Changelog

Release notes for quimb.

v1.14.1 (unreleased)

Enhancements:

• add CircuitPEPSSimpleUpdate: a high level quantum circuit simulator that keeps the state as an arbitrary geometry PEPS and applies nearest-neighbor gates with ‘simple update’ style gauging. The geometry is given by a set of edges, inferred from the gates or read from a psi0; the accuracy is set by max_bond; gauges can be periodically re-equilibrated with equilibrate; local expectations are computed with the cluster approximation.

• add CircuitPEPOSimpleUpdate: the Heisenberg-picture companion to CircuitPEPSSimpleUpdate. Gates are recorded lazily, then a local observable is built as a bond dimension 1 PEPO on the edges and evolved backwards through them with simple update gauging and compression (skipping gates outside its reverse lightcone), exposing the evolved operator via get_evolved_operator and its |00...0> expectation via local_expectation.

• TensorNetwork.gauge_all_simple: add a fuse_multibonds option for updating gauges while preserving multi-index bonds, supported by explicit bond-index selection in tensor_compress_bond.

• add LatticeBondMap: helper for consistently assigning lattice bond indices across ordinary and periodic boundaries, use it in PEPS, PEPO, PEPS3D, scalar 2D/3D lattice tensor-network construction, and classical Ising tensor-network construction.

• eigh_truncated: add a shift option for optional diagonal regularization.

• CircuitMPSLazy: add a MPS-based circuit simulator using lazily evaluated gates and periodic automated compression, performing better compared to CircuitMPS for long-range gates when using src compression method.

• Circuit.from_openqasm3_str, Circuit.from_openqasm3_file, and Circuit.from_openqasm3_url: add OpenQASM 3 parsing with custom gates, register broadcasting, and symbolic input tracking.

Bug fixes:

• tensor_network_1d_compress_src and tensor_network_1d_compress_srcmps: call enforce_1d_like like the other 1D compression methods, fixing compression of tensor networks with long range (site skipping) bonds, e.g. from lazily applied long range gates.

• enforce_1d_like: fix the identity string insertion for long range bonds when the supplied site_tags order the two tensors in reverse (e.g. with sweep_reverse=True), which previously wired the identities to the wrong sites.

• PEPS, PEPO, and PEPS3D: fix periodic construction for length-1 and length-2 cyclic dimensions so normal and periodic bonds remain distinct, including bond-dimension-1 cyclic tensors.

• TensorNetwork2DVector.compute_norm: ensure we always return a scalar rather than unwrapped tensor network.

• D2BP.partial_trace_loop_series_expansion: fix the loop series expansion for complex (hermitian) BP messages, which were inserted with the wrong (ket, bra) index ordering in get_cluster_excited (both boundary messages and inner excitation projectors), giving incorrect reduced density matrices for complex states (GH #380).

• D2BP.normalize_tensors: keep the cached dual tensors in sync when rescaling, so that repeated reduced density matrix computations no longer drift (GH #381).

v1.14.0 (2026-05-10)

Breaking Changes

• tensor_compress_bond: rename input tensor args ta and tb

Enhancements:

• D2BP: support fermionic tensor networks (only computing norm^2 so far, gating/compression need work).

• tensor_compress_bond: add reduce_opts for controlling the decomposition options used when reducing each tensor before the main truncating decomposition. For example reduce_opts={"method": "qr:cholesky"}.

• add TensorNetworkGen.select_sites as a convenience method for selecting a sub network given a list of sites.

• add PEPO_product_operator for bond-dimension-1 PEPOs given by a product of on-site operators, including cyclic boundary conditions via cyclic=True or cyclic=(cyclic_x, cyclic_y).

• PEPO: accept explicit cyclic kwarg in the constructor, to override shape-based boundary-condition inference (required for bond dimension 1 cyclic PEPOs).

• TensorNetworkGenOperator: add generic apply (dispatching on operator/vector tensor networks), trace and partial_transpose methods. These now work for arbitrary geometry operator tensor networks (including MPO and PEPO); partial_transpose supports arbitrary hashable site labels. apply also gains an inplace option that propagates to the acting operator rather than the one being acted on.

• add TensorNetworkGen.has_site to test whether an object is a valid site label of a tensor network. The generic implementation checks membership in the site set; 1D, 2D and 3D tensor networks override it with a fast bounds check.

• add LocalHam2D.build_pepo_propagator_trotterized for a first-order Trotter decomposition of expm(x H) as a PEPO. Accepts an ordering argument to control the order in which terms are applied.

• TensorNetwork.split_simplify: consider all candidate bipartitions for each tensor and accept the one that minimizes the resulting maximum tensor size, rather than the first reduction found.

• contract_hotrg, coarse_grain_hotrg, their 3D counterparts, and tensor_network_ag_compress_projector: add gauge_power parameter to control the power applied to the bond gauge weights when canonize=True before computing the compressed projectors.

• RegionGraph: add get_maximal_regions, get_minimal_regions, and get_maximal_ancestors helpers for querying the region hierarchy.

Drawing and schematic updates:

• Drawing: add orthographic projection mode alongside the existing axonometric projection via the new projection parameter (replaces a/b). Named presets include "orthographic", "axonometric", and "isometric".

• Drawing.translate: new context manager to temporarily offset all draw operations in coordinate space (before projection).

• Drawing.translate_screen: new context manager to temporarily offset all draw operations in screen space (after projection).

• Drawing.grid3d: automatically select back-facing planes based on projection so grids always appear behind the scene, use readable tick label orientations for all projections, and place axis labels correctly.

Bug fixes:

• CircuitPermMPS.sample: fix output bitstring ordering when the internal MPS qubit order is permuted (GH #327).

• TensorNetwork.split_tensor: fix handling of absorb=None, adding all tensors returned by the split (GH #260).

• D2BP.gate_: correctly mark touched tensors and rebuild local contraction expressions after applying gates.

• contract_hotrg and 3D counterpart: fix bug when specifying strip_exponent in final_contract_opts.

v1.13.0 (2026-03-19)

Breaking Changes

• ham_hubbard_hardcore fix description and sign convention of hopping strength t.

• heisenberg_from_edges fix sign convention of magnetic field terms.

• the quimb.tensor submodule structure has been refactored with tn1d, tn2d, tn3d, and tnag submodules for better organization. Imports from old locations will still work, but are deprecated. Public classes and functions such as MatrixProductState are directly accessible from the top level quimb.tensor module as before.

Enhancements:

Major updates to splitting/decomposing individual tensors/arrays:

• add array_split and array_svals as the primary array-level entry points for matrix decomposition, consolidating dispatch logic that was previously internal to tensor_core.

• add register_split_driver and register_svals_driver decorators for registering custom matrix decomposition methods with array_split and array_svals.

• allow array_split to handle batches of matrices (for most methods).

• array_split: automatically detect and forward valid kwargs to underlying decomposition methods.

• tensor_split and array_split: expand absorb options significantly beyond "left", "both", "right", None to include "lorthog", "rorthog", "lfactor", "rfactor", "lsqrt", "rsqrt and "s" for returning partial results (single factors or singular values only). Default changed from "both" to "auto", which uses each method’s natural default.

• add method "svd:eig" with main implementation svd_via_eig for efficient SVD via hermitian eigen-decomposition, with shortcuts for all absorb modes. This can be faster (especially e.g. on GPU) than the standard SVD, but entails some loss of precision.

• tensor_split: rename method option "eig" to "svd:eig" to make it clearer that this is an SVD split via eigen-decomposition. "eig" remains as a deprecated alias for "svd:eig".

• add method "svd:rand" with main implementation svd_rand_truncated for randomized SVD with truncation, with shortcuts for all absorb modes. (This is a new and backend agnostic implementation as opposed to the existing 'rsvd' method).

• add method "qr:cholesky" qr_via_cholesky for efficient QR or LQ like decompositions via cholesky decomposition, with shortcuts for all absorb modes. This can be faster than the standard QR (especially on GPU) but entails some loss of precision.

• tensor_split and array_split: add "lsqrt" and "rsqrt" absorb options, update cholesky decomposition to cholesky_regularized with shift as exposed parameter.

• compute_oblique_projectors: allow method kwarg.

• QR decomposition: add stabilize kwarg for controlling QR stabilization behavior.

• decomposition methods: various compatibility improvements for JAX backend.

Other enhancements:

• add shift and clock operators.

• add Tensor.isfermionic and TensorNetwork.isfermionic methods.

• add Tensor.isblocksparse and TensorNetwork.isblocksparse methods.

• add phase_dual option to TensorNetwork.conj.

• rename tensor_network_1d_compress_zipup_first to tensor_network_1d_compress_zipup_oversample and standardise oversample arguments.

• add tensor_network_1d_compress_srcmps_oversample and tensor_network_1d_compress_fit_oversample methods.

• add connected_bipartitions for finding all connected bipartitions of a tensor network

• tn.distribute_exponent: add new_exponent option for specifying the new exponent value (default 0.0).

• tensor_network_1d_compress: correctly handle input networks with non-zero exponents and equalize_norms.

• add tensor_network_gate_sandwich_inds for applying a gate and its conjugate like \(G A G^\dagger\) to a tensor network.

• tensor_network_ag_gate: add which="sandwich" option for applying a gate and its conjugate like \(G A G^\dagger\) to a tensor network, default to this if the supplied tensor network is a TensorNetworkGenOperator.

• add function tensor_network_ag_gate_simple for applying a gate to an arbitrary geometry tensor network vector or operator, using simple update style gauges to perform any compression.

• insert_compressor_between_regions and upstream CTMRG/HOTRG methods: add explicit contract_opts, reduce_opts, and compress_opts keyword arguments for fine-grained control.

• TensorNetwork2D.contract_boundary, contract_ctmrg, contract_hotrg, coarse_grain_hotrg and their 3D counterparts: add strip_exponent parameter and equalize_norms="auto" default.

• TensorNetwork3D.contract_hotrg: use updated projecting/gauging scheme.

• all compression methods: accept an explicit compress_opts kwarg.

• tensor_network_ag_compress: allow fine-grained control over split options via compress_opts.

• TensorNetworkGen.flatten: add arbitrary geometry flatten method, used in 1D/2D/3D.

• RegionGraph: various improvements.

• add hash_kwargs_to_int utility for hashing keyword arguments to a deterministic integer.

Bug fixes:

• fix isometrize_qr for complex torch arrays (GH #346).

• fix right_canonicalize to return the right canonicalized tensor network (GH #347)

• ensure all belief propagation contraction methods correctly propagate the target tensor network’s .exponent.

• fix cutoff mode bug in array_split decomposition truncation.

• fix tensor_network_1d_compress_zipup equalize_norms exponent accumulation.

• fix final_contract_opts inplace handling in boundary contraction methods.

• fix squared_op_to_reduced_factor argument handling.

• fix cholesky decomposition shift kwarg forwarding and absorb="right" direction.

• fix sample_hd1bp sub-progress bar display.

• fix gate tag propagation in tensor_network_gate_inds.

• handle equalize_norms correctly in TensorNetwork2D.compute_environments (GH #352).

v1.12.1 (2026-01-12)

Breaking Changes

• bump minimum required python version to 3.11

Bug fixes:

• fix SimpleUpdateGen mixin inheritance order.

• fix insert_compressor_between_regions for fermionic tensor networks with bond signature +-.

v1.12.0 (2026-01-09)

Enhancements:

• move the experimental operatorbuilder module to the main quimb.operator module.

• add basic introduction to the operator module - Basics

• add new example on tracing tensor network functions Tracing tensor network functions and reusing intermediates

• tensor_split: add an info kwarg, supplying this with an empty dict or with the entry 'error' will store the truncation error when using method in {"svd", "svd:eig"}.

• update infrastructure for TEBD and SimpleUpdate based algorithms.

• schematic.Drawing: add grid, grid3d, bezier, star, cross and zigzag methods.

• schematic.Drawing: add relative option to arrowhead, shorten option to text_between and text_left and text_right options to line.

• add Drawing.scale_figsize for automatically setting the absolute figsize based on placed elements.

• refactor TEBDGen and SimpleUpdateGen

• update the 2d specific SimpleUpdate to use the new infrastructure.

• tn.draw(): show abelian signature if using symmray arrays.

• tn.draw(): add adjust_lims option

• TNOptimizer: allow autodiff_backend="torch" with jit_fn=True to work with array backends with general pytree parameters, e.g. symmray arrays.

• tn.gen_gloops and tn.gen_gloops_sites: add join_overlap option. When building cluster by joining smaller generalized loops, this option controls how many nodes they need to overlap by to be joined together.

• all message passing routines: add callback option

• GBP: allow a message initilization function.

• D1BP: allow messages to be a callable initialization function.

• MatrixProductState.gate_nonlocal: add method="lazy" option for lazily applying a non-local gate as a sub-MPO without contraction or compression.

• LocalHamGen.apply_to_arrays: support pytree parameter arrays such as symmray.

• add Tensor.get_namespace and TensorNetwork.get_namespace for getting a reusable data array namespace

• TensorNetwork.isel: use take where possible to better support e.g. torch.vmap across amplitudes.

• MatrixProductState.measure, and MatrixProductState.sample: add backend_random option for specifying which backend to use for random number generation when sampling, this can be set for example to jax to make the whole process jittable, but by default is numpy, regardless of the actual array backend.

Bug fixes:

• fix insert_compressor_between_regions when insert_into is None.

• tensor network drawing, ensure hyper indices can be specified as output_inds.

• fix MatrixProductState.measure when using jax arrays (GH #340).

• fix MatrixProductState.measure when projecting and keeping a site site (GH #344).

v1.11.2 (2025-07-30)

Enhancements:

• Update the introduction to tensor contraction docs

• Improve efficiency of 1D structured contractions when default optimize is used, especially for large bond dimension overlaps.

Bug fixes:

• fixes for MPS and MPO constructors when L=1, (GH #314)

• tensor splitting with absorb=”left” now correctly marks left indices.

• tn.isel: fix bug when value could not be compared to string "r"

• truncated svd, make n_chi comparison more robust to different backends

v1.11.1 (2025-06-20)

Enhancements:

• add create_bond to tensor_canonize_bond and tensor_compress_bond for optionally creating a new bond between two tensors if they don’t already share one. Add as a flag to TensorNetwork1DFlat.compress and related functions (GH #294).

• add ensure_bonds_exist for ensuring that all bonds in a 1D flat tensor network exist. Use this in the permute_arrays methods and optionally in the expand_bond_dimension method.

• tn.draw(): permit empty network, and allow color=True to automatically color all tags.

• tn.add_tag: add a record: Optional[dict] kwarg, to allow for easy rewinding of temporary tags without tracking the actual networks.

• add qu.plot as a quick wrapper for calling matplotlib.pyplot.plot with the quimb style.

• quimb.schematic: add zorder_delta kwarg for fine adjustments to layering of objects in approximately the same position.

• operatorbuilder: big performance improvements and fixes for building matrix representations including Z2 symmetry. Add default symmetry and sector options that can be overridden at build time. Add lazy (slow, matrix free) ‘apply’ method. Add pauli_decompose transformation. Add experimental PEPO builder for nearest neighbor operators. Add unit tests.

Bug fixes:

• Fix TensorNetwork2D.compute_plaquette_environments for mode="zipup" and other boundary contraction methods that use the generic 1D compression algorithms.

• parse_openqasm2_str allow custom gate names to start with the word gate (GH #312).

• MatrixProductState.gate_with_mpo: fix bug to do with inplace argument (GH #313).

v1.11.0 (2025-05-14)

Breaking Changes

• move belief propagation to quimb.tensor.belief_propagation

• calling tn.contract() when an non-zero value has been accrued into tn.exponent now automatically re-absorbs that exponent.

• binary tensor operations that would previously have errored now will align and broadcast

Enhancements:

• Tensor: make binary operations (+, -, *, /, **) automatically align and broadcast indices. This would previously error.

• MatrixProductState.measure: add a seed kwarg

• belief propagation, implement DIIS (direct inversion in the iterative subspace)

• belief propagation, unify various aspects such as message normalization and distance.

• belief propagation, add a plot method.

• belief propagation, add a contract_every option.

• HV1BP: vectorize both contraction and message initialization

• add qu.plot_multi_series_zoom for plotting multiple series with a zoomed inset, useful for various convergence plots such as BP

• add info option to tn.gauge_all_simple for tracking extra information such as number of iterations and max gauge diffs

• Tensor.gate: add transposed option

• TensorNetwork.contract: add strip_exponent option for return the mantissa and exponent (log10) separately. Compatible with contract_tags, contract_cumulative, contract_compressed sub modes.

• tensor_split: add matrix_svals option, if True any returned singular values are put into the diagonal of a matrix (by default, False, they are returned as a vector).

• add Tensor.new_ind_pair_diag for expanding an existing index into a pair of new indices, such that the diagonal of the new tensor on those indices is the old tensor.

• TNOptimizer: add ‘cautious’ ADAM

• TensorNetwork.pop_tensor: allow tid or tags to be specified.

• add an example notebook for converting hyper tensor networks to normal tensor networks, for approximate contraction - Converting a hyper TN for approximate contraction

• add “SX” and “SXDG” gates to Circuit (PR #277)

• add “XXPLUSYY” and “XXPLUSYY” gates to Circuit (PR #279)

• add progress bar to various Circuit methods (PR #288)

• quimb.operator: fix MPO building for congested operators (GH #296 and GH #301), allow arbitrary dtype (GH #289). Fix building of sparse and matrix representations for non-translationally symmetric operators and operators with trivial (all identity) terms.

Bug fixes:

• fix MatrixProductState.measure for cupy backend arrays (GH #276).

• fix linalg.expm dispatch (GH #275)

• fix ‘dm’ 1d compress method for disconnected subgraphs

• fix docs source lookup in quimb.tensor module

• fix raw gate copying in Circuit (GH #285)

v1.10.0 (2024-12-18)

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, \(\langle O |T \rangle\), 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 schematic - manual drawing.

• TensorNetwork: add .backend and .dtype_name properties.

v1.9.0 (2024-11-19)

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:

• add Circuit.sample_gate_by_gate and related methods Circuit.reordered_gates_dfs_clustered and Circuit.get_qubit_distances for sampling a circuit using the ‘gate by gate’ method introduced in https://arxiv.org/abs/2112.08499.

• add Circuit.draw for drawing a very simple circuit schematic.

• Circuit: by default turn on simplify_equalize_norms and use a group_size=10 for sampling. This should result in faster and more stable sampling.

• Circuit: use numpy.random.default_rng for random number generation.

• add qtn.circ_a2a_rand for generating random all-to-all circuits.

• expose qtn.edge_coloring as top level function and allow layers to be returned grouped.

• add docstring for tn.contract_compressed and by default pick up important settings from the supplied contraction path optimizer (max_bond and compress_late)

• add Tensor.rand_reduce for randomly removing a tensor index by contracting a random vector into it. One can also supply the value "r" to isel selectors to use this.

• add fit-zipup and fit-projector shorthand methods to the general 1d tensor network compression function

• add MatrixProductState.compute_local_expectation for computing many local expectations for a MPS at once, to match the interface for this method elsewhere. These can either be computed via canonicalization (method="canonical"), or via explicit left and right environment contraction (method="envs")

• specialize CircuitMPS.local_expectation to make use of the MPS form.

• add PEPS.product_state for constructing a PEPS representing a product state.

• add PEPS.vacuum for constructing a PEPS representing the vacuum state \(|000\ldots0\rangle\).

• add PEPS.zeros for constructing a PEPS whose entries are all zero.

• tn.gauge_all_simple: improve scheduling and add damping and touched_tids options.

• qtn.SimpleUpdateGen: add gauge difference update checking and tol and equilibrate settings. Update .plot() method. Default to a small cutoff.

• add psi.sample_configuration_cluster for sampling a tensor network using the simple update or cluster style environment approximation.

• add the new doc Exploring circuit sampling with various methods

---

v1.8.4 (2024-07-20)

Bug fixes:

• fix for MPS sampling with fixed seed (GH #247 and PR #248)

• fix for mps_gate_with_mpo_lazy (GH #246).

---

v1.8.3 (2024-07-10)

Enhancements:

• support for numpy v2.0 and scipy v1.14

• add MPS sampling: MatrixProductState.sample_configuration and MatrixProductState.sample (generating multiple samples) and use these for CircuitMPS.sample and CircuitPermMPS.sample.

• add basic .plot() method for SimpleUpdate classes

• add edges_1d_chain for generating 1D chain edges

• operatorbuilder: better coefficient placement for long range MPO building

---

v1.8.2 (2024-06-12)

Enhancements:

• TNOptimizer can now accept an arbitrary pytree (nested combination of dicts, lists, tuples, etc. with TensorNetwork, Tensor or raw array_like objects as the leaves) as the target object to optimize.

• TNOptimizer can now directly optimize Circuit objects, returning a new optimized circuit with updated parameters.

• Circuit: add .copy(), .get_params() and .set_params() interface methods.

• Update generic TN optimizer docs.

• add tn.gen_paths_loops for generating all loops of indices in a TN.

• add tn.gen_inds_connected for generating all connected sets of indices in a TN.

• make SVD fallback error catching more generic (PR #238)

• fix some windows + numba CI issues.

• approx_spectral_function add plotting and tracking

• add dispatching to various tensor primitives to allow overriding

---

v1.8.1 (2024-05-06)

Enhancements:

• CircuitMPS now supports multi qubit gates, including arbitrary multi-controls (which are treated in a low-rank manner), and faster simulation via better orthogonality center tracking.

• add CircuitPermMPS

• add MatrixProductState.gate_nonlocal for applying a gate, supplied as a raw matrix, to a non-local and arbitrary number of sites. The kwarg contract="nonlocal" can be used to force this method, or the new option "auto-mps" will select this method if the gate is non-local (GH #230)

• add MatrixProductState.gate_with_mpo for applying an MPO to an MPS, and immediately compressing back to MPS form using tensor_network_1d_compress

• add MatrixProductState.gate_with_submpo for applying an MPO acting only of a subset of sites to an MPS

• add MatrixProductOperator.from_dense for constructing MPOs from dense matrices, including an only subset of sites

• add MatrixProductOperator.fill_empty_sites for ‘completing’ an MPO which only has tensors on a subset of sites with (by default) identities

• MatrixProductState and MatrixProductOperator, now support the sites kwarg in common constructors, enabling the TN to act on a subset of the full L sites.

• add TensorNetwork.drape_bond_between for ‘draping’ an existing bond between two tensors through a third

• add Tensor.new_ind_pair_with_identity

• TN2D, TN3D and arbitrary geom classical partition function builders (TN_classical_partition_function_from_edges) now all support outputs= kwarg specifying non-marginalized variables

• add simple dense 1-norm belief propagation algorithm D1BP

• add qtn.enforce_1d_like for checking whether a tensor network is 1D-like, including automatically adding strings of identities between non-local bonds, expanding applicability of tensor_network_1d_compress

• add MatrixProductState.canonicalize as (by default non-inplace) version of canonize, to follow the pattern of other tensor network methods. canonize is now an alias for canonicalize_ [note trailing underscore].

• add MatrixProductState.left_canonicalize as (by default non-inplace) version of left_canonize, to follow the pattern of other tensor network methods. left_canonize is now an alias for left_canonicalize_ [note trailing underscore].

• add MatrixProductState.right_canonicalize as (by default non-inplace) version of right_canonize, to follow the pattern of other tensor network methods. right_canonize is now an alias for right_canonicalize_ [note trailing underscore].

Bug fixes:

• Circuit.apply_gate_raw: fix kwarg bug (PR #226)

• fix for retrieving opt_einsum.PathInfo for single scalar contraction (GH #231)

---

v1.8.0 (2024-04-10)

Breaking Changes

• all singular value renormalization is turned off by default

• TensorNetwork.compress_all now defaults to using some local gauging

Enhancements:

• add quimb.tensor.tn1d.compress.py with functions for compressing generic 1D tensor networks (with arbitrary local structure) using various methods. The methods are:

  • The ‘direct’ method: tensor_network_1d_compress_direct

  • The ‘dm’ (density matrix) method: tensor_network_1d_compress_dm

  • The ‘zipup’ method: tensor_network_1d_compress_zipup

  • The ‘zipup-oversample’ method: tensor_network_1d_compress_zipup_oversample

  • The 1 and 2 site ‘fit’ or sweeping method: tensor_network_1d_compress_fit

  • … and some more niche methods for debugging and testing.

  And can be accessed via the unified function tensor_network_1d_compress. Boundary contraction in 2D can now utilize any of these methods.

• add quimb.tensor.tnag.compress.py with functions for compressing arbitrary geometry tensor networks using various methods. The methods are:

  • The ‘local-early’ method: tensor_network_ag_compress_local_early

  • The ‘local-late’ method: tensor_network_ag_compress_local_late

  • The ‘projector’ method: tensor_network_ag_compress_projector

  • The ‘superorthogonal’ method: tensor_network_ag_compress_superorthogonal

  • The ‘l2bp’ method: tensor_network_ag_compress_l2bp

  And can be accessed via the unified function tensor_network_ag_compress. 1D compression can also fall back to these methods.

• support PBC in tn2d.contract_hotrg, tn2d.contract_ctmrg, tn3d.contract_hotrg and the new function tn3d.contract_ctmrg.

• support PBC in gen_2d_bonds and gen_3d_bonds, with cyclic kwarg.

• support PBC in TN2D_rand_hidden_loop and TN3D_rand_hidden_loop, with cyclic kwarg.

• support PBC in the various base PEPS and PEPO construction methods.

• add tensor_network_apply_op_op for applying ‘operator’ TNs to ‘operator’ TNs.

• tweak tensor_network_apply_op_vec for applying ‘operator’ TNs to ‘vector’ or ‘state’ TNs.

• add tnvec.gate_with_op_lazy method for applying ‘operator’ TNs to ‘vector’ or ‘state’ TNs like \(x \rightarrow A x\).

• add tnop.gate_upper_with_op_lazy method for applying ‘operator’ TNs to the upper indices of ‘operator’ TNs like \(B \rightarrow A B\).

• add tnop.gate_lower_with_op_lazy method for applying ‘operator’ TNs to the lower indices of ‘operator’ TNs like \(B \rightarrow B A\).

• add tnop.gate_sandwich_with_op_lazy method for applying ‘operator’ TNs to the upper and lower indices of ‘operator’ TNs like \(B \rightarrow A B A^\dagger\).

• unify all TN summing routines into `tensor_network_ag_sum, which allows summing any two tensor networks with matching site tags and outer indices, replacing specific MPS, MPO, PEPS, PEPO, etc. summing routines.

• add rand_symmetric_array, rand_tensor_symmetric TN2D_rand_symmetric for generating random symmetric arrays, tensors and 2D tensor networks.

Bug fixes:

• fix scipy sparse monkey patch for scipy>=1.13 (GH #222)

• fix autoblock bug where connected sectors were not being merged (GH #223)

---

v1.7.3 (2024-02-08)

Enhancements:

• qu.randn: support dist="rademacher".

• support dist and other randn options in various TN builders.

Bug fixes:

• restore fallback (to scipy.linalg.svd with driver=’gesvd’) behavior for truncated SVD with numpy backend.

---

v1.7.2 (2024-01-30)

Enhancements:

• add normalized=True option to tensor_network_distance for computing the normalized distance between tensor networks: \(2 |A - B| / (|A| + |B|)\), which is useful for convergence checks. Tensor.distance_normalized and TensorNetwork.distance_normalized added as aliases.

• add TensorNetwork.cut_bond for cutting a bond index

Bug fixes:

• removed import of deprecated numba.generated_jit decorator.

---

v1.7.1 (2024-01-30)

Enhancements:

• add TensorNetwork.visualize_tensors for visualizing the actual data entries of an entire tensor network.

• add ham.build_mpo_propagator_trotterized for building a trotterized propagator from a local 1D hamiltonian. This also includes updates for creating ‘empty’ tensor networks using TensorNetwork.new, and building up gates from empty tensor networks using TensorNetwork.gate_inds_with_tn.

• add more options to Tensor.expand_ind and Tensor.new_ind: repeat tiling mode and random padding mode.

• tensor decomposition: make eigh_truncated backend agnostic.

• tensor_compress_bond: add reduced="left" and reduced="right" modes for when the pair of tensors is already in a canonical form.

• add qtn.TN2D_embedded_classical_ising_partition_function for constructing 2D (triangular) tensor networks representing all-to-all classical ising partition functions.

Bug fixes:

• fix bug in kruas_op when operator spanned multiple subsystems (GH #214)

• fix bug in qr_stabilized when the diagonal of R has significant imaginary parts.

• fix bug in quantum discord computation when the state was diagonal (GH #217)

---

v1.7.0 (2023-12-08)

Breaking Changes

• Circuit : remove target_size in preparation for all contraction specifications to be encapsulated at the contract level (e.g. with cotengra)

• some TN drawing options (mainly arrow options) have changed due to the backend change detailed below.

Enhancements:

• TensorNetwork.draw: use quimb.schematic for main backend="matplotlib" drawing. Enabling:

  1. multi tag coloring for single tensors

  2. arrows and labels on multi-edges

  3. better sizing of tensors using absolute units

  4. neater single tensor drawing, in 2D and 3D

• add quimb.schematic.Drawing from experimental submodule, add example docs at schematic - manual drawing. Add methods text_between, wedge, line_offset and other tweaks for future use by main TN drawing.

• upgrade all contraction to use cotengra as the backend

• Circuit : allow any gate to be controlled by any number of qubits.

• Circuit : support for parsing openqasm2 specifications now with custom and nested gate definitions etc.

• add is_cyclic_x, is_cyclic_y and is_cyclic_z to TensorNetwork2D and TensorNetwork3D.

• add TensorNetwork.compress_all_1d for compressing generic tensor networks that you promise have a 1D topology, without casting as a TensorNetwork1D.

• add MatrixProductState.from_fill_fn for constructing MPS from a function that fills the tensors.

• add Tensor.idxmin and Tensor.idxmax for finding the index of the minimum/maximum element.

• 2D and 3D classical partition function TN builders: allow output indices.

• quimb.tensor.belief_propagation: add various 1-norm/2-norm dense/lazy BP algorithms.

Bug fixes:

• fixed bug where an output index could be removed by squeezing when performing tensor network simplifications.

---

v1.6.0 (2023-09-10)

Breaking Changes

• Quantum circuit RZZ definition corrected (angle changed by -1/2 to match qiskit).

Enhancements:

• add OpenQASM 2.0 parsing support: Circuit.from_openqasm2_file,

• Circuit: add RXX, RYY, CRX, CRY, CRZ, toffoli, fredkin, givens gates

• truncate TN pretty html reprentation to 100 tensors for performance

• add Tensor.sum_reduce and Tensor.vector_reduce

• contract_compressed, default to ‘virtual-tree’ gauge

• add TN_rand_tree

• experimental.operatorbuilder: fix parallel and heisenberg builder

• make parametrized gate generation even more robost (ensure matching types so e.g. tensorflow can be used)

Bug fixes:

• fix gauge size check for some backends

---

v1.5.1 (2023-07-28)

Enhancements:

• add MPS_COPY().

• add ‘density matrix’ and ‘zip-up’ MPO-MPS algorithms.

• add drop_tags option to tensor_contract()

• compress_all_simple(), allow cutoff.

• add structure checking debug methods: Tensor.check() and TensorNetwork.check().

• add several direction contraction utility functions: get_symbol(), inds_to_eq() and array_contract().

Bug fixes:

• Circuit: use stack for more robust parametrized gate generation

• fix for gate_with_auto_swap() for i > j.

• fix bug where calling tn.norm() would mangle indices.

---

v1.5.0 (2023-05-03)

Enhancements

• refactor ‘isometrize’ methods including new “cayley”, “householder” and “torch_householder” methods. See quimb.tensor.decomp.isometrize().

• add compute_reduced_factor() and insert_compressor_between_regions() methos, for some RG style algorithms.

• add the mode="projector" option for 2D tensor network contractions

• add HOTRG style coarse graining and contraction in 2D and 3D. See coarse_grain_hotrg(), contract_hotrg(), coarse_grain_hotrg(), and contract_hotrg(),

• add CTMRG style contraction for 2D tensor networks: contract_ctmrg()

• add 2D tensor network ‘corner double line’ (CDL) builders: TN2D_corner_double_line()

• update the docs to use the furo theme, myst_nb for notebooks, and several other sphinx extensions.

• add the 'adabelief' optimizer to TNOptimizer as well as a quick plotter: plot()

• add initial 3D plotting methods for tensors networks ( TensorNetwork.draw(dim=3, backend='matplotlib3d') or TensorNetwork.draw(dim=3, backend='plotly') ). The new backend='plotly' can also be used for 2D interactive plots.

• Update HTN_from_cnf() to handle more weighted model counting formats.

• Add cnf_file_parse()

• Add random_ksat_instance()

• Add TN_from_strings()

• Add convert_to_2d()

• Add TN2D_rand_hidden_loop()

• Add convert_to_3d()

• Add TN3D_corner_double_line()

• Add TN3D_rand_hidden_loop()

• various optimizations for minimizing computational graph size and construction time.

• add 'lu', 'polar_left' and 'polar_right' methods to tensor_split().

• add experimental arbitrary hamilotonian MPO building

• TensorNetwork: allow empty constructor (i.e. no tensors representing simply the scalar 1)

• drop_tags(): allow all tags to be dropped

• tweaks to compressed contraction and gauging

• add jax, flax and optax example

• add 3D and interactive plotting of tensors networks with via plotly.

• add pygraphiviz layout options

• add combine() for unified handling of combining tensor networks potentially with structure

• add HTML colored pretty printing of tensor networks for notebooks

• add quimb.experimental.cluster_update.py

Bug fixes:

• fix qr_stabilized() bug for strictly upper triangular R factors.

---

v1.4.2 (2022-11-28)

Enhancements

• move from versioneer to to setuptools_scm for versioning

---

v1.4.1 (2022-11-28)

Enhancements

• unify much functionality from 1D, 2D and 3D into general arbitrary geometry class quimb.tensor.tnag.core.TensorNetworkGen

• refactor contraction, allowing using cotengra directly

• add visualize() for visualizing the actual data entries of an arbitrarily high dimensional tensor

• add Gate class for more robust tracking and manipulation of gates in quantum Circuit simulation

• tweak TN drawing style and layout

• tweak default gauging options of compressed contraction

• add compute_hierarchical_grouping()

• add as_network()

• add inds_size()

• add get_hyperinds()

• add outer_size()

• improve group_inds()

• refactor tensor decompositiona and ‘isometrization’ methods

• begin supporting pytree specifications in TNOptimizer, e.g. for constants

• add experimental submodule for new sharing features

• register tensor and tensor network objects with jax pytree interface (PR #150)

• update CI infrastructure

Bug fixes:

• fix force atlas 2 and weight_attr bug (GH #126)

• allow unpickling of PTensor objects (GH #128, PR #131)

---

v1.4.0 (2022-06-14)

Enhancements

• Add 2D tensor network support and algorithms

• Add 3D tensor network infrastructure

• Add arbitrary geometry quantum state infrastructure

• Many changes to TNOptimizer

• Many changes to TN drawing

• Many changes to Circuit simulation

• Many improvements to TN simplification

• Make all tag and index operations deterministic

• Add tensor_network_sum(), tensor_network_distance() and fit()

• Various memory and performance improvements

• Various graph generators and TN builders

---

v1.3.0 (2020-02-18)

Enhancements

• Added time dependent evolutions to Evolution when integrating a pure state - see Time-Dependent Evolutions - as well as supporting LinearOperator defined hamiltonians (PR #40).

• Allow the Evolution callback compute= to optionally access the Hamiltonian (PR #49).

• Added quimb.tensor.tensor_core.Tensor.randomize() and quimb.tensor.tensor_core.TensorNetwork.randomize() to randomize tensor and tensor network entries.

• Automatically squeeze tensor networks when rank-simplifying.

• Add compress_site() for compressing around single sites of MPS etc.

• Add MPS_ghz_state() and MPS_w_state() for building bond dimension 2 open boundary MPS reprentations of those states.

• Various changes in conjunction with autoray to improve the agnostic-ness of tensor network operations with respect to the backend array type.

• Add new_bond() on top of quimb.tensor.tensor_core.Tensor.new_ind() and quimb.tensor.tensor_core.Tensor.expand_ind() for more graph orientated construction of tensor networks, see Graph Orientated Tensor Network Creation.

• Add the fsim() gate.

• Make the parallel number generation functions use new numpy 1.17+ functionality rather than randomgen (which can still be used as the underlying bit generator) (PR #50)

• TN: rename contraction_complexity to contraction_width().

• TN: update quimb.tensor.tensor_core.TensorNetwork.rank_simplify(), to handle hyper-edges.

• TN: add quimb.tensor.tensor_core.TensorNetwork.diagonal_reduce(), to automatically collapse all diagonal tensor axes in a tensor network, introducing hyper edges.

• TN: add quimb.tensor.tensor_core.TensorNetwork.antidiag_gauge(), to automatically flip all anti-diagonal tensor axes in a tensor network allowing subsequent diagonal reduction.

• TN: add quimb.tensor.tensor_core.TensorNetwork.column_reduce(), to automatically identify tensor axes with a single non-zero column, allowing the corresponding index to be cut.

• TN: add quimb.tensor.tensor_core.TensorNetwork.full_simplify(), to iteratively perform all the above simplifications in a specfied order until nothing is left to be done.

• TN: add num_tensors and num_indices attributes, show num_indices in __repr__.

• TN: various improvements to the pytorch optimizer (PR #34)

• TN: add some built-in 1D quantum circuit ansatzes: circ_ansatz_1D_zigzag(), circ_ansatz_1D_brickwork(), and circ_ansatz_1D_rand().

• TN: add parametrized tensors PTensor and so trainable, TN based quantum circuits – see Tensor Network Training of Quantum Circuits.

Bug fixes:

• Fix consistency of fidelity() by making the unsquared version the default for the case when either state is pure, and always return a real number.

• Fix a bug in the 2D system example for when j != 1.0

• Add environment variable QUIMB_NUMBA_PAR to set whether numba should use automatic parallelization - mainly to fix travis segfaults.

• Make cache import and initilization of petsc4py and slepc4py more robust.

---

v1.2.0 (2019-06-06)

Enhancements

• Added kraus_op() for general, noisy quantum operations

• Added projector() for constructing projectors from observables

• Added measure() for measuring and collapsing quantum states

• Added cprint() pretty printing states in computational basis

• Added simulate_counts() for simulating computational basis counts

• TN: Add quimb.tensor.tensor_core.TensorNetwork.rank_simplify()

• TN: Add quimb.tensor.tensor_core.TensorNetwork.isel()

• TN: Add quimb.tensor.tensor_core.TensorNetwork.cut_iter()

• TN: Add 'split-gate' gate mode

• TN: Add TNOptimizer for tensorflow based optimization of arbitrary, contstrained tensor networks.

• TN: Add quimb.tensor.tn1d.core.Dense1D.rand()

• TN: Add connect() to conveniently set a shared index for tensors

• TN: make many more tensor operations agnostic of the array backend (e.g. numpy, cupy, tensorflow, …)

• TN: allow align_TN_1D() to take an MPO as the first argument

• TN: add build_sparse()

• TN: add quimb.tensor.tensor_core.Tensor.unitize() and quimb.tensor.tensor_core.TensorNetwork.unitize() to impose unitary/isometric constraints on tensors specfied using the left_inds kwarg

• Many updates to tensor network quantum circuit (quimb.tensor.circuit.Circuit) simulation including:

  • quimb.tensor.circuit.CircuitMPS

  • quimb.tensor.circuit.CircuitDense

  • 49-qubit depth 30 circuit simulation example Quantum Circuits

• Add from quimb.gates import * as shortcut to import X, Z, CNOT, ....

• Add U_gate() for parametrized arbitrary single qubit unitary

Bug fixes:

• Fix pkron for case len(dims) == len(inds) (GH #17, PR #18).

• Fix qarray printing for older numpy versions

• Fix TN quantum circuit bug where Z and X rotations were swapped

• Fix variable bond MPO building (GH #22) and L=2 DMRG

• Fix norm(X, 'trace') for non-hermitian matrices

• Add autoray as dependency (GH #21)