Quimb

**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.

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**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.

---


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

**Enhancements**

- move from versioneer to to
[setuptools_scm](https://pypi.org/project/setuptools-scm/) for versioning

---


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

**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`)

---


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**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

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

**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](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.

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