netket.models.NDM¶
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class
netket.models.
NDM
(dtype=<class 'numpy.float64'>, activation=<function log_cosh>, alpha=1, beta=1, use_hidden_bias=True, use_ancilla_bias=True, use_visible_bias=True, precision=None, kernel_init=<function normal.<locals>.init>, bias_init=<function normal.<locals>.init>, visible_bias_init=<function normal.<locals>.init>, parent=<flax.linen.module._Sentinel object>, name=None)[source]¶ Bases:
flax.linen.module.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
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alpha
: Union[float, int] = 1¶ The feature density for the pure-part of the ansatz. Number of features equal to alpha * input.shape[-1]
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beta
: Union[float, int] = 1¶ The feature density for the mixed-part of the ansatz. Number of features equal to beta * input.shape[-1]
if True uses a bias in the dense layer (hidden layer bias).
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