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Quantum Coherence and Its Signatures in Extended Quantum Systems

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journal contribution
posted on 2020-05-25, 04:48 authored by Rajesh Dutta, Biman Bagchi
Quantum coherence controls almost every aspect of static and dynamic response of a strongly correlated quantum system, although details of this control have not been elucidated in many cases. We find that, in the presence of a significant static off-diagonal coupling, quantum coherence can survive much longer than the bath correlation time in a noisy environment. In the presence of time correlated noise (non-Markovian limit), coherence could propagate through the excited bath states, and this plays a nontrivial role in giving rise to a noncanonical temperature dependence of population distribution in an extended conjugated polymer-like system. The quantum coherence through the excited bath states vanishes in the high temperature limit, giving rise to the equilibrium Boltzmann distribution. Second, we discuss a role of quantum coherence in exciton localization that bears resemblance to Anderson localization. Calculations have been carried out not only with a chain of conjugated polymer but also with dimer and trimer subunits of the Fenna–Matthews–Olson (FMO) complex. We derive an analytical expression of the relation between steady state coherence and excitionic population distribution. We analytically showed that steady state coherence in equilibrium bath states is governed by interchromophoric coupling (J) whereas coherence in excited bath states is dictated by fluctuation strength (Vd) for the spatially correlated bath model. For the spatially uncorrelated bath model, we observe that at the low temperature limit coherence in the excited bath states dominates over coherence in equilibrium bath states and vice versa. In the study of the localization problem, we analytically show that, in the limit of a negligibly small fluctuation rate (bd), the diffusion coefficient is exactly proportional to the fluctuation rate, leading to complete breakdown of the Haken–Strobl–Silbey Markovian prediction.

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