jax.numpy.linalg.cholesky

jax.numpy.linalg.cholesky(a)

Cholesky decomposition.

LAX-backend implementation of numpy.linalg.cholesky().

Original docstring below.

Return the Cholesky decomposition, L * L.H, of the square matrix a, where L is lower-triangular and .H is the conjugate transpose operator (which is the ordinary transpose if a is real-valued). a must be Hermitian (symmetric if real-valued) and positive-definite. No checking is performed to verify whether a is Hermitian or not. In addition, only the lower-triangular and diagonal elements of a are used. Only L is actually returned.

Parameters:

a ((..., M, M) array_like) – Hermitian (symmetric if all elements are real), positive-definite input matrix.

Returns:

L – Lower-triangular Cholesky factor of a. Returns a matrix object if a is a matrix object.

Return type:

(…, M, M) array_like