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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.
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
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 cha
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
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
Gradient-based algorithms, popular strategies to optimization problems, are essential for many modern machine-learning techniques. Theoretically, extreme points of certain cost functions can be found iteratively along the directions of the gradient.