Spectral signatures of the Markovian to Non-Markovian transition in open quantum systems

TL;DR

This paper introduces a spectral analysis method using hierarchical algebraic equations to identify the transition from Markovian to non-Markovian dynamics in quantum aggregates, revealing how spectral features indicate system-bath interactions and aggregate geometry.

Contribution

It presents a novel spectral approach to detect Markovian to non-Markovian transitions in quantum systems, emphasizing the role of dissipation, interactions, and geometry.

Findings

Spectral peak splitting signals non-Markovian effects.

Aggregate-bath coupling influences spectral peak merging or splitting.

Spectral features can identify aggregate geometric structures.

Abstract

We present a new approach for investigating the Markovian to non-Markovian transition in quantum aggregates strongly coupled to a vibrational bath through the analysis of linear absorption spectra. Utilizing hierarchical algebraic equations in the frequency domain, we elucidate how these spectra can effectively reveal transitions between Markovian and non-Markovian regimes, driven by the complex interplay of dissipation, aggregate-bath coupling, and intra-aggregate dipole-dipole interactions. Our results demonstrate that reduced dissipation induces spectral peak splitting, signaling the emergence of bath-induced non-Markovian effects. The spectral peak splitting can also be driven by enhanced dipole-dipole interactions, although the underlying mechanism differs from that of dissipation-induced splitting. Additionally, with an increase in aggregate-bath coupling strength, initially symmetric or asymmetric peaks with varying spectral amplitudes may merge under weak dipole-dipole interactions, whereas strong dipole-dipole interactions are more likely to cause peak splitting. Moreover, we find that spectral features serve as highly sensitive indicators for distinguishing the geometric structures of aggregates, while also unveiling the critical role geometry plays in shaping non-Markovian behavior. This study not only deepens our understanding of the Markovian to non-Markovian transition but also provides a robust framework for optimizing and controlling quantum systems.