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Deep learning quantum Monte Carlo for electrons in real space
Main repository for QMCPACK, an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support
The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.
Classical and quantum Monte Carlo simulations in Julia
DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electron Schrödinger equation. DeepErwin supports weight-sharing when optimizing wave functions for multiple nuclear geometries and the usage of pre-trained neural network weights to accelerate optimization.
A continuous-time hybridization-expansion Monte Carlo code for calculating n-particle Green's functions of the Anderson impurity model and within dynamical mean-field theory.
Neural-Network representation of Quantum Systems
Quantum Monte Carlo methods for Ising model
Tracking citations of atomistic simulation engines
Introduction to quantum Monte Carlo. From the foundations to state-of-the-art Restricted Boltzmann Machine ansatz.
Implementation of Stochastic Series Expansion Monte Carlo method for the spin-S XXZ model. https://doi.org/10.1103/PhysRevE.67.046701
Simulating the fractional quantum Hall effect with neural network variational Monte Carlo
Repository for PseudopotentialLibrary.org website and database
Example class structure for use in FYS4411: Quantum mechanical systems at UiO.
Variational Quantum Monte Carlo for a molecule, using Fokker-Planck/Langevin approach
FPGA accelerated Path Integral Monte Carlo. Project for computational physics.
Efficient continuous-time quantum Monte Carlo method for spinless fermions