Papers › relentless: Transparent, reproducible molecular dynamics simulations for optimization
relentless: Transparent, reproducible molecular dynamics simulations for optimization
Adithya N Sreenivasan, C. Levi Petix, Zachary M. Sherman, Michael P. Howard
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relentless is an open-source Python package that enables the optimization of objective functions computed using molecular dynamics simulations. It has a high-level, extensible interface for model parametrization; setting up, running, and analyzing simulations natively in established software packages; and gradient-based optimization. We describe the design and implementation of relentless in the context of relative entropy minimization, and we demonstrate its abilities to design pairwise interactions between particles that form targeted structures. relentless aims to streamline the development of computational materials design methodologies and promote the transparency and reproducibility of complex workflows integrating molecular dynamics simulations.
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