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arXiv:1605.07476

Optimal control of many-body non-equilibrium quantum thermodynamics

Niklas Rach, Simone Montangero, Mauro Paternostro

Published May 24, 2016• 2 citations
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Abstract

We demonstrate the effectiveness of quantum optimal control techniques in harnessing irreversibility generated by non-equilibrium processes, implemented in unitarily evolving quantum many-body systems. We address the dynamics of a finite-size quantum Ising model subjected to finite-time transformations, which unavoidably generate irreversibility. We show that work can be generated through such transformation by means of optimal controlled quenches, while quenching the degree of irreversibility to very low values, thus boosting the efficiency of the process and paving the way to a fully controllable non-equilibrium thermodynamics of quantum processes.

DOI
10.48550/arxiv.1605.07476

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We demonstrate the effectiveness of quantum optimal control techniques in harnessing irreversibility generated by non-equilibrium processes, implemented in unitarily evolving quantum many-body systems. We address the dynamics of a finite-size quantum Ising model subjected to finite-time transformations, which unavoidably generate irreversibility. We show that work can be generated through such transformation by means of optimal controlled quenches, while quenching the degree of irreversibility to very low values, thus boosting the efficiency of the process and paving the way to a fully controllable non-equilibrium thermodynamics of quantum processes.
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We use a reinforcement learning approach to reduce entropy production in a closed quantum system brought out of equilibrium. Our strategy makes use of an external control Hamiltonian and a policy gradient technique. Our approach bears no dependence on the quantitative tool chosen to characterize the degree of thermodynamic irreversibility induced by the dynamical process being considered, requires little knowledge of the dynamics itself, and does not need the tracking of the quantum state of the system during the evolution, thus embodying an experimentally nondemanding approach to the control of nonequilibrium quantum thermodynamics. We successfully apply our methods to the case of single- and two-particle systems subjected to time-dependent driving potentials.
We study optimal control strategies to optimize the relaxation rate towards the fixed point of a quantum system in the presence of a non-Markovian (NM) dissipative bath. Contrary to naive expectations that suggest that memory effects might be exploited to improve optimal control effectiveness, NM effects influence the optimal strategy in a non trivial way: we present a necessary condition to be satisfied so that the effectiveness of optimal control is enhanced by NM subject to suitable unitary controls. For illustration, we specialize our findings for the case of the dynamics of single qubit amplitude damping channels. The optimal control strategy presented here can be used to implement optimal cooling processes in quantum technologies and may have implications in quantum thermodynamics when assessing the efficiency of thermal micro-machines.
Abstract We study optimal control strategies to optimize the relaxation rate towards the fixed point of a quantum system in the presence of a non-Markovian (NM) dissipative bath. Contrary to naive expectations that suggest that memory effects might be exploited to improve optimal control effectiveness, NM effects influence the optimal strategy in a non trivial way: we present a necessary condition to be satisfied so that the effectiveness of optimal control is enhanced by NM subject to suitable unitary controls. For illustration, we specialize our findings for the case of the dynamics of single qubit amplitude damping channels. The optimal control strategy presented here can be used to implement optimal cooling processes in quantum technologies and may have implications in quantum thermodynamics when assessing the efficiency of thermal micro-machines.
Recent advances in coherent manipulation and control have led to new opportunities to study non-equilibrium dynamics in quantum many-body systems. Using a variety of experimental platforms ranging from cold atoms and ions to solid-state spin defects, small building blocks of fully controllable quantum systems can be assembled into a strongly interacting many-body system. With this approach, one can gain new insights into fundamental questions in basic science such as the mechanism of quantum thermalization or the existence of exotic phases of matter out of equilibrium. At the same time, a fully controllable large-scale quantum device has promising applications for high precision sensing, secure communication, and quantum information processing.\nThis thesis describes recent progress in engineering quantum dynamics that is robust against various imperfections such as environmental noise, disorder, or imprecise controls. We find that non-equilibrium quantum states of strongly interacting systems can be protected from imperfections upon appropriate external manipulations such as time-dependent periodic controls, engineered coherent or dissipative interactions, or an introduction of strong quenched disorder. Furthermore, under certain conditions, these imperfections can be utilized to stabilize non-trivial quantum states. Our results challenge conventional wisdom of statistical mechanics, shedding light on the microscopic mechanisms of thermalization.\nWe also discuss how engineered dynamics can be harnessed for applications such as quantum metrology, simulations, or information processing.
Achieving precise preparation of quantum many-body states is crucial for the practical implementation of quantum computation and quantum simulation. However, the inherent challenges posed by unavoidable excitations at critical points during quench processes necessitate careful design of control fields. In this work, we introduce a promising and versatile dynamic control neural network tailored to optimize control fields. We address the problem of suppressing defect density and enhancing cat-state fidelity during the passage across the critical point in the quantum Ising model. Our method facilitates seamless transitions between different objective functions by adjusting the optimization strategy. In comparison to gradient-based power-law quench methods, our approach demonstrates significant advantages for both small system sizes and long-term evolutions. We provide a detailed analysis of the specific forms of control fields and summarize common features for experimental implementation. Furthermore, numerical simulations demonstrate the robustness of our proposal against random noise and spin number fluctuations. The optimized defect density and cat-state fidelity exhibit a transition at a critical ratio of the quench duration to the system size, coinciding with the quantum speed limit for quantum evolution.