MC/DC: Monte Carlo Dynamic Code

MC/DC is an open-source, Python-based Monte Carlo radiation transport code that combines rapid methods development with scalable, high-performance execution on modern computing systems. Originally initiated by the Center for Exascale Monte Carlo Neutron Transport (CEMeNT), MC/DC development is now led by the Center for Advancing the Radiation Resilience of Electronics (CARRE).

Features

• Monte Carlo neutron transport, with photon and charged-particle transport and coupled multi-particle capabilities under development
• Time-dependent, steady-state, and eigenvalue simulations
• Multiple physics fidelities (e.g., continuous-energy and multigroup neutron transport, with single-scattering and condensed-history charged-particle transport under development)
• Distributed-memory parallel execution with MPI
• Machine-portable Python implementation accelerated by Numba JIT compilation
• Extensible architecture for prototyping new transport methods

Installation

MC/DC requires Python 3.11 or newer.

Install the latest stable release from PyPI:

pip install mcdc

For development installation and additional options, see the Installation Guide.

Documentation

Complete documentation is available on Read the Docs, including:

• User Guide
• Getting Started
• API Reference
• Developer Guide
• Contributing

Citing

If you use MC/DC in published work, please cite the following article:

• J. P. Morgan et al. (2024). Monte Carlo / Dynamic Code (MC/DC): An accelerated Python package for fully transient neutron transport and rapid methods development. Journal of Open Source Software, 9(96), 6415.

Reporting Bugs and Issues

To report bugs, request features, or ask questions, please open a GitHub Issue.