Netket

Bug Fixes

* Fixed a bug where it was not possible to recompile functions using two identical but different instances of PauliStringJax [1647](https://github.com/netket/netket/pull/1647).
* Fixed a minor bug where chunking was never actually used inside of {meth}`~netket.vqs.MCState.local_estimators`. This will turn on chunking for some other drivers such as {class}`netket.experimental.driver.VMC_SRt` and {class}`netket.experimental.driver.TDVPSchmitt`) [1650](https://github.com/netket/netket/pull/1650).
* {class}`netket.operator.Ising` now throws an error when it is constructed using a non-{class}`netket.hilbert.Spin` hilbert space [1648](https://github.com/netket/netket/pull/1648).

Bug Fixes
* Added support for neural networks with complex parameters to {class}`netket.experimental.driver.VMC_SRt`, which was just crashing with unreadable errors before [1644](https://github.com/netket/netket/pull/1644).

The highlights of this version are a new experimental driver to optimise networks with millions of parameters using SR, and introduces new utility functions to convert a pyscf molecule to a netket Hamiltonian.

Read below for a more detailed changelog

New Features

* Added new {class}`netket.experimental.driver.VMC_SRt` driver, which leads in identical parameter updates as the standard Stochastic Reconfiguration with diagonal shift regularization. Therefore, it is essentially equivalent to using the standard {class}`netket.driver.VMC` with the {class}`netket.optimizer.SR` preconditioner. The advantage of this method is that it requires the inversion of a matrix with side number of samples instead of number of parameters, making this formulation particularly useful in typical deep learning scenarios [1623](https://github.com/netket/netket/pull/1623).
* Added a new function {func}`netket.experimental.operator.from_pyscf_molecule` to construct the electronic hamiltonian of a given molecule specified through pyscf. This is accompanied by {func}`netket.experimental.operator.pyscf.TV_from_pyscf_molecule` to compute the T and V tensors of a pyscf molecule [1602](https://github.com/netket/netket/pull/1602).
* Added the operator computing the Rényi2 entanglement entropy on Hilbert spaces with discrete dofs [1591](https://github.com/netket/netket/pull/1591).
* It is now possible to disable netket's double precision default activation and force all calculations to be performed using single precision by setting the environment variable/configuration flag `NETKET_ENABLE_X64=0`, which also sets `JAX_ENABLE_X64=0`. When running with this flag, the number of warnings printed by jax is considerably reduced as well [1544](https://github.com/netket/netket/pull/1544).
* Added new shortcuts to build the identity operator as {func}`netket.operator.spin.identity` and {func}`netket.operator.boson.identity` [1601](https://github.com/netket/netket/pull/1601).
* Added new {class}`netket.hilbert.Particle` constructor that only takes as input the number of dimensions of the system [1577](https://github.com/netket/netket/pull/1577).
* Added new {class}`netket.experimental.models.Slater2nd` model implementing a Slater ansatz [1622](https://github.com/netket/netket/pull/1622).
* Added new {func}`netket.jax.logdet_cmplx` function to compute the complex log-determinant of a batch of matrices [1622](https://github.com/netket/netket/pull/1622).

Breaking changes

* {class}`netket.experimental.hilbert.SpinOrbitalFermions` attributes have been changed: {attr}`~netket.experimental.hilbert.SpinOrbitalFermions.n_fermions` now always returns an integer with the total number of fermions in the system (if specified). A new attribute {attr}`~netket.experimental.hilbert.SpinOrbitalFermions.n_fermions_per_spin` has been introduced that returns the same tuple of fermion number per spin subsector as before. A few fields are now marked as read-only as modifications where ignored [1622](https://github.com/netket/netket/pull/1622).
* The {class}`netket.nn.blocks.SymmExpSum` layer is now normalised by the number of elements in the symmetry group in order to maintain a reasonable normalisation [1624](https://github.com/netket/netket/pull/1624).
* The labelling of spin sectors in {func}`netket.experimental.operator.fermion.create` and similar operators has now changed from the eigenvalue of the spin operator ({math}`\pm 1/2` and so on) to the eigenvalue of the Pauli matrices ({math}`\pm 1` and so on) [1637](https://github.com/netket/netket/pull/1637).
* The connected elements and expectation values of all non-simmetric fermionic operators is now changed in order to be correct [1640](https://github.com/netket/netket/pull/1640).

Improvements

* Considerably reduced the memory consumption of {class}`~netket.operator.LocalOperator`, especially in the case of large local hilbert spaces. Also leveraged sparsity in the terms to speed up compilation (`_setup`) in the same cases [1558](https://github.com/netket/netket/pull/1558).
* {class}`netket.nn.blocks.SymmExpSum` now works with inputs of arbitrary dimensions, while previously it errored for all inputs that were not 2D [1616](https://github.com/netket/netket/pull/1616)
* Stop using `FrozenDict` from `flax` and instead return standard dictionaries for the variational parameters from the variational state. This makes it much easier to edit parameters [1547](https://github.com/netket/netket/pull/1547).
* Vastly improved, finally readable documentation of all Flax modules and neural network architectures [1641](https://github.com/netket/netket/pull/1641).

Bug Fixes

* Fixed minor bug where {class}`netket.operator.LocalOperator` could not be built with `np.matrix` object obtained by converting scipy sparse matrices to dense [1597](https://github.com/netket/netket/pull/1597).
* Raise correct error instead of unintelligible one when multiplying {class}`netket.experimental.operator.FermionOperator2nd` with other operators [1599](https://github.com/netket/netket/pull/1599).
* Do not rescale the output of {func}`netket.jax.jacobian` by the square root of number of samples. Previously, when specifying `center=True` we were incorrectly rescaling the output [1614](https://github.com/netket/netket/pull/1614).
* Fix bug in {class}`netket.operator.PauliStrings` that caused the dtype to get out of sync with the dtype of the internal arrays, causing errors when manipulating them symbolically [1619](https://github.com/netket/netket/pull/1619).
* Fix bug that prevented the use of {class}`netket.operator.DiscreteJaxOperator` as observables with all drivers [1625](https://github.com/netket/netket/pull/1625).
* Fermionic operator `get_conn` method was returning values as if the operator was transposed, and has now been fixed. This will break the expectation value of non-simmetric fermionic operators, but hopefully nobody was looking into them [1640](https://github.com/netket/netket/pull/1640).

This release requires at least Python 3.9 and Jax 0.4.

Bug Fixes

* Fix a bug introduced in version 3.9 for {class}`netket.experimental.driver.TDVPSchmitt` which resulted in the wrong dynamics [1551](https://github.com/netket/netket/pull/1551).

Bug Fixes

* Fix a bug in the construction of {class}`netket.operator.PauliStringsJax` in some cases [1539](https://github.com/netket/netket/pull/1539).

This release requires Python 3.8 and Jax 0.4.

New Features
* {class}`netket.callbacks.EarlyStopping` now supports relative tolerances for determining when to stop [1481](https://github.com/netket/netket/pull/1481).
* {class}`netket.callbacks.ConvergenceStopping` has been added, which can stop a driver when the loss function reaches a certain threshold [1481](https://github.com/netket/netket/pull/1481).
* A new base class {class}`netket.operator.DiscreteJaxOperator` has been added, which will be used as a base class for a set of operators that are jax-compatible [1506](https://github.com/netket/netket/pull/1506).
* {func}`netket.sampler.rules.HamiltonianRule` has been split into two implementations, {class}`netket.sampler.rules.HamiltonianRuleJax` and {class}`netket.sampler.rules.HamiltonianRuleNumba`, which are to be used for {class}`~netket.operator.DiscreteJaxOperator` and standard numba-based {class}`~netket.operator.DiscreteOperator`s. The user-facing API is unchanged, but the returned type might now depend on the input operator [1514](https://github.com/netket/netket/pull/1514).
* {class}`netket.operator.PauliStringsJax` is a new operator that behaves as {class}`netket.operator.PauliStrings` but is Jax-compatible, meaning that it can be used inside of jax-jitted contexts and works better with chunking. It can also be constructed starting from a standard Ising operator by calling `operator.to_jax_operator()` [1506](https://github.com/netket/netket/pull/1506).
* {class}`netket.operator.IsingJax` is a new operator that behaves as `netket.operator.Ising` but is Jax-compatible, meaning that it can be used inside of jax-jitted contexts and works better with chunking. It can also be constructed starting from a standard Ising operator by calling `operator.to_jax_operator()` [1506](https://github.com/netket/netket/pull/1506).
* Added a new method {meth}`netket.operator.LocalOperator.to_pauli_strings` to convert {class}`netket.operator.LocalOperator` to {class}`netket.operator.PauliStrings`. As PauliStrings can be converted to Jax-operators, this now allows to convert arbitrary operators to Jax-compatible ones [1515](https://github.com/netket/netket/pull/1515).
* The constructor of {meth}`~netket.optimizer.qgt.QGTOnTheFly` now takes an optional boolean argument `holomorphic : Optional[bool]` in line with the other geometric tensor implementations. This flag does not affect the computation algorithm, but will be used to raise an error if the user attempts to call {meth}`~netket.optimizer.qgt.QGTOnTheFly.to_dense()` with a non-holomorphic ansatz. While this might break past code, the numerical results were incorrect.

Breaking Changes
* The first two axes in the output of the samplers have been swapped, samples are now of shape `(n_chains, n_samples_per_chain, ...)` consistent with `netket.stats.statistics`. Custom samplers need to be updated to return arrays of shape `(n_chains, n_samples_per_chain, ...)` instead of `(n_samples_per_chain, n_chains, ...)`. [1502](https://github.com/netket/netket/pull/1502)
* The tolerance arguments of {class}`~netket.experimental.dynamics.TDVPSchmitt` have all been renamed to more understandable quantities without inspecting the source code. In particular, `num_tol` has been renamed to `rcond`, `svd_tol` to `rcond_smooth` and `noise_tol` to `noise_atol`.

Deprecations
* `netket.vqs.ExactState` has been renamed to {class}`netket.vqs.FullSumState` to better reflect what it does. Using the old name will now raise a warning [1477](https://github.com/netket/netket/pull/1477).


Known Issues
* The new `Jax`-friendly operators do not work with {class}`netket.vqs.FullSumState` because they are not hashable. This will be fixed in a minor patch (coming soon).