation∆ξof H in Cξ[W b]:(3.19)H→δ(ˆH⋄)def=δ(H)for H∈H.Explicitly,δπr=πr=δ(πr),r∈O,and forˆw=bwδ(Ti(g))(ˆw))=t1/2ix ai(w(ξ))q(a i,b)−t−1/2ix ai(w(ξ))q(a i,b)−1g(ˆw)for0≤i≤n,(3.20)δ(T i)(δˆw)=t1/2ix ai(w(ξ))q(a i,b)−t−1/2x ai(w(ξ))q(a i,b)−1δˆw for0≤i≤n.(3.21)There is a natural Cξ-linear pairing between Fξand∆ξ.Given g∈Funct(W b,Cξ),ˆw∈W b,{g,δˆw}def=g(ˆw),{H(g),δˆw}={g,H⋄(δˆw)},H∈H.(3.22)It also gives a nondegenerate pairing between V0and∆ξ.For arbitrary ope-rators A∈A,the relation is as follows:{δA(g),δˆw}={g,δA(δˆw)}.Let us extend the discretization map and the pairing with∆ξto V1.We use the map from(3.10)for theδ-Gaussian:(3.23)δγ(bw)def=q(b,b)/2xb(w(ξ)),which satisfies(3.8)and is a discretization ofγfor a proper constant(cf.[C4], (6.20)).The representations Fξand∆ξcan be introduced when q,t,{ξi}are con-sidered as complex numbers ensuring that x˜a(ξ)=1for all˜a∈(R a)∨.Follow-ing Proposition5.2from[C4],let us specialize the definition of∆forξ=t−ρ. In this casex a(bw)=x a(q b t−w(ρ))=q(a,b) νt−(w(ρν),a)ν.(3.24)Proposition3.3.The H-module∆(−ρ)def=∆t−ρcontains the H-sub-module∆#def=⊕b∈B Cδπb.This also holds for any q∈C∗and generic t. Moreover,∆#is irreducible if and only if q is not a root of unity.When q→0and t is a power of prime p the action of the algebra H a generated by{T j,0≤j≤n}in∆(−ρ)coincides with the standard action ofthe p-adic Hecke algebra H(G//I)∼=H a on the(linear span of)delta-functions on I\G/I∼=W a.Here I is the Iwahori subgroup of the split semisimple p-adic group G(see[IM]).However∆#does not remain a submodule in this limit.Multiplying the delta-functions on the right by the operator of t-symmet-rization we can get an H a-submodule isomorphic to∆#(upon the restriction to H a).Its limit readily exists and coincides with the space of delta-functions on I\G/K for the maximal parahoric subgroup K.However the latter space can be identified with neither spaces of delta-functions for smaller subsets of W a(as in Proposition3.3).It is possible only for the q-deformation under consideration.Practically,when calculating with right K-invariant functions in the p-adic case one needs to consider their values on the whole W a(that is an obviousflaw since much fewer number of points is enough to reconstruct them uniquely).4.OrthogonalityThe coefficient of x0=1(the constant term)of a polynomilal f∈C q,t[x] will be denoted by f 0.Let(4.1)µ= a∈R∨+∞ i=0(1−x a q i a)(1−x−1a q i+1a).(1−x a(tρ)t a q i a)(1−x a(tρ)t−1a q i a)Here x b(t±ρq c)=q(b,c) νt±(b,ρν)ν.We note thatµ∗0=µ0with respect to the involutionx∗b=x−b,t∗=t−1,q∗=q−1.Setting(4.3)f,g 0= µ0f g∗ 0= g,f ∗0for f,g∈C(q,t)[x],we introduce the non-symmetric Macdonald polynomials e b(x),b∈B−,by means of the conditions(4.4)e b−x b∈Σ∗(b), e b,x c =0for c∈σ∗={c∈B,c≻b}in the setup of Section1.They can be determined by the Gram-Schmidt process because the pairing is non-degenerate and form a basis in C(q,t)[x].This definition is due to Macdonald[M3](for tν=q k,k∈Z+)who extended Opdam’s nonsymmetric polynomials introduced in the degenerate (differential)case in[O2].He also established the connection with the Y-operators.The general case was considered in[C4].The notations are from Proposition1.1and(1.1).We use the involution ¯x a=x−1a,¯q=q,¯t=t,a∈B.Proposition4.1.a)For any H∈H and the anti-involution∗from (2.11), ˆH(f),g 0= f,ˆH∗(g) 0.Here f,g are either from V0or from V1.All products of{X b,Y b,T j,πr,q,tν}are unitary operators.b)The polynomials{e b,b∈B}are eigenvectors of the operators{L f def= f(Y1,···,Y n),f∈C[x]}:L¯f(e b)=f(#b)e b,where#b def=πb=bω−1b ,(4.5)x a(#b)def=x a(q b t−ω−1b(ρ))=q(a,b) νt−(ω−1b(ρν),a)ν,w∈W.(4.6)Proof.Assertion a)for V0is from[C2].Using(3.10)we come to V1(a formal proof is equally simple).Since operators{Y b}are unitary relative to , 0and leave allΣ(a),Σ∗(a)invariant(Proposition3.2),their eigenvectors in C q,t[x]are exactly{e}.See[M3,C4].The theorem results immediately in the orthogonality of{e b}for pairwise distinct b.Macdonald also gives the formula for the squares of e b(for tν= q k,k∈Z+)and writes that he deduced it from the corresponding formula in the W-symmetric case(proved in[C2]).The general case was considered in [C4]where we used the recurrence relations.A direct simple proof(based on the intertwiners)will be given below.The symmetric Macdonald polynomials form a basis in the space C q,t[x]W of all W-invariant polynomials and can be expressed as follows:(4.7)p b=P t b e b=P1b e b,b=b+∈B+,P t def= c∈W(b) νt lν(w c)/2νˆTw c,w cdef=ω−1c w0,P1b=P t=1b.This presentation is from[M3,C4](from[O2]in the differential case). Here one can take the complete symmetrizations(with proper coefficients) since e b is W b-invariant for the stabilizer W b of b.Macdonald introduced these polynomials in[M1,M2]by the conditionsp b−m b∈Σ+(b), p b,m c 0=0,b∈B+,c≻b,(4.8)for the monomial symmetric functions m b= c∈W(b)x c.One can also define {p}as eigenvectors for the(W-invariant)operators L f,f∈C q,t[x]W:L f(p b)=f(q b o tρ)p b,b∈B+,b o=−w0(b),(4.9)normalized as above.Applying any elements from H Y=<T j,Y b>to e c(c∈W(b+))we get solutions of(4.9),because symmetric Y-polynomials are central in H Y(due to I.Bernstein).It readily gives the coincidence of(4.7)and(4.9).Functional representations.The representations Fξ,∆ξalso have in-variant skew-symmetric forms.Letµ1(bw)=µ(bw)/µ(1)def=(4.10)a∈R∨+∞i=0(1−x a(bw)q i a)(1−x−1a(bw)q i+1a)(1−x a(1)t a q i a)(1−x−1a(1)t a q i+1a)t1/2α−qjαt−1/2αx a(ξ),(4.11)where a=α∨,and we extend the conjugation∗from C q,t to Cξsettingξ∗i=ξ−1i.b)The following Cξ-valued scalar product is well-defined for f,g from the H-submodule offinitely supported functions Fξ⊂Fξ=Funct(W b,Cξ):f,g 1= ˆw∈W bµ1(ˆw)f(ˆw)g(ˆw)∗= g,f ∗1.(4.12)c)Assertion a)from Proposition4.1holds for Fξand∆ξ,where the latter module is endowed with the scalar productf,g −1= ˆw∈W b(µ1(ˆw))−1uˆw v∗ˆw,f= uˆwδˆw,g= vˆwδˆw.(4.13)Namely, H(f),g ±1= f,H∗(g) ±1.Proof.Since x˜a(ˆw)=x˜a′(1)for˜a=˜α∨∈(R a+)∨,where˜a′def=ˆw−1(˜a), one has forˆw=bw:(4.14)µ1(ˆw)= ˜α∈R a+(1−x˜a(ˆw))(1−t a x˜a(1))(1−x˜a(1))(1−t a x˜a′(1)) = ˜α∈λ(ˆw)(1−x−1˜a(1))(1−t a x˜a(1))Here we use thatˆw−1(R a+)={−λ(ˆw)}∪{R a+\λ(ˆw)}.The invariance of µ1(ˆw)∈Cξwith respect to the conjugation∗is obvious.Other statements are completely analogous to those forµ0(and follow from them).The key relation(4.15)ˆHµ(X)=µ(X)(ˆH∗)+,H∈H,readily holds after the discretization.Here by+we mean the anti-involutionˆw+=ˆw−1∈W b,x+b=x−1b,b∈B,q,t→q−1,t−1.Its discretization conjugates the values of functions from Fξand the coefficients ofδˆw in∆ξ(fixingδˆw).The characteristic functions fˆw∈Fξ(ˆw∈W b)are defined from the rela-tions fˆw(ˆu)=δˆw,ˆu for the Kronecker delta.The action of the operators X b on them is the same as for{δˆw}:X b(fˆw)=x b(ˆw)fˆw,X b(δˆw)=x b(ˆw)δˆw,b∈B,ˆw∈W b.Moreover the mapfˆw→µ1(ˆw)δˆw,ˆw∈W b,(4.16)establishes an H-isomorphism between Fξand∆ξ,taking , 1to , −1.It readily results from the formulas:δTi(fˆw)=t1/2ix−1ai(w(ξ))q−(a i,b)−t−1/2x ai(w(ξ))q(a i,b)−1fˆw for0≤i≤n,(4.17)and the formulas for the action of{πr}.Let us consider the special caseξ=t−ρ(see(3.24)).Using the pairing(3.22),we see that the subspace(4.18)F#=⊕ˆw∈#B C q,t fˆw⊂F(−ρ)=F t−ρ,where#B={#b=πb∈W b,b∈B},is an H-submodule.It is exactly the radical of the form , 1,which is well-defined for suchξ.Indeed,anyˆw can be uniquely represented in the form(see[C2])ˆw=πb w,where b=ˆw b ,w∈W,l(ˆw)=l(πb)+l(w). Hence,{ˆw∈#B}⇒{αi∈λ(ˆw)for some i>0}⇒{µ1(ˆw)=0}.On the other hand,µ1(#b)= a∈R∨+ t−1/2α−q jαt1/2αx a(tρ)。

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