Efficient time evolution for dynamical mean-field theory
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Updated
Jul 21, 2026 - C++
Efficient time evolution for dynamical mean-field theory
This repository contains the post-processed data and MATLAB scripts used to reproduce all figures presented in the manuscript and Supplementary Information (SI) of: "Nonequilibrium Self-Assembly Control by the Stochastic Landscape Method". Authors: Michael Faran and Prof. Gili Bisker.
Code, processed data, figures, and manuscript sources for a TDGL study of seed geometry in nucleation-controlled transition times.
Reproducible 2D Kawasaki–Ising coarsening and a two-tier (spectral + coarsening) operational test of the Mpemba effect under conserved dynamics. Result: no Mpemba-like inversion.
Making signal restoration measurable: the same chemical reaction network run as deterministic mass-action ODEs and as an exact Gillespie SSA, and what the gap between them costs in free energy.
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