Rigorous-dynamical-mean-field-theory

Code for integrating the DMFT equations in "Rigorous dynamical mean field theory for stochastic gradient descent methods"

Dependencies

• Numpy version 1.22.2
• Scipy version 1.7.1
• MPI4PY version 3.0.3
• Matplotlib version 3.5.1
• Pandas version 1.3.2

Note that MPI4PY also requires a MPI implementation. We refer to the MPI4PY documentation for further information. A convinient way to setup the enviroment is by using conda and environment.yml

How to integrate the equations

You can compute the DMFT fixed point iteration by running main.py. It's necessary to have a folder caller 'data'

How view the results

A convenient plotting script is provided. Running plot.py will visualise the last steps of the iteration. We also provided a numerical simulation, which can be used to compare the results of the DMFT procedure. Any personal computer should reproduce comparison.png in approximately 1 minute using a single core.