Hybrid Monte Carlo with Fourier Acceleration simulation package for the N=2 Principal Chiral model.
Project description
SU(2) x SU(2)
This python package offers efficient simulation and data analysis routines for the SU(2) x SU(2) Principal Chiral model. The key feature offered is the integration of Fourier Acceleration into the Hybrid Monte Carlo algorithm which leads to a significant reduction in the degree of critical slowing down.
Currently the simulation is only supported for a two dimensional cubic lattice.
Installation
To install SU2xSU2
using pip
run:
pip install SU2xSU2
Its is recommended to work in a virtual environment.
Documentation
Read the docs here.
Example
A basic example showing how to set up a simulation using Fourier accelerated HMC to measure the wall-to-wall correlation function. Further examples can be found here.
from SU2xSU2.SU2xSU2 import SU2xSU2
# define model and lattice parameters
model_paras = {'L':40, 'a':1, 'ell':5, 'eps':1/5, 'beta':0.6}
model = SU2xSU2(**model_paras)
# define simulation parameters and measurements
sim_paras = {'M':500, 'thin_freq':1, 'burnin_frac':0.5, 'accel':True, 'measurements':[model.ww_correlation_func], 'chain_paths':['corfunc_chain.npy']}
model.run_HMC(**sim_paras)
Licence
SU2xSU2
is free software made available under the MIT License. For details see the LICENSE
file.
To DO
- commit changes to build backend and making distribution
- check that imports in package work, i.e. test examples
- once package is published and can be installed
- check if example in README works
- check if example.py works
- data storage: Check that paths are relative to the to current working directory
- change name of function that integrates the beta function (state that 1/beta expansion of integrand is used)
- add tests
- plotting
- get latex error when plotting within analysis.py
- no apparent option to add errorbar format '.' in style sheet
- include mplstyle file in stylelib/ to be used globally. Currently, the file needs to be copied manually into the directory. Possible approaches:
- https://github.com/garrettj403/SciencePlots/blob/master/scienceplots/__init__.py using https://github.com/matplotlib/matplotlib/blob/main/lib/matplotlib/style/core.py
- https://matplotlib.org/stable/tutorials/introductory/customizing.html#distributing-styles
- https://stackoverflow.com/a/52997575
- https://stackoverflow.com/questions/35851201/how-can-i-share-matplotlib-style
- generalize simulation and data analysis to d-dimensional cubic lattice
Project details
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