* Breaking Changes
+ renamed MatrixProductState.partial_trace and MatrixProductState.ptr to
MatrixProductState.partial_trace_to_mpo to avoid confusion with other
partial_trace methods that usually produce a dense matrix.
* Enhancements:
+ tensor network fitting: add method="tree" for when ansatz is a tree -
tensor_network_fit_tree
+ tensor network fitting: fix method="als" for complex networks
+ tensor network fitting: allow method="als" to use a iterative solver
suited to much larger tensors, by default a custom conjugate gradient
implementation.
+ tensor_network_distance and fitting: support hyper indices explicitly
via output_inds kwarg
+ add tn.make_overlap and tn.overlap for computing the overlap between
two tensor networks, ⟨ O | T ⟩ , with explicit handling of outer
indices to address hyper networks. Add output_inds to tn.norm and
tn.make_norm also, as well as the squared kwarg.
+ replace all numba based paralellism (prange and parallel vectorize)
with explicit thread pool based parallelism. Should be more reliable
and no need to set NUMBA_NUM_THREADS anymore. Remove env var
QUIMB_NUMBA_PAR.
+ Circuit: add dtype and convert_eager options. dtype specifies what the
computation should be performed in. convert_eager specifies whether to
apply this (and any to_backend calls) as soon as gates are applied
(the default for MPS circuit simulation) or just prior to contraction
(the default for exact contraction simulation).
+ tn.full_simplify: add check_zero (by default set of "auto") option
which explicitly checks for zero tensor norms when equalizing norms to
avoid log10(norm) resulting in -inf or nan. Since it creates a data
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-quimb?expand=0&rev=23
