No Arabic abstract
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 of the vibrational manifolds present in its chromophores. The study of linear spectra provides us with the basis to understand the dynamical features arising from the vibronic structure in non-linear spectra in a progressive fashion, starting from a microscopic model to finally performing an inhomogenous average. We show that the discreteness of the vibronic structure can be witnessed by probing the diagonal peaks of the non-linear spectra by means of a relative phase shift in the waiting time resolved signal. Moreover, we demonstrate the photon-echo and non-rephasing paths are sensitive to different harmonics in the vibrational manifold when static disorder is taken into account. Supported by analytical and numerical calculations, we show that nondiagonal resonances in the 2D spectra in the waiting time, further capture the discreteness of vibrations through a modulation of the amplitude without any effect in the signal intrinsic frequency. This fact generates a signal that is highly sensitive to correlations in the static disorder of the excitonic energy albeit protected against dephasing due to inhomogeneities of the vibrational ensemble.
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 results for the quantum dynamics of the excitons in the presence of nonadiabatic vibrational states in the Fenna-Matthews-Olson aggregate employing a environmental fluctuation spectral function derived from experiments. Assuming the prominent 180 cm$^{-1}$ vibrational mode to be underdamped, we observe, on the one hand, besides vibrational coherent oscillations between different excitation levels of the vibration also prolonged electronic coherent oscillations between the initially excited site and its neighbours. On the other hand, however, the underdamped vibrations provide additional channels for the excitation energy transfer and by this increase the transfer speed by up to $30%$ .
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 this hybrid system, we find that when certain sites of the FMO complex are subject to either the suppression of inter-site transitions or are entirely disconnected from the complex, the resulting variations in the excitation transfer rates through the complex can be monitored through the corresponding changes in the scattering spectra of the incident nanowire surface plasmons. We also find that these changes can be further enhanced by changing the ratio of plasmon-site couplings. The change of the Fano lineshape in the scattering spectra further reveals that site 5 in the FMO complex plays a distinct role from other sites. Our results provide a feasible way, using single photons, to detect mutation-induced, or bleaching-induced, local defects or modifications of the FMO complex, and allows access to both the local and global properties of the excitation transfer in such systems.
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 a generalized quantum algorithm to simulate any dynamical process represented by either the operator sum representation or the Lindblad master equation. We then demonstrate the quantum algorithm by simulating the dynamics of the Fenna-Matthews-Olson (FMO) complex on the IBM QASM quantum simulator. This work represents a first demonstration of a quantum algorithm for open quantum dynamics with a moderately sophisticated dynamical process involving a realistic biological structure. We discuss the complexity of the quantum algorithm relative to the classical method for the same purpose, presenting a decisive query complexity advantage of the quantum approach based on the unique property of quantum measurement. An accurate yet tractable quantum algorithm for the description of complex open quantum systems (like the FMO complex) has a myriad of significant applications from catalytic chemistry and correlated materials physics to descriptions of hybrid quantum systems.
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 novel uses of hardware. Special focus is placed on classifying algorithms -- most of which are underpinned by a few key ideas -- in order to understand their fundamental strengths and limitations. Although algorithms have proliferated, progress resulting from novel hardware use appears to be more clear-cut than from algorithms alone, partly due to the lack of widely used sampling measures.