linalg

  • full name: tenpy.linalg

  • parent module: tenpy

  • type: module

Module description

Linear-algebra tools for tensor networks.

Most notably is the module np_conserved, which contains everything needed to make use of charge conservation in the context of tensor networks.

Relevant contents of charges are imported to np_conserved, so you probably won’t need to import charges directly.

Submodules

np_conserved

A module to handle charge conservation in tensor networks.

charges

Basic definitions of a charge.

svd_robust

(More) robust version of singular value decomposition.

random_matrix

Provide some random matrix ensembles for numpy.

sparse

Providing support for sparse algorithms (using matrix-vector products only).

krylov_based

Lanczos algorithm for np_conserved arrays.