Variational Tensor Network Monte Carlo Approach to Non-Equilibrium Quantum Many-Body Systems

Zoom link: https://us06web.zoom.us/j/87057373249?pwd=MNnyk4rUf9cOVZoxeqIaKkhwYk5STm.1

Abstract

The modelling of realistic quantum devices necessitates the development of advanced simulation methods for out-of-equilibrium quantum many-body systems with complex interactions and environments. We propose a novel tensor-network-based variational Monte Carlo algorithm applicable to open quantum lattices described by the Gorini–Kossakowski–Sudarshan–Lindblad master equation [1]. Our method performs competitively with comparable state-of-the-art tensor network and neural network approaches, while offering several unique advantages. We showcase its versatility and effectiveness by simulating the dynamics and steady states of a range of driven-dissipative quantum spin lattices, including models with otherwise prohibitively challenging strongly-long-ranged interactions and highly non-local dissipation channels with potential applications to near-term quantum technologies. Time-permitting, we shall also discuss preliminary work and proof-of-principle results on an extension of the present approach to non-Markovian quantum master equations.  

[1] D. A. Hryniuk and M. H. Szymańska, Tensor-network-based variational Monte Carlo approach to the non-equilibrium steady state of open quantum systems, Quantum 8, 1475 (2024)