changelog.md

Changelog

Release notes for quimb.

(whats-new-1-7-2)=

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.

(whats-new-1-7-1)=

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 ({issue}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 ({issue}217)

(whats-new-1-7-0)=

v1.7.0 (2023-12-08)

Breaking Changes

• {class}~quimb.tensor.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 {ref}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.

(whats-new-1-6-0)=

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

(whats-new-1-5-1)=

v1.5.1 (2023-07-28)

Enhancements:

• add {func}~quimb.tensor.tensor_builder.MPS_COPY.
• add 'density matrix' and 'zip-up' MPO-MPS algorithms.
• add drop_tags option to {meth}~quimb.tensor.tensor_contract
• {meth}compress_all_simple, allow cutoff.
• add structure checking debug methods: {meth}Tensor.check and {meth}TensorNetwork.check.
• add several direction contraction utility functions: {func}get_symbol, {func}inds_to_eq and {func}array_contract.

Bug fixes:

• {class}Circuit: use stack for more robust parametrized gate generation
• fix for {meth}gate_with_auto_swap for i > j.
• fix bug where calling tn.norm() would mangle indices.

(whats-new-1-5-0)=

v1.5.0 (2023-05-03)

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 theme, myst_nb 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.

(whats-new-1-4-2)=

v1.4.2 (2022-11-28)

Enhancements

• move from versioneer to to setuptools_scm for versioning

(whats-new-1-4-1)=

v1.4.1 (2022-11-28)

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)

(whats-new-1-4-0)=

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 {class}~quimb.tensor.optimize.TNOptimizer
• Many changes to TN drawing
• Many changes to {class}~quimb.tensor.circuit.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

(whats-new-1-3-0)=

v1.3.0 (2020-02-18)

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_builder.MPS_ghz_state and {func}~quimb.tensor.tensor_builder.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 {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.

(whats-new-1-2-0)=

v1.2.0 (2019-06-06)

Enhancements

• Added {func}~quimb.calc.kraus_op for general, noisy quantum operations

• Added {func}~quimb.calc.projector for constructing projectors from observables

• Added {func}~quimb.calc.measure for measuring and collapsing quantum states

• Added {func}~quimb.calc.cprint pretty printing states in computational basis

• Added {func}~quimb.calc.simulate_counts for simulating computational basis counts

• TN: Add {meth}quimb.tensor.tensor_core.TensorNetwork.rank_simplify

• TN: Add {meth}quimb.tensor.tensor_core.TensorNetwork.isel

• TN: Add {meth}quimb.tensor.tensor_core.TensorNetwork.cut_iter

• TN: Add 'split-gate' gate mode

• TN: Add {class}~quimb.tensor.optimize_tensorflow.TNOptimizer for tensorflow based optimization of arbitrary, contstrained tensor networks.

• TN: Add {meth}quimb.tensor.tensor_1d.Dense1D.rand

• TN: Add {func}~quimb.tensor.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 {func}~quimb.tensor.tensor_1d.align_TN_1D to take an MPO as the first argument

• TN: add {meth}~quimb.tensor.tensor_builder.SpinHam1D.build_sparse

• TN: add {meth}quimb.tensor.tensor_core.Tensor.unitize and {meth}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 ({class}quimb.tensor.circuit.Circuit) simulation including:

  • {class}quimb.tensor.circuit.CircuitMPS
  • {class}quimb.tensor.circuit.CircuitDense
  • 49-qubit depth 30 circuit simulation example {ref}quantum-circuit-example

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

• Add {func}~quimb.gen.operators.U_gate for parametrized arbitrary single qubit unitary

Bug fixes:

• Fix pkron for case len(dims) == len(inds) ({issue}17, {pull}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 ({issue}22) and L=2 DMRG
• Fix norm(X, 'trace') for non-hermitian matrices
• Add autoray as dependency ({issue}21)