Python code implementing Markov Chain Monte Carlo for 2D and 3D square-lattice Ising model. Numba JIT compiling supported; Multiprocessing supported

2D Ising model: For two and higher dimensions, we can introduce islands of defects, which cost only at the boundaries, and are thus, proportional to the perimeter L = εN2, where 0 <ε <1. In...

Jan 29, 2018 · I've coded out the Ising Model simulation based on Monte Carlo simulation and the Metropolis Algorithm but I am having some trouble, namely the ValueError: setting an array element with a sequence. Any help to solve this would be appreciated. The following shows where the error lies in the code:.

Nov 4, 2017 · I am trying to calculate the energy, magnetization and specific heat of a two dimensional lattice using the metropolis monte carlo algorithm. return np.ones((rows, cols)) left = (x, y - 1) right = (x, (y + 1) % lattice) top = (x - 1, y) bottom = ((x + 1) % lattice, y) return [spin_array[left[0], left[1]], spin_array[right[0], right[1]],

Jul 23, 2013 · This code is written in Python, using the Visual module (VPython) developed by David Scherer and Bruce Sherwood. Although VPython is intended mostly for 3D graphics, it can also be used to draw a two-dimensional lattice of squares such as this.

This article explores an implementation of the 2D Ising model using the Metropolis algorithm in the Python programming language. The goal of this work was to explore the scope of behaviours this model can demonstrate through a simplistic implementation on a relatively low-end machine.

In your Python code, you compute the specific heat for each iteration. The calculation should be outside the loop over 'sweep'. You should accumulate $E$ and $E^2$ at each iteration (what it is done correctly with $e_0$ and $e_1$) and then, at the end of the loop, normalize them by dividing them by sweeps ($e_1=e_1/{\rm sweeps}$) and finally ...

This repository contains a Python implementation of the Ising model simulation using the Metropolis-Hastings algorithm. The code allows for studying phase transitions in magnetic systems, computing specific heat, mean energy, magnetization, and magnetic susceptibility for a …

Jan 9, 2023 · Without further ado, let us implement the Metropolis algorithm for the 2D Ising model in Python. To start with, we can randomly generate the initial spin configuration.

2D Ising model: In two (and higher dimensions), we can introduce islands of defects, which cost only at the boundaries, and are thus, proportional to the perimeter $L=\varepsilon N$ , where $0\varepsilon\leq1$. Total number of spins: $N$.