IsingMonteCarlo

• (Mostly incomplete) docs: https://docs.rs/qmc/

• Python binding: https://github.com/Renmusxd/PyIsingMonteCarlo

• WASM binding: https://github.com/Renmusxd/WASMIsingMonteCarlo

  • Example: https://renmusxd.github.io/wasm_qmc/index.html

lib.rs:

qmc is a library for simulating classical and quantum ising systems on a lattice using monte carlo methods.

The sse library contains built-in classes to handle ising models, as well as classes which handle arbitrary interactions.

It also offers a few feature gated modules:

• parallel tempering system using the tempering or parallel-tempering feature gates.
• autocorrelation calculations on variables, bonds, or arbitrary values: use autocorrelations
• graph serialization using serde with the serialize feature.

Basic Quantum Ising Example

use qmc::sse::*;
use rand::prelude::*;

// H = J_ij s_i s_j
let edges = vec![
  ((0, 1), -1.0), // ((i, j), J)
  ((1, 2), 1.0),
  ((2, 3), 1.0),
  ((3, 0), 1.0)
];
let transverse = 1.0;
let longitudinal = 0.0;
let beta = 1.0;

// Make an ising model using default system prng.
let rng = rand::thread_rng();
let mut g = DefaultQmcIsingGraph::<ThreadRng>::new_with_rng(edges, transverse, longitudinal, 3, rng, None);

// Take timesteps
g.timesteps(1000, beta);

// Take timesteps and sample states (as Vec<Vec<bool>>).
let (state, average_energy) = g.timesteps_sample(1000, beta, None);