* 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
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133 B
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4 lines
133 B
Plaintext
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