Cauchy matrix

In mathematics, a Cauchy matrix, named after Augustin-Louis Cauchy, is an m×n matrix with elements aij in the form

a i j = 1 x i y j ; x i y j 0 , 1 i m , 1 j n {\displaystyle a_{ij}={\frac {1}{x_{i}-y_{j}}};\quad x_{i}-y_{j}\neq 0,\quad 1\leq i\leq m,\quad 1\leq j\leq n}

where x i {\displaystyle x_{i}} and y j {\displaystyle y_{j}} are elements of a field F {\displaystyle {\mathcal {F}}} , and ( x i ) {\displaystyle (x_{i})} and ( y j ) {\displaystyle (y_{j})} are injective sequences (they contain distinct elements).

The Hilbert matrix is a special case of the Cauchy matrix, where

x i y j = i + j 1. {\displaystyle x_{i}-y_{j}=i+j-1.\;}

Every submatrix of a Cauchy matrix is itself a Cauchy matrix.

Cauchy determinants

The determinant of a Cauchy matrix is clearly a rational fraction in the parameters ( x i ) {\displaystyle (x_{i})} and ( y j ) {\displaystyle (y_{j})} . If the sequences were not injective, the determinant would vanish, and tends to infinity if some x i {\displaystyle x_{i}} tends to y j {\displaystyle y_{j}} . A subset of its zeros and poles are thus known. The fact is that there are no more zeros and poles:

The determinant of a square Cauchy matrix A is known as a Cauchy determinant and can be given explicitly as

det A = i = 2 n j = 1 i 1 ( x i x j ) ( y j y i ) i = 1 n j = 1 n ( x i y j ) {\displaystyle \det \mathbf {A} ={{\prod _{i=2}^{n}\prod _{j=1}^{i-1}(x_{i}-x_{j})(y_{j}-y_{i})} \over {\prod _{i=1}^{n}\prod _{j=1}^{n}(x_{i}-y_{j})}}}     (Schechter 1959, eqn 4; Cauchy 1841, p. 154, eqn. 10).

It is always nonzero, and thus all square Cauchy matrices are invertible. The inverse A−1 = B = [bij] is given by

b i j = ( x j y i ) A j ( y i ) B i ( x j ) {\displaystyle b_{ij}=(x_{j}-y_{i})A_{j}(y_{i})B_{i}(x_{j})\,}     (Schechter 1959, Theorem 1)

where Ai(x) and Bi(x) are the Lagrange polynomials for ( x i ) {\displaystyle (x_{i})} and ( y j ) {\displaystyle (y_{j})} , respectively. That is,

A i ( x ) = A ( x ) A ( x i ) ( x x i ) and B i ( x ) = B ( x ) B ( y i ) ( x y i ) , {\displaystyle A_{i}(x)={\frac {A(x)}{A^{\prime }(x_{i})(x-x_{i})}}\quad {\text{and}}\quad B_{i}(x)={\frac {B(x)}{B^{\prime }(y_{i})(x-y_{i})}},}

with

A ( x ) = i = 1 n ( x x i ) and B ( x ) = i = 1 n ( x y i ) . {\displaystyle A(x)=\prod _{i=1}^{n}(x-x_{i})\quad {\text{and}}\quad B(x)=\prod _{i=1}^{n}(x-y_{i}).}

Generalization

A matrix C is called Cauchy-like if it is of the form

C i j = r i s j x i y j . {\displaystyle C_{ij}={\frac {r_{i}s_{j}}{x_{i}-y_{j}}}.}

Defining X=diag(xi), Y=diag(yi), one sees that both Cauchy and Cauchy-like matrices satisfy the displacement equation

X C C Y = r s T {\displaystyle \mathbf {XC} -\mathbf {CY} =rs^{\mathrm {T} }}

(with r = s = ( 1 , 1 , , 1 ) {\displaystyle r=s=(1,1,\ldots ,1)} for the Cauchy one). Hence Cauchy-like matrices have a common displacement structure, which can be exploited while working with the matrix. For example, there are known algorithms in literature for

  • approximate Cauchy matrix-vector multiplication with O ( n log n ) {\displaystyle O(n\log n)} ops (e.g. the fast multipole method),
  • (pivoted) LU factorization with O ( n 2 ) {\displaystyle O(n^{2})} ops (GKO algorithm), and thus linear system solving,
  • approximated or unstable algorithms for linear system solving in O ( n log 2 n ) {\displaystyle O(n\log ^{2}n)} .

Here n {\displaystyle n} denotes the size of the matrix (one usually deals with square matrices, though all algorithms can be easily generalized to rectangular matrices).

See also

References

  • Cauchy, Augustin-Louis (1841). Exercices d'analyse et de physique mathématique. Vol. 2 (in French). Bachelier.
  • A. Gerasoulis (1988). "A fast algorithm for the multiplication of generalized Hilbert matrices with vectors" (PDF). Mathematics of Computation. 50 (181): 179–188. doi:10.2307/2007921. JSTOR 2007921.
  • I. Gohberg; T. Kailath; V. Olshevsky (1995). "Fast Gaussian elimination with partial pivoting for matrices with displacement structure" (PDF). Mathematics of Computation. 64 (212): 1557–1576. Bibcode:1995MaCom..64.1557G. doi:10.1090/s0025-5718-1995-1312096-x.
  • P. G. Martinsson; M. Tygert; V. Rokhlin (2005). "An O ( N log 2 N ) {\displaystyle O(N\log ^{2}N)} algorithm for the inversion of general Toeplitz matrices" (PDF). Computers & Mathematics with Applications. 50 (5–6): 741–752. doi:10.1016/j.camwa.2005.03.011.
  • S. Schechter (1959). "On the inversion of certain matrices" (PDF). Mathematical Tables and Other Aids to Computation. 13 (66): 73–77. doi:10.2307/2001955. JSTOR 2001955.
  • TiIo Finck, Georg Heinig, and Karla Rost: "An Inversion Formula and Fast Algorithms for Cauchy-Vandermonde Matrices", Linear Algebra and its Applications, vol.183 (1993), pp.179-191.
  • Dario Fasino: "Orthogonal Cauchy-like matrices", Numerical Algorithms, vol.92 (2023), pp.619-637. url=https://doi.org/10.1007/s11075-022-01391-y .
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