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arXiv:1901.03118 · International Journal of Quantum Information

Quantum simulation dynamics and circuit synthesis of FMO complex on an NMR quantum computer

M. Mahdian, H. Davoodi Yeganeh, A. Dehghani

Published Sep 1, 2020• 5 citations
arXivHTMLPDF

Abstract

Recently, the dynamics simulation of light-harvesting complexes as an open quantum system, in the weak and strong coupling regimes, has received much attention. In this paper, we investigate a digital quantum simulation approach of the Fenna–Matthews–Olson (FMO) photosynthetic pigment-protein complex surrounded with a Markovian bath, i.e. memoryless, based on a nuclear magnetic resonance (NMR) quantum computer. For this purpose, we apply the decoupling (recoupling) method, which is turn off (on) the couplings, and also Solovay–Kitaev techniques to decompose Hamiltonian and Lindbladians into efficient elementary gates on an NMR simulator. Finally, we design the quantum circuits for the unitary and nonunitary part due to the system-environment interactions of the open system dynamics.

DOI
10.1142/s0219749920500343

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Recently, the dynamics simulation of light-harvesting complexes as an open quantum system, in the weak and strong coupling regimes, has received much attention. In this paper, we investigate a digital quantum simulation approach of the Fenna–Matthews–Olson (FMO) photosynthetic pigment-protein complex surrounded with a Markovian bath, i.e. memoryless, based on a nuclear magnetic resonance (NMR) quantum computer. For this purpose, we apply the decoupling (recoupling) method, which is turn off (on) the couplings, and also Solovay–Kitaev techniques to decompose Hamiltonian and Lindbladians into efficient elementary gates on an NMR simulator. Finally, we design the quantum circuits for the unitary and nonunitary part due to the system-environment interactions of the open system dynamics.
The simulation dynamics of light-harvesting complexes as open quantum systems in the weak and strong coupling regimes has been recently attended. In this paper, we investigate digital approach to quantum dynamics simulation of photosynthetic Fenna-Matthew-Olson (FMO) complex in contact with a Markovian bath, i.e., memoryless, with the nuclear spin-based quantum simulator. For this purpose, we use recoupling and decoupling method on nuclear magnetic resonance(NMR) quantum computation and Solovay-Kitaev decomposition strategy for single-qubit channels. Finally we use near-term quantum computer that developed by Rigetti to implement circuits. The results shows an efficient quantum simulation of photosynthesis system.
The application of the theory of open quantum systems in biological processes such as photosynthetic complexes, has recently received renewed attention. In this paper, a quantum algorithm is presented for simulation of arbitrary Markovian dynamics of the FMO complex exist in photosynthesis using a 'universal set ' of one-parameter semigroup of generators. We investigate the detailed constitution of each generator that obtain from spectral decomposition of the Gorini-Kossakowski-Sudarshan (GKS) matrix by using of linear combination and unitary conjugation. Also, we design a quantum circuit for implementing of these generators.
Open quantum system approaches are widely used in the description of physical, chemical and biological systems. A famous example is electronic excitation transfer in the initial stage of photosynthesis, where harvested energy is transferred with remarkably high efficiency to a reaction center. This transport is affected by the motion of a structured vibrational environment, which makes simulations on a classical computer very demanding. Here we propose an analog quantum simulator of complex open system dynamics with a precisely engineered quantum environment. Our setup is based on superconducting circuits, a well established technology. As an example, we demonstrate that it is feasible to simulate exciton transport in the Fenna–Matthews–Olson photosynthetic complex. Our approach allows for a controllable single-molecule simulation and the investigation of energy transfer pathways as well as non-Markovian noise-correlation effects.
The Fenna-Mathews-Olson (FMO) complex present in green sulfur bacteria is known to mediate the transfer of excitation energy between light-harvesting chlorosomes and membrane-embedded bacterial reaction centers. Due to the high efficiency of this transport process, it is an extensively studied pigment-protein complex system with the eventual aim of modeling and engineering similar dynamics in other systems and using it for real-time application. Some studies have attributed the enhancement of transport efficiency to wavelike behavior and non-Markovian quantum jumps resulting in long-lived and revival of quantum coherence, respectively. Since dynamics in these systems reside in the quantum-classical regime, quantum simulation of such dynamics will help in exploring the subtle role of quantum features in enhancing the transport efficiency, which has remained unsettled. Discrete simulation of the dynamics in the FMO complex can help in efficient engineering of the heat bath and controlling the environment with the system. In this work, using the discrete quantum jump model we show and quantify the presence of higher non-Markovian memory effects in specific site pairs when internal structures and environmental effects are in favor of faster transport. As a consequence, our study leans toward the connection between non-Markovianity in quantum jumps with the enhancement of transport efficiency.
Abstract Simulating the behaviour of complex quantum systems is impossible on classical supercomputers due to the exponential scaling of the number of quantum states with the number of particles in the simulated system. Quantum computers aim to break through this limit by using one quantum system to simulate another quantum system. Although in their infancy, they are a promising tool for applied fields seeking to simulate quantum interactions in complex atomic and molecular structures. Here, we show an efficient technique for transpiling the unitary evolution of quantum systems into the language of universal quantum computation using the IBM quantum computer and show that it is a viable tool for compiling near-term quantum simulation algorithms. We develop code that decomposes arbitrary 3-qubit gates and implement it in a quantum simulation first for a linear ordered chain to highlight the generality of the approach, and second, for a complex molecule. We choose the Fenna-Matthews-Olsen (FMO) photosynthetic protein because it has a well characterised Hamiltonian and presents a complex dissipative system coupled to a noisy environment that helps to improve the efficiency of energy transport. The method can be implemented in a broad range of molecular and other simulation settings.
The unique capability of quantum mechanics to evolve alternative possibilities in parallel is appealing and over the years a number of quantum algorithms have been developed offering great computational benefits. Systems coupled to the environment lose quantum coherence quickly and realization of schemes based on unitarity might be impossible. Recent discovery of room temperature quantum coherence in light harvesting complexes opens up new possibilities to borrow concepts from biology to use quantum effects for computational purposes. While it has been conjectured that light harvesting complexes such as the Fenna-Matthews-Olson (FMO) complex in the green sulfur bacteria performs an efficient quantum search similar to the quantum Grover's algorithm the analogy has yet to be established. In this work we show that quantum dissipation plays an essential role in the quantum search performed in the FMO complex and it is fundamentally different from known algorithms. In the FMO complex not just the optimal level of phase breaking is present to avoid both quantum localization and Zeno trapping but it can harness quantum dissipation as well to speed the process even further up. With detailed quantum calculations taking into account both phase breaking and quantum dissipation we show that the design of the FMO complex has been evolutionarily optimized and works faster than pure quantum or classical-stochastic algorithms. Inspired by the findings we introduce a new computational concept based on decoherent quantum evolution. While it is inspired by light harvesting systems, the new computational devices can also be realized on different material basis opening new magnitude scales for miniaturization and speed.