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• W3209013527 abstract "Developments in ultrafast-spectroscopy techniques have revealed notably long-lived quantum coherence between electronic states in Fenna–Matthews–Olson complex bacteriochlorophylls, a group of molecules setting a nanoscale structure responsible of the coherent energy transfer in the photosynthetic process of green sulfur bacteria. Despite the experimental advances, such a task should normally be complemented with physical computer simulations to understand its complexity. Several methods have been explored to model this quantum phenomenon, mainly using the quantum open systems theory as a first approach. The traditional methods used in this approach do not take into account the memory effects of the surroundings, which is commonly approximated as a phonon bath on thermal equilibrium. To surpass such an approximation, this article applies the Hierarchical Equations of Motion method, a non-markovian approach also used to analyze the dynamic of such a complex, for the modeling of the system evolution. We perform a parametric analysis about some physical features in the quantum regime involved during the quantum excitation process in order to get a comprehension about its non-trivial dependence on operation parameters. Thus, the analysis is conducted in terms of some relevant physical parameters in the system to track the complex global behavior in aspects as coherence, entanglement, decoherence times, transference times, and efficiency of the main process of energy capturing. As a complementary analysis from the derived outcomes, we compare those features for two different species as a suggestive possible roadmap to track genetic differences in the photosynthetic performance of the complex through its biological nature." @default.
• W3209013527 created "2021-11-08" @default.
• W3209013527 creator A5055558957 @default.
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• W3209013527 date "2020-09-17" @default.
• W3209013527 modified "2023-10-01" @default.
• W3209013527 title "Parametric Mapping of Quantum Regime in Fenna–Matthews–Olson Light-Harvesting Complexes: A Synthetic Review of Models, Methods and Approaches" @default.
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• W3209013527 doi "https://doi.org/10.3390/app10186474" @default.
• W3209013527 hasPublicationYear "2020" @default.
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