# netket.models.RBMModPhase#

class netket.models.RBMModPhase[source]#

A fully connected Restricted Boltzmann Machine (RBM) with real-valued parameters.

In this case, two RBMs are taken to parameterize, respectively, the real and imaginary part of the log-wave-function, as introduced in Torlai et al., Nature Physics 14, 447–450(2018).

This type of RBM has spin 1/2 hidden units and is defined by:

$\Psi(s_1,\dots s_N) = e^{\sum_i^N a_i s_i} \times \Pi_{j=1}^M \cosh \left(\sum_i^N W_{ij} s_i + b_j \right)$

for arbitrary local quantum numbers $$s_i$$.

Attributes
alpha: Union[float, int] = 1#

feature density. Number of features equal to alpha * input.shape[-1]

precision: Any = None#

numerical precision of the computation see jax.lax.Precision for details.

use_hidden_bias: bool = True#

if True uses a bias in the dense layer (hidden layer bias).

variables#

Returns the variables in this module.

Return type
Methods
activation()#
has_rng(name)#

Returns true if a PRNGSequence with name name exists.

Return type

bool

Parameters

name (str) –

kernel_init(shape, dtype=<class 'jax.numpy.float64'>)#
put_variable(col, name, value)#

Sets the value of a Variable.

Parameters

Returns: