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
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Updated
Sep 23, 2024 - C++
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
Python realisation of Casino (QMC) program
Deep learning quantum Monte Carlo for electrons in real space
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.
Variational Matrix Product Operator Monte Carlo
Tracking citations of atomistic simulation engines
QMC=Chem version 2
Implementation of Stochastic Series Expansion Monte Carlo method for the spin-S XXZ model. https://doi.org/10.1103/PhysRevE.67.046701
Python wrappers for TurboRVB
Repository for PseudopotentialLibrary.org website and database
Project developed for the Numeric Simulation Laboratory A.A. 2023-2024, held by professor Davide Emilio Galli at the University of Milan, Physics Department.
Quantum Monte Carlo package, TurboRVB
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.
Calculating Force in FermiNet
Variational Quantum Monte Carlo for a molecule, using Fokker-Planck/Langevin approach
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 net…
This repository contains Python implementation Path integral Quantum Monte-Carlo to find the ground state energy of the harmonic oscillator.
Classical and quantum Monte Carlo simulations in Julia
Detecting phase transitions from Quantum Monte Carlo datasets using the "learning by confusion" (LbC) technique. Training CNNs in PyTorch to classify phases of matter in an electron-phonon model.
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