Title: Tensor Networks for Stochastic Chemical Kinetics

Speaker: Todd Gingrich, Northwestern University

Abstract: 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. When the stochastic chemical kinetics describes a nonequilibrium process, how can we computationally study the steady state? The traditional answer is to sample trajectories. In this talk, I will discuss how the tensor network techniques (DMRG and TDVP) from quantum many-body problems are naturally repurposed to study many-body stochastic chemical kinetics.

Zoom: https://northwestern.zoom.us/s/94712118004

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