Bibliography

Key references behind the algorithms implemented in mcpy. The list is intentionally short; add domain-specific citations from your own work as you adapt the library.

Note

When sphinxcontrib-bibtex is enabled (see docs/requirements.txt), this page will be regenerated automatically from bibliography.bib. The entries below are placeholders so the page renders before that switch is made.

Hybrid Grand Canonical Monte Carlo

Senftle, T. P., Janik, M. J., van Duin, A. C. T. A ReaxFF investigation of hydride formation in palladium nanoclusters via Monte Carlo and molecular dynamics simulations. Journal of Physical Chemistry C, 118 (9), 4967–4981 (2014). doi:10.1021/jp411015a.

The hybrid scheme — every trial insertion or deletion is followed by a local relaxation before acceptance — is the basis of the GCMC loop in GrandCanonicalEnsemble.

Replica Exchange / Parallel Tempering

Swendsen, R. H., Wang, J.-S. Replica Monte Carlo simulation of spin-glasses. Physical Review Letters, 57 (21), 2607–2609 (1986). doi:10.1103/PhysRevLett.57.2607.

The exchange acceptance rule used by ReplicaExchange follows the standard parallel-tempering criterion derived in this paper.

Atomic Simulation Environment

Larsen, A. H., Mortensen, J. J., Blomqvist, J., et al. The atomic simulation environment — a Python library for working with atoms. Journal of Physics: Condensed Matter, 29 (27), 273002 (2017). doi:10.1088/1361-648X/aa680e.

mcpy is built directly on ASE: every configuration is an ase.Atoms object, and any ASE-compatible calculator can drive the sampling.

MACE

Batatia, I., Kovács, D. P., Simm, G. N. C., Ortner, C., Csányi, G. MACE: Higher order equivariant message passing neural networks for fast and accurate force fields. NeurIPS 2022. arXiv:2206.07697.

The reference MLIP used in the bundled examples and tutorials.