This release supports Python 3.12 through the latest release of Numba, introduces several new jax-compatible operators and adds a new experimental way to distribute calculations among multiple GPUs without using MPI.
We have a few breaking changes as well: deprecations that were issued more than 18 months ago have now been finalized, most notable the `dtype` argument to several models and layers, some keywords to GCNN and setting the number of chains of exact samplers.
New Features
* Recurrent neural networks and layers have been added to `nkx.models` and `nkx.nn` [1305](https://github.com/netket/netket/pull/1305).
* Added experimental support for running NetKet on multiple jax devices (as an alternative to MPI). It is enabled by setting the environment variable/configuration flag `NETKET_EXPERIMENTAL_SHARDING=1`. Parallelization is achieved by distributing the Markov chains / samples equally across all available devices utilizing [`jax.Array` sharding](https://jax.readthedocs.io/en/latest/notebooks/Distributed_arrays_and_automatic_parallelization.html). On GPU multi-node setups are supported via [jax.distribued](https://jax.readthedocs.io/en/latest/multi_process.html), whereas on CPU it is limited to a single process but several threads can be used by setting `XLA_FLAGS='--xla_force_host_platform_device_count=XX'` [#1511](https://github.com/netket/netket/pull/1511).
* {class}`netket.experimental.operator.FermionOperator2nd` is a new Jax-compatible implementation of fermionic operators. It can also be constructed starting from a standard fermionic operator by calling `operator.to_jax_operator()`, or used in combination with `pyscf` converters[1675](https://github.com/netket/netket/pull/1675),[#1684](https://github.com/netket/netket/pull/1684).
* {class}`netket.operator.LocalOperatorJax` is a new Jax-compatible implementation of local operators. It can also be constructed starting from a standard operator by calling `operator.to_jax_operator()` [1654](https://github.com/netket/netket/pull/1654).
* The logger interface has been formalised and documented in the abstract base class {class}`netket.logging.AbstractLog` [1665](https://github.com/netket/netket/pull/1665).
* The {class}`~netket.experimental.sampler.ParticleExchange` sampler and corresponding rule {class}`~netket.experimental.sampler.rules.ParticleExchangeRule` has been added, which special cases {class}`~netket.sampler.ExchangeSampler` to fermionic spaces in order to avoid proposing moves where the two site exchanged have the same population [1683](https://github.com/netket/netket/issues/1683).
Breaking Changes
* The {class}`netket.models.Jastrow` wave-function now only has {math}`N (N-1)` variational parameters, instead of the {math}`N^2` redundant ones it had before. Saving and loading format has now changed and won't be compatible with previous versions[1664](https://github.com/netket/netket/pull/1664).
* Finalize deprecations of some old methods in `nk.sampler` namespace (see original commit [1f77ad8267e16fe8b2b2641d1d48a0e7ae94832e](https://github.com/netket/netket/commit/1f77ad8267e16fe8b2b2641d1d48a0e7ae94832e))
* Finalize deprecations of 2D input to DenseSymm layers, which now turn into error and `extra_bias` option of Equivariant Networks/GCNNs (see original commit [c61ea542e9d0f3e899d87a7471dea96d4f6b152d](https://github.com/netket/netket/commit/c61ea542e9d0f3e899d87a7471dea96d4f6b152d))
* Finalize deprecations of very old input/properties to Lattices [0f6f520da9cb6afcd2361dd6fd029e7ad6a2693e](https://github.com/netket/netket/commit/0f6f520da9cb6afcd2361dd6fd029e7ad6a2693e))
* Finalie the deprecation for `dtype=` attribute of several modules in `nk.nn` and `nk.models`, which has been printing an error since April 2022. You should update usages of `dtype=` to `param_dtype=` [1724](https://github.com/netket/netket/issues/1724)
Deprecations
* `MetropolisSampler.n_sweeps` has been renamed to {attr}`~netket.sampler.MetropolisSampler.MetropolisSampler.sweep_size` for clarity. Using `n_sweeps` when constructing the sampler now throws a deprecation warning; `sweep_size` should be used instead going forward [1657](https://github.com/netket/netket/issues/1657).
* Samplers and metropolis rules defined as {func}`netket.utils.struct.dataclass` are deprecated because the base class is now a {class}`netket.utils.struct.Pytree`. The only change needed is to remove the dataclass decorator and define a standard init method [1653](https://github.com/netket/netket/issues/1653).
* The `out` keyword of Discrete Hilbert indexing methods (`all_states`, `numbers_to_states` and `states_to_numbers`) is deprecated and will be removed in the next release. Plan ahead and remove usages to avoid breaking your code 3 months from now [1725](https://github.com/netket/netket/issues/1725)!
Internal changes
* A new class {class}`netket.utils.struct.Pytree`, can be used to create Pytrees for which inheritance autoamtically works and for which it is possible to define `__init__`. Several structures such as samplers and rules have been transitioned to this new interface instead of old style `struct.dataclass` [1653](https://github.com/netket/netket/issues/1653).
* The {class}`~netket.experimental.operator.FermionOperator2nd` and related classes now store the constant diagonal shift as another term instead of a completely special cased scalar value. The same operators now also respect the `cutoff` keyword argument more strictly [1686](https://github.com/netket/netket/issues/1686).
* Dtypes of the matrix elements of operators are now handled more correctly, and fewer warnings are raised when running NetKet in X32 mode. Moreover, operators like Ising now default to floating point dtype even if the coefficients are integers [1697](https://github.com/netket/netket/issues/1697).
Bug Fixes
* Support multiplication of Discrete Operators by Sparse arrays [1661](https://github.com/netket/netket/issues/1661).