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Release Notes
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=========================
cuQuantum Python v22.07.1
=========================

* Bugs fixed:

  * The 22.07.0 ``cuquantum`` wheel had a wrong file layout. (If you are using the ``cuqauntum`` 22.07.0.1 or 22.07.0.2 hot-fix wheel, they will work fine.)

=========================
cuQuantum Python v22.07.0
=========================

* Add new APIs and functionalities:

  * For low-level APIs, please refer to the release notes of :ref:`cuStateVec v1.1.0 <custatevec/release_notes:cuStateVec v1.1.0>`
    and :ref:`cuTensorNet v1.1.0 <cutensornet/release_notes:cuTensorNet v1.1.0>`.
  * New high-level API :class:`cuquantum.CircuitToEinsum` that supports conversion of :class:`qiskit.QuantumCircuit` and :class:`cirq.Circuit` to tensor network contraction:

    - Support state coefficient
    - Support bitstring amplitude
    - Support reduced density matrix
    - Backend support on NumPy, CuPy and PyTorch

  * Add a keyword-only argument ``slices`` to the :meth:`cuquantum.Network.contract` method to support contracting an arbitrary subset of the slices.
  * Add a new attribute ``intermediate_modes`` to the :class:`cuquantum.OptimizerInfo` object for retrieving the mode labels of all intermediate tensors.
  * Add a new attribute ``num_slices`` to the :class:`cuquantum.OptimizerInfo` object for querying the total number of slices.

* Functionality/performance improvements:

  * Improve the einsum expression parser.

* Bugs fixed:

  * An exception mistakenly raised in :func:`cuquantum.einsum` when ``optimize`` is set to `False`.
  * Missing f-specifier in the string representation of :class:`cuquantum.OptimizerInfo`.

* Other changes:

  * Drop the dependency on ``typing_extensions``.
  * Provide distributed (MPI-based) Python samples that show how easy it is to use cuTensorNet and create parallelism. ``mpi4py`` is required for running these samples.
  * Update the low-level, non-distributed sample ``tensornet_example.py`` by improving memory usage and switching to the new contraction API :func:`~cuquantum.cutensornet.contract_slices`.
  * Provide Jupyter notebooks to show how to convert a quantum circuit to a tensor network contraction.
  * Add a Python sample to illustrate the usage of the new multi-device bit-swapping :func:`~cuquantum.custatevec.multi_device_swap_index_bits` API.
  * Restructure the ``samples`` folder to separate cuStateVec and cuTensorNet samples.

*Compatibility notes*:

* cuQuantum Python now requires cuQuantum v22.07.
* cuQuantum Python now requires Python 3.8+.
* cuQuantum Python now requires NumPy v1.19+.
* cuQuantum Python supports Cirq v0.6.0+.
* cuQuantum Python supports Qiskit v0.24.0+.

=========================
cuQuantum Python v22.05.0
=========================

* Bugs fixed:

  * Make ``typing_extensions`` a required dependency (`NVIDIA/cuQuantum#3 <https://github.com/NVIDIA/cuQuantum/issues/3>`_)
  * Fix issues in the test suite

* Other changes:

  * The Python sample (`python/samples/tensornet_example.py <https://github.com/NVIDIA/cuQuantum/blob/main/python/samples/cutensornet/tensornet_example.py>`_) is updated to include a correctness check

=========================
cuQuantum Python v22.03.0
=========================

* Stable release:

  * Starting this release, cuQuantum Python switches to the CalVer versioning scheme, following cuQuantum SDK
  * ``pip`` wheels are released on PyPI: ``pip install cuquantum-python``

* Functionality/performance improvements:

  * High-level tensor network APIs are now fully NumPy compliant:

    - Support generalized einsum expressions
    - Support ellipsis
    - Support broadcasting

* Add new APIs and functionalities for:

  * For low-level APIs, please refer to the release notes of :ref:`cuStateVec v1.0.0 <custatevec/release_notes:cuStateVec v1.0.0>`
    and :ref:`cuTensorNet v1.0.0 <cutensornet/release_notes:cuTensorNet v1.0.0>`.
  * The high-level APIs support an EMM-like memory plugin interface (see :ref:`high-level memory management`).

* API changes:

  * For low-level APIs, please refer to the release notes of :ref:`cuStateVec v1.0.0 <custatevec/release_notes:cuStateVec v1.0.0>`
    and :ref:`cuTensorNet v1.0.0 <cutensornet/release_notes:cuTensorNet v1.0.0>`.
  * No API breaking changes for the high-level APIs.

*Compatibility notes*:

* cuQuantum Python requires cuQuantum v22.03
* cuQuantum Python requires Python 3.7+

  - In the next release, Python 3.7 will be dropped to follow `NEP-29`_.

* cuQuantum Python requires NumPy v1.17+

  - In the next release, NumPy 1.17 & 1.18 will be dropped to follow `NEP-29`_.

* cuQuantum Python requires CuPy v9.5+
* cuQuantum Python supports PyTorch v1.10+

.. _NEP-29: https://numpy.org/neps/nep-0029-deprecation_policy.html

*Known issues*:

* If you install cuQuantum Python from PyPI (``pip install cuquantum-python``), make sure you also install ``typing_extensions`` (via ``pip`` or ``conda``). This only affects the wheel installation and will be fixed in the next release. (`NVIDIA/cuQuantum#3 <https://github.com/NVIDIA/cuQuantum/issues/3>`_)

=========================
cuQuantum Python v0.1.0.1
=========================

* Patch release:

  - Add a ``__version__`` string

=========================
cuQuantum Python v0.1.0.0
=========================

* Initial release (beta 2)

*Compatibility notes*:

* cuQuantum Python requires cuQuantum v0.1.0
* cuQuantum Python requires NumPy v1.17+
* cuQuantum Python requires CuPy v9.5+
* cuQuantum Python supports PyTorch v1.10+

*Limitation notes*:

* In certain environments, if PyTorch is installed ``import cuquantum`` could fail (with a segmentation fault). It is currently under investigation and a temporary workaround is to import ``torch`` before importing ``cuquantum``.