Code for 'Solving Statistical Mechanics using Variational Autoregressive Networks'.
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Updated
Jul 29, 2024 - Python
Code for 'Solving Statistical Mechanics using Variational Autoregressive Networks'.
Implementation of deep implicit attention in PyTorch
Physics-inspired transformer modules based on mean-field dynamics of vector-spin models in JAX
A Python package for efficient optimisation of real-space renormalization group transformations using Tensorflow.
Code for 'From Tensor Network Quantum States to Tensorial Recurrent Neural Networks'.
Implementation of approximate free-energy minimization in PyTorch
Code for 'Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks'.
A simulation framework for nonequilibrium statistical physics
A python implementation of ELE method in paper "Abrupt phase transition of epidemic spreading in simplicial complexes", PRR 2020
Sedimention of active Brownian particles in a box. Codes for numerical simulations and numerical solution of PDEs.
Gas simulation with graphical PyQt5 interface. It can simulate either an ideal or real gas and calculate some of its properties as the thermodynamic pressure, the particle velocity distribution, etc. It can also simulate some thermodynamics processes like an isothermal expansion or isochoric heating and calculate the compressibility.
Another phase transition in the Axelrod model
Ising model with super long-range interactions. Includes code for Monte Carlo simulations and an analytical exploration of the model.
Strong Disorder RG Flow and the Random Singlet Phase of a 1D Random AF Heisenberg Spin-1/2 Chain.
Memo's research works.
An implementation of a genetic algorithm in Python for predicting equilibrium crystal structures for a given potential. The potential implemented here is the Daoud-Cotton model, but this can be easily changed.
Pair correlation function simulation for liquid noble gases.
A Python Package to perform Widom's Test-Particle method on molecular-dynamics simulation data
Python little library to simulate nanoscale hat transport from the Gray Model approach.
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