# netket.models#

This sub-module contains several pre-built models to be used as neural quantum states.

 LogStateVector _Exact_ ansatz storing the logarithm of the full, exponentially large wavefunction coefficients. RBM A restricted boltzman Machine, equivalent to a 2-layer FFNN with a nonlinear activation function in between. RBMModPhase A fully connected Restricted Boltzmann Machine (RBM) with real-valued parameters. RBMMultiVal A fully connected Restricted Boltzmann Machine (see netket.models.RBM) suitable for large local hilbert spaces. RBMSymm A symmetrized RBM using the netket.nn.DenseSymm layer internally. Jastrow Jastrow wave function $$\Psi(s) = \exp(\sum_{ij} s_i W_{ij} s_j)$$. MPSPeriodic A periodic Matrix Product State (MPS) for a quantum state of discrete degrees of freedom, wrapped as Jax machine. NDM Encodes a Positive-Definite Neural Density Matrix using the ansatz from Torlai and Melko, PRL 120, 240503 (2018). GCNN Implements a Group Convolutional Neural Network (G-CNN) that outputs a wavefunction that is invariant over a specified symmetry group. AbstractARNN Base class for autoregressive neural networks. ARNNDense Autoregressive neural network with dense layers. ARNNConv1D Autoregressive neural network with 1D convolution layers. ARNNConv2D Autoregressive neural network with 2D convolution layers. FastARNNConv1D Fast autoregressive neural network with 1D convolution layers. FastARNNConv2D Fast autoregressive neural network with 2D convolution layers. DeepSetMLP Implements the DeepSets architecture, which is permutation invariant. DeepSetRelDistance Implements an equivariant version of the DeepSets architecture given by (https://arxiv.org/abs/1703.06114) MLP A Multi-Layer Perceptron with hidden layers.