neuralqx.vqs.mc package

check_hilbert(A, B)
get_local_kernel_arguments(vstate, Ô)

Returns the samples of vstate used to compute the expectation value of the operator O, and the connected elements and matrix elements.

Parameters:

  • vstate (Any) – the variational state

  • Ô – the operator

Returns:

A Tuple with 2 elements (sigma, args), where the first elements should be the samples over which the classical expectation value should be computed, while the latter is anything that can be fed as input to the local_kernel.

get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._lazy.Squared)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator.DiscreteOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._continuous_operator.ContinuousOperator)
get_local_kernel_arguments(vs: netket.vqs.mc.mc_state.state.MCState, O: netket.operator._sum.operator.SumGenericOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._discrete_operator.DiscreteOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._abstract_super_operator.AbstractSuperOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._lazy.Squared[netket.operator._abstract_super_operator.AbstractSuperOperator])
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators._lazy.PenaltyCost)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._lazy.Squared)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator.DiscreteOperator | neuralqx.operators.types._discrete_operator.DiscreteOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._continuous_operator.ContinuousOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.experimental.observable.variance.variance_operator.VarianceObservable)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators.types.computational_operator.base.ComputationalOperator)
get_local_kernel_arguments(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators.types.computational_operator.jax.ComputationalJaxOperator)
get_local_kernel(vstate, Ô)

Returns the function computing the local estimator for the given variational state and operator.

Parameters:

  • vstate (Any) – the variational state

  • Ô – the operator

Returns:

A callable accepting the output of get_configs(vstate, O).

get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._lazy.Squared)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator.DiscreteOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._continuous_operator.ContinuousOperator)
get_local_kernel(vs: netket.vqs.mc.mc_state.state.MCState, O: netket.operator._sum.operator.SumGenericOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._lazy.Squared, chunk_size: int)

# Dispatches to select what expect-kernel to use

get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator, chunk_size: int)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator.DiscreteOperator, chunk_size: int)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState, Ô: netket.operator._continuous_operator.ContinuousOperator, chunk_size: int)
get_local_kernel(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._abstract_super_operator.AbstractSuperOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._discrete_operator.DiscreteOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._lazy.Squared[netket.operator._abstract_super_operator.AbstractSuperOperator])
get_local_kernel(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._abstract_super_operator.AbstractSuperOperator, chunk_size: int)

# Dispatches to select what expect-kernel to use

get_local_kernel(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._lazy.Squared[netket.operator._abstract_super_operator.AbstractSuperOperator], chunk_size: int)
get_local_kernel(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._discrete_operator.DiscreteOperator, chunk_size: int)
get_local_kernel(vstate: netket.vqs.mc.mc_mixed_state.state.MCMixedState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator, chunk_size: int)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators._lazy.PenaltyCost)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._lazy.Squared)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator.DiscreteOperator | neuralqx.operators.types._discrete_operator.DiscreteOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._continuous_operator.ContinuousOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.experimental.observable.variance.variance_operator.VarianceObservable)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators.types.computational_operator.base.ComputationalOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators.types.computational_operator.jax.ComputationalJaxOperator)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator.DiscreteOperator | neuralqx.operators.types._discrete_operator.DiscreteOperator, chunk_size: int)

# standard numba operators

get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._discrete_operator_jax.DiscreteJaxOperator, chunk_size: int)

# standard JAX operators

get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._continuous_operator.ContinuousOperator, chunk_size: int)
get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.operator._lazy.Squared, chunk_size: int)

# Squared operators

get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators.types.computational_operator.base.ComputationalOperator, chunk_size: int)

# standard computational operators

get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators.types.computational_operator.jax.ComputationalJaxOperator, chunk_size: int)

# standard computational JAX operators

get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: neuralqx.operators._lazy.PenaltyCost, chunk_size: int)

# standard PenaltyCost operators

get_local_kernel(vstate: netket.vqs.mc.mc_state.state.MCState | neuralqx.vqs.mc.mc_state.state.MCState, Ô: netket.experimental.observable.variance.variance_operator.VarianceObservable, chunk_size: int)

# VarianceObservable not supported for now

class MCState(sampler, model=None, *, n_samples=None, n_samples_per_rank=None, n_discard_per_chain=None, chunk_size=None, variables=None, init_fun=None, apply_fun=None, seed=None, sampler_seed=None, mutable=False, training_kwargs={}, is_group_averaged=False)

Bases: VariationalState

Variational State for a Variational Neural Quantum State.

The state is sampled according to the provided sampler.

class MultiMCState(states)

Bases: object

Container for multiple MCState objects with overlap diagnostics.

This class groups several independently sampled variational Monte Carlo states that share the same Hilbert space, and provides tools to compute pairwise overlap measures such as the fidelity matrix and derived quantities (overlap magnitude and orthogonality).

All contained states must act on the same Hilbert space, a mismatch raises ValueError.

Parameters are managed per-state, no parameters are shared unless you explicitly tie them outside of this container.

Parameters:

states (Sequence[MCState]) – List of Monte Carlo variational states to manage.

Raises:

ValueError – If states is empty or if any pair of states has a different Hilbert space.

Subpackages

Submodules