2020
DOI: 10.1103/physreva.102.052206
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Discrete memory kernel for multitime correlations in non-Markovian quantum processes

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Cited by 24 publications
(10 citation statements)
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“…The only information kept about the environment is its correlation function, or equivalently its spectral density. The evolution of the system's density matrix can then be described, for example, by an approximate weak-coupling master equation [1] or exactly using a process tensor [17] or a tensor network representation of the influence functional as in the time-evolving matrix product operator (TEMPO) method [18,19]. Indeed, a process tensor can be extracted from the TEMPO method [20] and this can lead to still more efficient calculations [21].…”
Section: Etmentioning
confidence: 99%
“…The only information kept about the environment is its correlation function, or equivalently its spectral density. The evolution of the system's density matrix can then be described, for example, by an approximate weak-coupling master equation [1] or exactly using a process tensor [17] or a tensor network representation of the influence functional as in the time-evolving matrix product operator (TEMPO) method [18,19]. Indeed, a process tensor can be extracted from the TEMPO method [20] and this can lead to still more efficient calculations [21].…”
Section: Etmentioning
confidence: 99%
“…This approach has been popular in the community of mixed quantum-classical dynamics, including problems of nonadiabatic quantum dynamics (beyond the Born-Oppenheimer approximation) and coupling classical and quantum degrees of freedom, where various approximations to the quantum-classical Liouville equation can also be derived [217]. Starting from generalized versions of the master equation, one has to construct an efficient procedure for calculating memory kernels, including non-Markovian cases [218]. Nonperturbative approaches [219][220][221][222] can provide here superior efficiency and accuracy improvements, see, e.g., [223] where they were tested on the Fenna-Matthews-Olson (FMO) light-harvesting complexes important in the analysis of photosynthetic systems [224][225][226][227].…”
Section: Modelling With Nonlocality In Data-driven Environmentsmentioning
confidence: 99%
“…The only information kept about the environment is its correlation function -or equivalently its spectral density. The evolution of the system's density matrix can then be described for example, by an approximate weak coupling master equation [1], or exactly using a process tensor [17] or a tensor network representation of the influence functional as in the Time Evolving Matrix Product Operator (TEMPO) method [18,19]. Indeed, a process tensor can be extracted from the TEMPO method [20] and this can lead to still more efficient calculations [21].…”
Section: S S S S E E (A) (B)mentioning
confidence: 99%