neuralqx.samplers package

This module includes the implementation of different samplers for neuralqx

WeightedSamplerRule

alias of MultipleRules

class MetropolisKLocalRule(*args: Any, **kwargs: Any) → P

Bases: MetropolisRule

class RandomU1GaugeSampler(*args: Any, **kwargs: Any)

Bases: MetropolisRule

This class implements a U(1) gauge sampler which samples states from the Hilbert space based on a specified gauge fixing. The proposed states are essentially random gauge invariant states

class U1GaugeSampler(*args: Any, **kwargs: Any)

Bases: MetropolisRule

This class implements a U(1) gauge sampler which samples states from the Hilbert space based on a specified gauge fixing.

The proposed states are ones which lie in the neighborhood of the input states. This is done by flipping one of the free edges’ quantum numbers and reimposing the gauge fixing on the slave edges.

class U1InvariantPlaquetteSampler(*args: Any, **kwargs: Any)

Bases: MetropolisRule

This class implements a U(1) gauge sampler which samples states from the Hilbert space based on a specified gauge fixing.

The proposed states are ones which lie in the neighborhood of the input states. This is done by flipping one of the free edges’ quantum numbers and reimposing the gauge fixing on the slave edges.

class Sampler(sampler_type, number_of_chains=70, number_of_sweeps=10, machine_pow=2, reset_chains=True, number_of_samples=250, **sampler_kwargs)

Bases: object

class MuSampler(*args: Any, **kwargs: Any)

Bases: MetropolisRule

A sampler which is specific to the spherical model. It operates under the guide that the volume on the internal vertices of the half ladder graph are non-zero. This is done by sampling states where the quantum numbers associated to the mu-edges is never allowed to be zero.

Subpackages

Submodules