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

No description provided.

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 theory and related 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

Simulating non-equilibrium quantum lattices via time-dependent variational Monte Carlo and MPOs.

A PyTorch implementation of a Neural Quantum State (NQS) simulator for quantum many-body systems, featuring symmetry-preserving neural networks and advanced sampling techniques.