Theoretical and computational science and engineering are important components of research in the department. The continuing advances in computational capabilities have made it possible to study phenomena in unprecedented detail, over large length scales and long timescales. Princeton University has an active research-computing community that provides advanced hardware and software capabilities and educational opportunities for students and researchers at all levels.
Computational statistical mechanics plays a key role within the department is, typically done through classical Monte Carlo or molecular-dynamics simulations of proteins, complex fluids, polymers, or colloidal particles, frequently under non-equilibrium conditions.
Another focus area for theoretical and computational work involves quantum mechanical calculations (density functional theory and ab initio molecular dynamics). These are used to predict electronic properties of catalysts and to generate accurate force fields for use in larger-scale (classical) calculations. Machine learning and other big-data methods play an increasingly important role in this area.
In both classical and quantum calculations, at Princeton we strive to develop new theoretical methods and efficient computational algorithms, which are then shared with the broader research community as open-source software.