Todd Gingrich

Chemical processes exhibit chaotic, high-dimensional dynamics as molecules undergo reactions and diffusion. In the special case of a closed, isolated system, the complex dynamical processes relax into a comparatively simple equilibrium steady-state probability distribution. However, the situation is more complicated when fuel flows into a system and waste flows out. For example, supra-
molecular synthetic molecular motors mix reactions and diffusion to convert the fuel energy into directed motion. Away from equilibrium, the theoretical principles and computational methodologies for describing such systems are less well understood. Using open-system molecular dynamics simulations with a minimal model, I will address current reversals, power strokes, and the thermodynamic uncertainty relation. In the second part of my talk, I will discuss tensor-network strategies for studying chemical reaction network dynamics at the level of stochastic kinetics. I will give a flavor of how these methods promise to open up new avenues for studying how reaction networks respond to perturbations.