Molecular Dynamics: Probability and Uncertainty

Abstract This book explores the intersection of molecular dynamics (MD) simulation with advanced probabilistic methodologies to address the inherent uncertainties in the approach. Beginning with a clear and comprehensible introduction to classical mechanics, the book transitions into the probabilistic formulation of MD, highlighting the importance of ergodic theory, kinetic theory, and unstable periodic orbits, concepts which are largely unknown to current practitioners within the domain. It discussed ensemble-based simulations, free energy calculations and the study of polymer nanocomposites using multi-scale modelling, providing detailed guidance on performing reliable and reproducible computations. A thorough discussion on Verification, Validation, and Uncertainty Quantification (VVUQ) lays out a definitive approach to formulating the uncertainty of MD modelling and simulation. Its interaction with artificial intelligence is examined in the light of these issues. While machine learning (ML) methods offer some advantages and less often-noted drawbacks, the integration of ML with physics-based MD simulations may in future enhance our ability to predict new drugs and advanced materials. The final chapter, ‘The End of Certainty’, synthesizes these themes, advocating a systematic and careful approach to computational research and the embrace of uncertainty as an integral part of innovation. This book serves as a highly original, conceptual and comprehensible guide for researchers and practitioners, emphasizing the need for rapid, accurate, precise and actionable techniques in the rapidly-evolving field of molecular dynamics.