MC

"Monte-carlo"

• 

• 

Introduction

The subject of study is a statistical physics subject on the Ising model. We observe networks of size N and in dimension d. For example in dimension 1, it is a vector $N$, then in dimension two, it is a matrix $N \times N$, in dimension 3, it is an array in 3 dimensions $N \times N \times N$, etc $\cdots$ . Each network is composed of sites and on each site can live a particle, we talk about configuration. In this model, the particles are so big that they take two places, there can't be two neighboring particles, we talk about admissible configuration. In this study the objective is to determine the average density of gas on the admissible configurations by using several methods.

Notation

• $N$ is a integer
• $d$ is a integer
• $R$ is as integer

subject to :

• $N > 0$
• $d > 0$
• $R > 0$

to get started

change the value before run program

julia

in Main.jl

begin
    N = 3
    d = 2
    R = 10
    dims = Tuple([N for i in 1:N])
end

python

in program.py in directory OLD

if __name__=='__main__':
    N = 10
    R = 1000

pre-requisites

julia

• 

python

• 

the use of program progmanopt requires :

• 

• 

• 

• 

if the packages are not installed. you can install them the command in directory OLD:

pip install -r requirements.txt

if the command did not work, you can install the packages one by one with the command

pip install [package]

Contributor

• Loik johan ACAKPO-ADDRA alias @loik77360

• Lilian TEL alias @lil-tel

Links

packages

python

• numpy
• time
• copy
• matplotlib

Documentation

• Recueil de modèles aléatoires by Djalil Chafai and Florent Malrieu
• Sheldon M.Ross Simulation, Fifth Edition 2012