# linalg¶

Module description

Linear-algebra tools for tensor networks.

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

Relevant contents of charges are imported to np_conserved, so you propably 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). lanczos Lanczos algorithm for np_conserved arrays.