Description

COndensed Matter Physics Numerical Analytics Library (COMPNAL) is a numerical calculation library in the field of condensed matter physics. This library aims to provide a comprehensive set of numerical methods and algorithms tailored for analyzing various condensed matter systems.

API Reference

C++ Reference

Features

COMPNAL can calculate the following models on the following lattices by the following solvers.

Lattice

One-dimensional chain
Two-dimensional square lattice
Three-dimensional cubic lattice
Fully-connected lattice

Model

Classical models

Ising model
Polynomial Ising model

Solver

For Classical models

Classical Monte Carlo method
- Single spin flip
- Parallel tempering

Upcoming Features

We are actively working on expanding COMPNAL with the following upcoming features.

Lattice

[ ] Two-dimensional triangular lattice
[ ] Two-dimensional honeycomb lattice
[ ] User-defined lattice

Model

[ ] Classical model
- [ ] Potts model
[ ] Quantum model
- [ ] Transverse field Ising model
- [ ] Heisenberg model
- [ ] Hubbard model
- [ ] Kondo Lattice model

Algorithm

[ ] Classical Monte Carlo method
- [ ] Suwa-Todo algorithm
- [ ] Wolff algorithm
- [ ] Swendsen-Wang algorithm
[ ] Exact Diagonalization
- [ ] Lanczos method
- [ ] Locally Optimal Block Preconditioned Conjugate Gradient method
[ ] Density Matrix Renormalization Group

Installation

Install from PyPI

Only for Linux and MacOS.

pip install compnal

Install from GitHub

To install the latest release of compnal from the source, use the following command:

pip install git+https://github.com/K-Suzuki-Jij/compnal.git

Before installation, make sure that the following dependencies are installed.

Build from source

COMPNAL depends on the following libraries.

On MacOS

First, install the dependencies using Homebrew.

brew install cmake libomp

Then, clone this repository and install COMPNAL.

python -m pip install . -vvv

Run the test to check if the installation is successful.

python -m pytest tests

On Linux

First, install the dependencies using apt.

sudo apt install cmake

Then, clone this repository and install COMPNAL.

python -m pip install . -vvv

Run the test to check if the installation is successful.

python -m pytest tests