MC/DC: Monte Carlo Dynamic Code

MC/DC logo

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:

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.

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Publisher: publish-pypi.yml on mcdc-project/mcdc

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- Statement type: https://in-toto.io/Statement/v1
- Predicate type: https://docs.pypi.org/attestations/publish/v1
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- Permalink: mcdc-project/mcdc@7d292747a10e426e42fcdd810e05a025b0888695
- Branch / Tag: refs/tags/v0.15.0
- Owner: https://github.com/mcdc-project
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