This sampler acts locally only on one local degree of freedom , and proposes a new state: , where .

The transition probability associated to this sampler can be decomposed into two steps:

  1. One of the site indices is chosen with uniform probability.
  2. Among all the possible () values that can take, one of them is chosen with uniform probability.

For example, in the case of spin particles, and the possible local values are . In this case then MetropolisLocal is equivalent to flipping a random spin.

In the case of bosons, with occupation numbers , MetropolisLocal would pick a random local occupation number uniformly between and .

Class Constructor

Constructs a new MetropolisLocal sampler given a machine.

Argument Type Description
machine netket._C_netket.machine.Machine A machine used for the sampling. The probability distribution being sampled from is , where the function , is arbitrary, by default .


Sampling from a RBM machine in a 1D lattice of spin 1/2

>>> import netket as nk
>>> g=nk.graph.Hypercube(length=10,n_dim=2,pbc=True)
>>> hi=nk.hilbert.Spin(s=0.5,graph=g)
>>> # RBM Spin Machine
>>> ma = nk.machine.RbmSpin(alpha=1, hilbert=hi)
>>> # Construct a MetropolisLocal Sampler
>>> sa = nk.sampler.MetropolisLocal(machine=ma)
>>> print(sa.hilbert.size)

Class Methods


Resets the state of the sampler, including the acceptance rate statistics and optionally initializing at random the visible units being sampled.

Argument Type Description
init_random bool=False If True the quantum numbers (visible units)


Seeds the random number generator used by the Sampler.

Argument Type Description
base_seed int The base seed for the random number generator


Performs a sampling sweep. Typically a single sweep consists of an extensive number of local moves.


Property Type Description
acceptance numpy.array The measured acceptance rate for the sampling. In the case of rejection-free sampling this is always equal to 1.
hilbert netket.hilbert The Hilbert space used for the sampling.
machine netket.machine The machine used for the sampling.
machine_func function(complex) The function to be used for sampling. by default is sampled, however in general
visible numpy.array The quantum numbers being sampled, and distributed according to