Tutorials

This repository contains introductory tutorials that can either be used for self-study, or as part of a course.

1. Classical Monte Carlo methods for studying spin systems

This tutorial introduces probabilistic Monte Carlo methods for studying spin models. The tutorial explores the thermodynamics and criticality of the Ising model. Introduced Monte Carlo algorithms are very general and can be easily extended to other spin models, such as the XY or Heisenberg models.

Overview

• Aim 1: Study the Ising model within the local Metropolis algorithm - obtain a groundstate and calculating energy, magnetization, specific heat and susceptibility.
• Aim 2: introduce two upgraded Monte Carlo approaches - heat bath and Wolf cluster algorithm

Tutorial

MonteCarlo_IsingModel_amnedic_tutorial.ipynb

Requirements

• Programming Language: Python 3.0
• Libraries: numpy, matplotlib, random

Acknowledgements

This tutorial is motivated by the lectures and homeworks in the course of Numerical Physics given by Professor Alberto Rosso. The tutorial is prepared as part of the lecture for the Condensed Matter Theory group meeting at Iowa State University in Fall 2021.