netket.models.NDM#
- class netket.models.NDM[source]#
Bases:
Module
Encodes a Positive-Definite Neural Density Matrix using the ansatz from Torlai and Melko, PRL 120, 240503 (2018).
Assumes real dtype. A discussion on the effect of the feature density for the pure and mixed part is given in Vicentini et Al, PRL 122, 250503 (2019).
- Attributes
-
alpha:
Union
[float
,int
] = 1# The feature density for the pure-part of the ansatz. Number of features equal to alpha * input.shape[-1]
-
beta:
Union
[float
,int
] = 1# The feature density for the mixed-part of the ansatz. Number of features equal to beta * input.shape[-1]
-
precision:
Any
= None# numerical precision of the computation see
jax.lax.Precision
for details.
if True uses a bias in the dense layer (hidden layer bias).
-
use_visible_bias:
bool
= True# if True adds a bias to the input not passed through the nonlinear layer.
-
kernel_init:
Callable
[[Any
,Sequence
[int
],Any
],Union
[ndarray
,Array
]]# Initializer for the Dense layer matrix.
-
alpha: