quimb

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, more docs here: https://quimb.readthedocs.io/en/latest/tensor-circuit-mps.html
• 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 (https://github.com/jcmgray/quimb/issues/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 (https://github.com/jcmgray/quimb/pull/226) by @juliendrapeau
• fix for retrieving opt_einsum.PathInfo for single scalar contraction (https://github.com/jcmgray/quimb/issues/231).

New Contributors

• @juliendrapeau made their first contribution in https://github.com/jcmgray/quimb/pull/226

Full Changelog: https://github.com/jcmgray/quimb/compare/v1.8.0...v1.8.1

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.tensor_1d_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-first' method: tensor_network_1d_compress_zipup_first
  • 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.tensor_arbgeom_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 (#222)
• fix autoblock bug where connected sectors were not being merged (#223)

Full Changelog: https://github.com/jcmgray/quimb/compare/v1.7.3...v1.8.0

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.

Full Changelog: https://github.com/jcmgray/quimb/compare/v1.7.2...v1.7.3

Bug fixes:

• removed import of deprecated numba.generated_jit decorator.

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

Full Changelog: https://github.com/jcmgray/quimb/compare/v1.7.1...v1.7.2

What's Changed

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 (#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 (#217)
• Fix empty lines in dimacs by @jjcmoon in https://github.com/jcmgray/quimb/pull/215

New Contributors

• @jjcmoon made their first contribution in https://github.com/jcmgray/quimb/pull/215

Full Changelog: https://github.com/jcmgray/quimb/compare/v1.7.0...v1.7.1

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:

Multi tag drawing support:

• 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. 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.experimental.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.

• Fix deprecation warnings by @king-p3nguin in https://github.com/jcmgray/quimb/pull/209

New Contributors

• @king-p3nguin made their first contribution in https://github.com/jcmgray/quimb/pull/209

Full Changelog: https://github.com/jcmgray/quimb/compare/v1.6.0...v1.7.0

Breaking Changes

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

Enhancements:

• add OpenQASM 2.0 parsing support: :meth:Circuit.from_openqasm2_file
• :class:Circuit: add RXX, RYY, CRX, CRY, CRZ, toffoli, fredkin, givens gates
• truncate TN pretty html reprentation to 100 tensors for performance
• add :meth:Tensor.sum_reduce and :meth:Tensor.vector_reduce
• :meth:contract_compressed, default to 'virtual-tree' gauge
• add :func: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

Full Changelog: https://github.com/jcmgray/quimb/compare/v1.5.1...v1.6.0

• add various MPO-MPS gate methods, including zip-up and density matrix, in the experimental submodule
• some PTensor refactoring
• Circuit: more robust parametrized gate generation
• various new contraction convenience interfaces (incld. array_contract)
• add Tensor.check() and TensorNetwork.check() for diagnostics
• add TensorNetwork.isconnected(), TensorNetwork.istree()

Full Changelog: https://github.com/jcmgray/quimb/compare/v1.5.0...v1.5.1

Enhancements

• refactor 'isometrize' methods including new "cayley", "householder" and
  "torch_householder" methods. See :func:quimb.tensor.decomp.isometrize.
• add :meth:~quimb.tensor.tensor_core.TensorNetwork.compute_reduced_factor
  and :meth:~quimb.tensor.tensor_core.TensorNetwork.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
  :meth:~quimb.tensor.tensor_2d.TensorNetwork2D.coarse_grain_hotrg,
  :meth:~quimb.tensor.tensor_2d.TensorNetwork2D.contract_hotrg,
  :meth:~quimb.tensor.tensor_3d.TensorNetwork3D.coarse_grain_hotrg, and
  :meth:~quimb.tensor.tensor_3d.TensorNetwork3D.contract_hotrg,
• add CTMRG style contraction for 2D tensor networks:
  :meth:~quimb.tensor.tensor_2d.TensorNetwork2D.contract_ctmrg
• add 2D tensor network 'corner double line' (CDL) builders:
  :func:~quimb.tensor.tensor_builder.TN2D_corner_double_line
• update the docs to use the furo <https://pradyunsg.me/furo/>_ theme,
  myst_nb <https://myst-nb.readthedocs.io/en/latest/>_ for notebooks, and
  several other sphinx extensions.
• add the 'adabelief' optimizer to
  :class:~quimb.tensor.optimize.TNOptimizer as well as a quick plotter:
  :meth:~quimb.tensor.optimize.TNOptimizer.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 :func:~quimb.tensor.tensor_builder.HTN_from_cnf to handle more
  weighted model counting formats.
• Add :func:~quimb.tensor.tensor_builder.cnf_file_parse
• Add :func:~quimb.tensor.tensor_builder.random_ksat_instance
• Add :func:~quimb.tensor.tensor_builder.TN_from_strings
• Add :func:~quimb.tensor.tensor_builder.convert_to_2d
• Add :func:~quimb.tensor.tensor_builder.TN2D_rand_hidden_loop
• Add :func:~quimb.tensor.tensor_builder.convert_to_3d
• Add :func:~quimb.tensor.tensor_builder.TN3D_corner_double_line
• Add :func:~quimb.tensor.tensor_builder.TN3D_rand_hidden_loop
• various optimizations for minimizing computational graph size and
  construction time.
• add 'lu', 'polar_left' and 'polar_right' methods to
  :func:~quimb.tensor.tensor_core.tensor_split.
• add experimental arbitrary hamilotonian MPO building
• :class:~quimb.tensor.tensor_core.TensorNetwork: allow empty constructor
  (i.e. no tensors representing simply the scalar 1)
• :meth:~quimb.tensor.tensor_core.TensorNetwork.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 :meth:~quimb.tensor.tensor_core.TensorNetwork.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 :func:~quimb.tensor.decomp.qr_stabilized bug for strictly upper
  triangular R factors.

Full Changelog: https://github.com/jcmgray/quimb/compare/1.4.2...v1.5.0

Add automatic building and publishing of quimb to pypi.

Enhancements

• unify much functionality from 1D, 2D and 3D into general arbitrary geometry
  class :class:quimb.tensor.tensor_arbgeom.TensorNetworkGen
• refactor contraction, allowing using cotengra directly
• add :meth:~quimb.tensor.tensor_core.Tensor.visualize for visualizing the
  actual data entries of an arbitrarily high dimensional tensor
• add :class:~quimb.tensor.circuit.Gate class for more robust tracking and
  manipulation of gates in quantum :class:~quimb.tensor.circuit.Circuit
  simulation
• tweak TN drawing style and layout
• tweak default gauging options of compressed contraction
• add :meth:~quimb.tensor.tensor_core.TensorNetwork.compute_hierarchical_grouping
• add :meth:~quimb.tensor.tensor_core.Tensor.as_network
• add :meth:~quimb.tensor.tensor_core.TensorNetwork.inds_size
• add :meth:~quimb.tensor.tensor_core.TensorNetwork.get_hyperinds
• add :meth:~quimb.tensor.tensor_core.TensorNetwork.outer_size
• improve :meth:~quimb.tensor.tensor_core.TensorNetwork.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
  (:pull:150)
• update CI infrastructure

Bug fixes:

• fix force atlas 2 and weight_attr bug (:issue:126)
• allow unpickling of PTensor objects (:issue:128, :pull:131)

Enhancements

• Add 2D tensor network support and algorithms
• Add 3D tensor network infrastructure
• Add arbitrary geometry quantum state infrastructure
• Many changes to :class:TNOptimizer
• Many changes to TN drawing
• Many changes to :class:Circuit simulation
• Many improvements to TN simplification
• Make all tag and index operations deterministic
• Add :func:~quimb.tensor.tensor_core.tensor_network_sum,
  :func:~quimb.tensor.tensor_core.tensor_network_distance and
  :meth:~quimb.tensor.tensor_core.TensorNetwork.fit
• Various memory and performance improvements
• Various graph generators and TN builders

Enhancements

• Added time dependent evolutions to :class:~quimb.evo.Evolution when integrating a pure state - see :ref:time-dependent-evolution - as well as supporting LinearOperator defined hamiltonians (:pull:40).
• Allow the :class:~quimb.evo.Evolution callback compute= to optionally access the Hamiltonian (:pull:49).
• Added :meth:quimb.tensor.tensor_core.Tensor.randomize and :meth:quimb.tensor.tensor_core.TensorNetwork.randomize to randomize tensor and tensor network entries.
• Automatically squeeze tensor networks when rank-simplifying.
• Add :meth:~quimb.tensor.tensor_1d.TensorNetwork1DFlat.compress_site for compressing around single sites of MPS etc.
• Add :func:~quimb.tensor.tensor_gen.MPS_ghz_state and :func:~quimb.tensor.tensor_gen.MPS_w_state for building bond dimension 2 open boundary MPS reprentations of those states.
• Various changes in conjunction with autoray <https://github.com/jcmgray/autoray>_ to improve the agnostic-ness of tensor network operations with respect to the backend array type.
• Add :func:~quimb.tensor.tensor_core.new_bond on top of :meth:quimb.tensor.tensor_core.Tensor.new_ind and :meth:quimb.tensor.tensor_core.Tensor.expand_ind for more graph orientated construction of tensor networks, see :ref:tn-creation-graph-style.
• Add the :func:~quimb.gen.operators.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) (:pull:50)
• TN: rename contraction_complexity to :meth:~quimb.tensor.tensor_core.TensorNetwork.contraction_width.
• TN: update :meth:quimb.tensor.tensor_core.TensorNetwork.rank_simplify, to handle hyper-edges.
• TN: add :meth:quimb.tensor.tensor_core.TensorNetwork.diagonal_reduce, to automatically collapse all diagonal tensor axes in a tensor network, introducing hyper edges.
• TN: add :meth: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 :meth: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 :meth: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 (:pull:34)
• TN: add some built-in 1D quantum circuit ansatzes:
  :func:~quimb.tensor.circuit_gen.circ_ansatz_1D_zigzag,
  :func:~quimb.tensor.circuit_gen.circ_ansatz_1D_brickwork, and
  :func:~quimb.tensor.circuit_gen.circ_ansatz_1D_rand.
• TN: add parametrized tensors :class:~quimb.tensor.tensor_core.PTensor and so trainable, TN based quantum circuits -- see :ref:example-tn-training-circuits.

Bug fixes:

• Fix consistency of :func:~quimb.calc.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.

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 TensorNetwork.rank_simplify

• TN: Add TensorNetwork.isel

• TN: Add TensorNetwork.cut_iter

• TN: Add 'split-gate' gate mode

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

• TN: Add Dense1D.rand

• TN: Add tensor_core.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 tensor_1d.align_TN_1D to take an MPO as the first argument

• TN: add SpinHam.build_sparse

• TN: add Tensor.unitize and TensorNetwork.unitize to impose unitary/isometric constraints on tensors specified using the left_inds kwarg

• Many updates to tensor network quantum circuit simulation including:

  • CircuitMPS
  • CircuitDense
  • 49-qubit depth 30 circuit simulation example https://quimb.readthedocs.io/en/latest/examples/ex_quantum_circuit.html

• 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) (#17, #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 (#22) and L=2 DMRG
• Fix norm(X, 'trace') for non-hermitian matrices
• Add autoray as dependency (#21)