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1: 1.1 Special Notation
x , y real variables.
𝐀 1 inverse of the square matrix 𝐀
𝐈 identity matrix
det ( 𝐀 ) determinant of the square matrix 𝐀
tr ( 𝐀 ) trace of the square matrix 𝐀
In the physics, applied maths, and engineering literature a common alternative to a ¯ is a , a being a complex number or a matrix; the Hermitian conjugate of 𝐀 is usually being denoted 𝐀 .
2: 1.2 Elementary Algebra
The Matrix Exponential and the Exponential of the Trace
The matrix exponential is defined via
1.2.76 exp ( 𝐀 ) = n = 0 1 n ! 𝐀 n ,
1.2.77 det ( exp ( 𝐀 ) ) = exp ( tr ( 𝐀 ) ) = etr ( 𝐀 ) .
3: 35.6 Confluent Hypergeometric Functions of Matrix Argument
35.6.2 Ψ ( a ; b ; 𝐓 ) = 1 Γ m ( a ) 𝛀 etr ( 𝐓 𝐗 ) | 𝐗 | a 1 2 ( m + 1 ) | 𝐈 + 𝐗 | b a 1 2 ( m + 1 ) d 𝐗 , ( a ) > 1 2 ( m 1 ) , 𝐓 𝛀 .
4: 35.8 Generalized Hypergeometric Functions of Matrix Argument
5: 35.5 Bessel Functions of Matrix Argument
35.5.3 B ν ( 𝐓 ) = 𝛀 etr ( ( 𝐓 𝐗 + 𝐗 1 ) ) | 𝐗 | ν 1 2 ( m + 1 ) d 𝐗 , ν , 𝐓 𝛀 .
6: 35.1 Special Notation
a , b complex variables.
𝟎 zero matrix.
𝐈 identity matrix.
The main functions treated in this chapter are the multivariate gamma and beta functions, respectively Γ m ( a ) and B m ( a , b ) , and the special functions of matrix argument: Bessel (of the first kind) A ν ( 𝐓 ) and (of the second kind) B ν ( 𝐓 ) ; confluent hypergeometric (of the first kind) F 1 1 ( a ; b ; 𝐓 ) or F 1 1 ( a b ; 𝐓 ) and (of the second kind) Ψ ( a ; b ; 𝐓 ) ; Gaussian hypergeometric F 1 2 ( a 1 , a 2 ; b ; 𝐓 ) or F 1 2 ( a 1 , a 2 b ; 𝐓 ) ; generalized hypergeometric F q p ( a 1 , , a p ; b 1 , , b q ; 𝐓 ) or F q p ( a 1 , , a p b 1 , , b q ; 𝐓 ) . … Related notations for the Bessel functions are 𝒥 ν + 1 2 ( m + 1 ) ( 𝐓 ) = A ν ( 𝐓 ) / A ν ( 𝟎 ) (Faraut and Korányi (1994, pp. 320–329)), K m ( 0 , , 0 , ν | 𝐒 , 𝐓 ) = | 𝐓 | ν B ν ( 𝐒 𝐓 ) (Terras (1988, pp. 49–64)), and 𝒦 ν ( 𝐓 ) = | 𝐓 | ν B ν ( 𝐒 𝐓 ) (Faraut and Korányi (1994, pp. 357–358)).
7: 35.2 Laplace Transform
8: 21.3 Symmetry and Quasi-Periodicity
21.3.3 θ ( 𝐳 + 𝐦 1 + 𝛀 𝐦 2 | 𝛀 ) = e 2 π i ( 1 2 𝐦 2 𝛀 𝐦 2 + 𝐦 2 𝐳 ) θ ( 𝐳 | 𝛀 ) ,
21.3.4 θ [ 𝜶 + 𝐦 1 𝜷 + 𝐦 2 ] ( 𝐳 | 𝛀 ) = e 2 π i 𝜶 𝐦 2 θ [ 𝜶 𝜷 ] ( 𝐳 | 𝛀 ) .
21.3.5 θ [ 𝜶 𝜷 ] ( 𝐳 + 𝐦 1 + 𝛀 𝐦 2 | 𝛀 ) = e 2 π i ( 𝜶 𝐦 1 𝜷 𝐦 2 1 2 𝐦 2 𝛀 𝐦 2 𝐦 2 𝐳 ) θ [ 𝜶 𝜷 ] ( 𝐳 | 𝛀 ) .
9: 19.31 Probability Distributions
19.31.2 n ( 𝐱 T 𝐀 𝐱 ) μ exp ( 𝐱 T 𝐁 𝐱 ) d x 1 d x n = π n / 2 Γ ( μ + 1 2 n ) det 𝐁 Γ ( 1 2 n ) R μ ( 1 2 , , 1 2 ; λ 1 , , λ n ) , μ > 1 2 n .
10: 21.2 Definitions
21.2.1 θ ( 𝐳 | 𝛀 ) = 𝐧 g e 2 π i ( 1 2 𝐧 𝛀 𝐧 + 𝐧 𝐳 ) .
21.2.2 θ ^ ( 𝐳 | 𝛀 ) = e π [ 𝐳 ] [ 𝛀 ] 1 [ 𝐳 ] θ ( 𝐳 | 𝛀 ) .
21.2.5 θ [ 𝜶 𝜷 ] ( 𝐳 | 𝛀 ) = 𝐧 g e 2 π i ( 1 2 [ 𝐧 + 𝜶 ] 𝛀 [ 𝐧 + 𝜶 ] + [ 𝐧 + 𝜶 ] [ 𝐳 + 𝜷 ] ) .
21.2.6 θ [ 𝜶 𝜷 ] ( 𝐳 | 𝛀 ) = e 2 π i ( 1 2 𝜶 𝛀 𝜶 + 𝜶 [ 𝐳 + 𝜷 ] ) θ ( 𝐳 + 𝛀 𝜶 + 𝜷 | 𝛀 ) ,