v1.10.0

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 dtype 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, $\langle O |T \rangle$, 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 dependency that breaks e.g. jax tracing, it is optional.
• schematic.Drawing: add shorten kwarg to line drawing and curve drawing and examples to the docs.
• TensorNetwork: add .backend and .dtype_name properties.

PRs:

• Circuit: add default dtype and convert_eager options by @jcmgray in #273
• add fit(method="tree") and fix ALS for complex TNs by @jcmgray in #274

Full Changelog: v1.9.0...v1.10.0