Tensor Networks for Stochastic Chemical Kinetics.

Speaker: Prof. Todd Gingrich (Northwestern University)

Start Date/Time: 2025-5-14 / 9:00 a.m. (Taipei time) = 2025-5-13 / 8:00 p.m. (Chicago time)
End Date/Time: 2025-5-14 / 10:30 a.m.  

Host: Prof. Ching-Yu Huang (THU) 

Online Zoom Link: https://zoom.us/j/91356947494?pwd=IjtKbcM9ObQfbj6cAWZFySoszuKP1b.1
[Registration] is required

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 & TDVP) from quantum many-body problems are naturally repurposed to study many-body stochastic chemical kinetics.