Source-linked AI summary
Efficient simulation of strong system-environment interactions
Javier Prior, Alex. W. Chin, Susana. F. Huelga, Martin . B. Plenio
TL;DR
Strong system-environment interactions make standard weak-coupling and Markovian simulations unreliable for many open quantum systems. The paper combines an exact orthogonal-polynomial chain transformation with t-DMRG, obtaining efficient simulations that capture non-perturbative and non-Markovian dynamics across structured environments.
Problem
Standard approaches based on weak system-bath coupling and the Markov approximation are often invalid for realistic open quantum systems with strong or structured environmental interactions.
Method
The method combines time-adaptive density matrix renormalisation with orthogonal-polynomial transformations that exactly map continuous baths to one-dimensional chains suitable for DMRG.
Results
The simulations reproduce rich non-perturbative and non-Markovian dynamics, including optimal transfer near λ ≈80cm−1 and persistent oscillations lasting at least 1.5 ps when a high-energy mode is present.
Takeaways & Limitations
The approach provides a general simulation tool for arbitrary spectral densities and coupling strengths, including multi-component systems and structured environments.
Takeaways & Limitations
The reported simulations use T = 0 K and a separable initial state, while finite-temperature extensions and more complex settings are identified for future work.
Abstract
from arXiv · showhide
Multi-component quantum systems in strong interaction with their environment are receiving increasing attention due to their importance in a variety of contexts, ranging from solid state quantum information processing to the quantum dynamics of bio-molecular aggregates. Unfortunately, these systems are difficult to simulate as the system-bath interactions cannot be treated perturbatively and standard approaches are invalid or inefficient. Here we combine the time dependent density matrix renormalization group methods with techniques from the theory of orthogonal polynomials to provide an efficient method for simulating open quantum systems, including spin-boson models and their generalisations to multi-component systems.