(736a) Automated Tests for Physical Validity in Molecular Dynamics and Monte Carlo Simulations

Advances in recent years have made molecular dynamics (MD) and Monte Carlo (MC) simulations a powerful tool in molecular-level research, allowing the prediction of experimental observables in the study of systems such as proteins, membranes, and polymeric materials. The quality of any prediction based on molecular dynamics results will strongly depend on the validity of underlying physical assumptions.

Based on a number of examples, in which (sometimes hard-to-spot) unphysical behavior of simulations had statistically important influence on their results, we propose a two-fold approach to increase the robustness of molecular simulations. The first aspect involves tests which can be performed by the users of MD programs on their respective systems and setups. We present a number of tests of different complexity, ranging from simple post-processing analysis to more involved tests requiring additional simulations. These tests are shown to significantly increase the reliability of MD simulations by catching a number of common simulation errors violating physical assumptions, such as non-conservative integrators, deviating from the Boltzmann ensemble, or lack of ergodicity between degrees of freedom. To render the usage as easy as possible, an open-source and platform-independent Python library containing the presented tests is available.

The second aspect involves testing for code correctness. While unphysical behavior can be due to poor or incompatible choices of parameters by the user, it can just as well originate in coding errors within the program. We therefore propose to include physical validation tests in the code-checking mechanism of MD software packages. We have implemented such a validation for the GROMACS software package, ensuring that every major releases passes a number of physical sanity checks performed on selected representative systems before shipping. It is, to our knowledge, the first major molecular mechanics software package to run such validation routinely. The tests are, as the rest of the package, open source software, and can be adapted for other software packages.