https://github.com/msuzen/isinglenzmc

isingLenzMC: Monte Carlo for Classical Ising Model (with core C library)
https://github.com/msuzen/isinglenzmc

deep-learning hopfield hopfield-network ising-model monte-carlo neural-networks physics spin-glass statistical-mechanics

Last synced: 5 months ago
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isingLenzMC: Monte Carlo for Classical Ising Model (with core C library)

• Host: GitHub
• URL: https://github.com/msuzen/isinglenzmc
• Owner: msuzen
• License: other
• Created: 2015-04-07T07:42:47.000Z (about 11 years ago)
• Default Branch: master
• Last Pushed: 2025-09-25T14:03:57.000Z (8 months ago)
• Last Synced: 2025-09-25T15:39:59.983Z (8 months ago)
• Topics: deep-learning, hopfield, hopfield-network, ising-model, monte-carlo, neural-networks, physics, spin-glass, statistical-mechanics
• Language: Jupyter Notebook
• Homepage:
• Size: 277 KB
• Stars: 52
• Watchers: 3
• Forks: 4
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS

Awesome Lists containing this project

README

          
[![CRAN Version](https://www.r-pkg.org/badges/version/isingLenzMC)](https://cran.r-project.org/package=isingLenzMC)

[![Total RStudio Cloud Downloads](https://cranlogs.r-pkg.org/badges/grand-total/isingLenzMC?color=brightgreen)](https://cran.r-project.org/package=isingLenzMC)

[![RStudio Cloud Downloads](https://cranlogs.r-pkg.org/badges/isingLenzMC?color=brightgreen)](https://cran.r-project.org/package=isingLenzMC)

[![arXiv:1606.08693](http://img.shields.io/badge/arXiv-1606.08693-B31B1B.svg)](https://arxiv.org/abs/1606.08693)

[![arXiv:1405.4497](http://img.shields.io/badge/arXiv-1405.4497-B31B1B.svg)](https://arxiv.org/abs/1405.4497)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1065942.svg)](https://doi.org/10.5281/zenodo.1065942)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17151290.svg)](https://doi.org/10.5281/zenodo.17151290)

# isingLenzMC: Monte Carlo for Classical Ising Model

* [Stable release on CRAN](https://CRAN.R-project.org/package=isingLenzMC)   

* [Development repository](https://github.com/msuzen/isingLenzMC)

## Description

Classical Ising Model is a land mark system in statistical physics. The model explains 

the physics of spin glasses and magnetic materials, and cooperative phenomenon 

in general, for example phase transitions and neural networks. This package provides 

utilities to simulate one dimensional Ising Model with Metropolis and Glauber Monte 

Carlo with single flip dynamics in periodic boundary conditions. Utility functions 

for exact solutions are provided. Such as transfer matrix for 1D. Example use cases 

are as follows: Measuring effective ergodicity and power-laws in so called 

functional-diffusion. 

## Example use cases

These examples are scientific use cases of the package, some corresponds to papers.

*  [Measuring effective ergodicity on differring temperature ranges](inst/examples/effectiveErgodicity/README.md) 

* [Ergodic Dynamics of Ising Model : functional-diffusion regimes](inst/examples/powerLawErgodicity)

## Related Publications and Datasets

* Effective ergodicity in single-spin-flip dynamics  

 Mehmet Suezen, [Phys. Rev. E 90, 032141](https://doi.org/10.1103/PhysRevE.90.032141)  

 [Dataset](https://doi.org/10.5281/zenodo.1065942)

* Anomalous diffusion in convergence to effective ergodicity,

Suezen, Mehmet, [arXiv:1606.08693](https://arxiv.org/abs/1606.08693)  

[Dataset](https://doi.org/10.5281/zenodo.17151290)