https://github.com/jqhoogland/acm

Exercises for Advanced Computational Methods
https://github.com/jqhoogland/acm

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Exercises for Advanced Computational Methods

• Host: GitHub
• URL: https://github.com/jqhoogland/acm
• Owner: jqhoogland
• Created: 2021-02-17T08:38:51.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2021-02-17T08:52:24.000Z (almost 4 years ago)
• Last Synced: 2024-11-19T18:55:18.319Z (2 months ago)
• Language: Jupyter Notebook
• Size: 3.96 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## ACM (CMP)

Exercises for a course in my Masters: Advanced Computational Methods in Condensed Matter Physics 

---

### Project Overview

Together with [Guido Visser](https://github.com/GuidoVisser), I simulated kinetically-constrained on-lattice models to study the glass transition.

We looked at:

- The East model

- The one-spin Fredrickson-Andersen Model

on a one-dimensional chain in both discrete and continuous time. 

We weren't as successful as we hoped: likely because we needed to throw more computational power at longer simulations.

(or because of bugs we never isolated)

---

*From the [course catalogue](https://coursecatalogue.uva.nl/xmlpages/page/2020-2021-en/search-course/course/79888):*

### Objectives

- exploring and understanding the physics of a model/problem using numerical simulations

- programming and implementation of algorithms

- working independently on a research project

- production, post-processing, analysis, and interpretation of simulation data

- presentation skills

### Contents

In this course the student can choose from a selection of advanced computational research projects in condensed matter physics, either related to the simulation of quantum many-body systems or from soft condensed matter. Each project requires writing simulation codes (various methods will be covered), generating data, post-processing and analyzing the data, and finally presenting the problem and results to the other students in a pedagogical way. This course is an extension to the courses 'Advanced Numerical Methods in Many-Body Physics' and 'Statistical Physics of Soft and Living Matter', and is an ideal preparation for larger-scope research projects (e.g. Master thesis).

### Recommended prior knowledge

- Either the course 'Advanced Numerical Methods in Many-Body Physics' or the course 'Statistical Physics of Soft and Living Matter' is recommended.

- Previous experience in programming.