Variational Monte Carlo

19 papers with code • 0 benchmarks • 0 datasets

Variational methods for quantum physics

Most implemented papers

Towards a Foundation Model for Neural Network Wavefunctions

mdsunivie/deeperwin 17 Mar 2023

Furthermore, we provide ample experimental evidence to support the idea that extensive pre-training of a such a generalized wavefunction model across different compounds and geometries could lead to a foundation wavefunction model.

Spectral Inference Networks: Unifying Deep and Spectral Learning

deepmind/spectral_inference_networks ICLR 2019

We present Spectral Inference Networks, a framework for learning eigenfunctions of linear operators by stochastic optimization.

Solving Statistical Mechanics Using Variational Autoregressive Networks

wdphy16/stat-mech-van 27 Sep 2018

We propose a general framework for solving statistical mechanics of systems with finite size.

Deep autoregressive models for the efficient variational simulation of many-body quantum systems

HUJI-Deep/FlowKet 11 Feb 2019

Artificial Neural Networks were recently shown to be an efficient representation of highly-entangled many-body quantum states.

Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo

ywolfeee/lapjax 17 Jul 2023

Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry.

Natural Quantum Monte Carlo Computation of Excited States

deepmind/ferminet 31 Aug 2023

We present a variational Monte Carlo algorithm for estimating the lowest excited states of a quantum system which is a natural generalization of the estimation of ground states.

Streaming Variational Monte Carlo

catniplab/svmc 4 Jun 2019

Nonlinear state-space models are powerful tools to describe dynamical structures in complex time series.

Natural evolution strategies and variational Monte Carlo

Ericolony/QAOA 9 May 2020

A notion of quantum natural evolution strategies is introduced, which provides a geometric synthesis of a number of known quantum/classical algorithms for performing classical black-box optimization.

Convergence to the fixed-node limit in deep variational Monte Carlo

deepqmc/deepqmc 11 Oct 2020

Variational quantum Monte Carlo (QMC) is an ab-initio method for solving the electronic Schr\"odinger equation that is exact in principle, but limited by the flexibility of the available ansatzes in practice.

Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks

wdphy16/neural-cluster-update 12 May 2021

Efficient sampling of complex high-dimensional probability distributions is a central task in computational science.