pytenet

PyTeNet

Python implementation of quantum tensor network operations and simulations within the matrix product state framework.

Modules

autop	Operator state automaton, can be converted to an MPO via an operator graph.
bipartite_graph	Implementation of the Hopcroft-Karp algorithm, based on https://en.wikipedia.org/wiki/Hopcroft%E2%80%93Karp_algorithm
block_sparse_util	utility functions for handling block-sparse tensors with quantum number conservation.
bond_ops	Functions concerning virtual bonds.
chain_ops	Higher-level tensor network operations on a chain topology.
dmrg	DMRG algorithm.
hamiltonian	Construction of common quantum Hamiltonians as matrix product operators (MPOs).
krylov	Krylov subspace algorithms.
mpo	Matrix product operator (MPO) class and associated functionality.
mps	Matrix product state (MPS) class and associated functionality.
opchain	Symbolic operator chain.
opgraph	Operator graph internal data structure for generating MPO representations.
optree	Symbolic operator tree.
tdvp	TDVP time integration algorithms for MPS, based on a Lanczos iteration for the local time evolution steps.
thc	Tensor hypercontraction (THC) representation of molecular Hamiltonians.
util	Generic utility functions.