BCL: Balance Condition Library

The goal of the BCL is providing

• C++ reference implementation of the rejection-optimized irreversible kernel (ST2010) and its reversible version (ST2013) as well as Metropolis-Hasting and Gibbs sampler in Markov Chain Monte Carlo (MCMC),
• interface for C, Fortran, Python, etc, and
• example and benchmark programs of Markov Chain Monte Carlo simulation based on several MCMC kernels on standard models (Ising, Potts, etc) in the field of statistical physics.

Release Note

• Release 0.1 (2013/09/12)

  • Initial version

• Release 0.2 (2021/12/06)

  • Changed license to Apache 2.0
  • Removed dependency on Boost library

Reference

• H. Suwa and S. Todo, "Markov Chain Monte Carlo Method without Detailed Balance," Physical Review Letters 105, 120603 (2010).

Developers

• Synge Todo (University of Tokyo)
• Hidemaro Suwa (University of Tokyo)