qmctorch.sampler.metropolis module

class qmctorch.sampler.metropolis.Metropolis(nwalkers: int = 100, nstep: int = 1000, step_size: float = 0.2, ntherm: int = -1, ndecor: int = 1, nelec: int = 1, ndim: int = 3, init: Dict = {'max': 5, 'min': -5}, move: Dict = {'proba': 'normal', 'type': 'all-elec'}, cuda: bool = False)

Bases: SamplerBase

Metropolis Hasting generator

Parameters:

• nwalkers (int, optional) – Number of walkers. Defaults to 100.

• nstep (int, optional) – Number of steps. Defaults to 1000.

• step_size (int, optional) – length of the step. Defaults to 0.2.

• nelec (int, optional) – total number of electrons. Defaults to 1.

• ntherm (int, optional) – number of mc step to thermalize. Defaults to -1, i.e. keep only the last position

• ndecor (int, optional) – number of mc step for decorelation. Defauts to 1.

• ndim (int, optional) – total number of dimension. Defaults to 3.

• init (dict, optional) – method to init the positions of the walkers. See Molecule.domain()

• move (dict, optional) –

  method to move the electrons. default(‘all-elec’,’normal’)

  ’type’:

  ’one-elec’: move a single electron per iteration

  ’all-elec’: move all electrons at the same time

  ’all-elec-iter’: move all electrons by iterating through single elec moves

  ’proba’ :

  ’uniform’: uniform in a cube

  ’normal’: gussian in a sphere

• cuda (bool, optional) – turn CUDA ON/OFF. Defaults to False.

Examples::

>>> mol = Molecule('h2.xyz')
>>> wf = SlaterJastrow(mol)
>>> sampler = Metropolis(nwalkers=100, nelec=wf.nelec)
>>> pos = sampler(wf.pdf)

log_data()

log data about the sampler.

configure_move(move: Dict)

Configure the electron moves

Parameters:

move (dict, optional) –

method to move the electrons. default(‘all-elec’,’normal’)

’type’:

’one-elec’: move a single electron per iteration

’all-elec’: move all electrons at the same time

’all-elec-iter’: move all electrons by iterating through single elec moves

’proba’ :

’uniform’: uniform ina cube

’normal’: gussian in a sphere

Raises:

ValueError – If moves are not recognized

move(pdf: Callable, id_elec: int) → torch.Tensor

Move electron one at a time in a vectorized way.

Parameters:

• pdf (callable) – function to sample

• id_elec (int) – index f the electron to move

Returns:

new positions of the walkers

Return type:

torch.tensor