Julia package for the construction of quantum lattice systems.
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Updated
Apr 30, 2026 - Julia
Julia package for the construction of quantum lattice systems.
Tutorials for the lecture "Computational Methods in Many-Body Physics"
Official code for the paper "Predicting Properties of Quantum Systems with Conditional Generative Models"
A method which combines quantum many-body calculation and unbiased optimizers to automatically learn effective Hamiltonians for quantum magnets
variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions
OpenMS is a collection of multiscale solvers for coupled Maxwell-Schrödinger equations in Open quantum environments.
UvA Master thesis "Towards Quantum Graph Neural Networks". The research explores integrating quantum physics into Graph Neural Networks through methods like Tensor Networks to tackle computational challenges in quantum many-body systems.
Neural Network Quantum State
MeanFieldTheories.jl is a Julia package for studying quantum many-body systems using mean-field methods.
Variational Matrix Product Operator Monte Carlo
mini exact diagonalization code for many-body Green's functions of atoms
In my licenciatura (BA + M.Sc. in Physics equivalent) thesis, with my director J.M. Matera, we worked in both analytical and computational techniques for the study of non-markovian quantum systems using Max-Ent approximation for instantaneous states, the latter with open code and hand-made also.
Neural network ansatz to approximate a ground state by using variational Monte Carlo (VMC)
Exact diagonalization of interacting quantum many-body systems
Training Camp Materials
A PyTorch implementation of a Neural Quantum State (NQS) simulator for quantum many-body systems, featuring symmetry-preserving neural networks and advanced sampling techniques.
A graduate course at the University of Chicago on the topics of quantum gases and optics and many-body interactions. The .py files here are projects from the course on many-body quantum simulation that we turned into web apps using Streamlit Cloud. Taught by Professor Cheng Chin, Spring Quarter 2026.
Simulating non-equilibrium quantum lattices via time-dependent variational Monte Carlo and MPOs.
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