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We investigate, using the Hierarchy method, the entanglement and the excitation transfer efficiency of the Fenna-Matthews-Olson complex under two different local modifications: the suppression of transitions between particular sites and localized changes to the protein environment. We find that inhibiting the connection between the site-5 and site-6, or disconnecting site-5 from the complex completely, leads to an dramatic enhancement of the entanglement between site-6 and site-7. Similarly, the transfer efficiency actually increases if site-5 is disconnected from the complex entirely. We further show that if site-5 and site-7 are conjointly removed, the efficiency falls. This suggests that while not contributing to the transport efficiency in a normal complex, site-5 introduces a redundant transport route in case of damage to site-7. Our results suggest an overall robustness of excitation energy transfer in the FMO complex under mutations, local defects, and other abnormal situations.
Based entirely upon actual experimental observations on electron-phonon coupling, we develop a theoretical framework to show that the lowest energy band of the Fenna- Matthews-Olson (FMO) complex exhibits observable features due to the quantum nature
We show that the efficient excitation energy transfer in the Fenna-Matthews-Olson molecular aggregate under realistic physiological conditions is fueled by underdamped vibrations of the embedding proteins. For this, we present numerically exact resul
We study theoretically the bio-sensing capabilities of metal nanowire surface plasmons. As a specific example, we couple the nanowire to specific sites (bacteriochlorophyll) of the Fenna-Matthews-Olson (FMO) photosynthetic pigment protein complex. In
Using quantum algorithms to simulate complex physical processes and correlations in quantum matter has been a major direction of quantum computing research, towards the promise of a quantum advantage over classical approaches. In this work we develop
Equilibrium sampling of biomolecules remains an unmet challenge after more than 30 years of atomistic simulation. Efforts to enhance sampling capability, which are reviewed here, range from the development of new algorithms to parallelization to nove