We discuss the case of a harmonic oscillator-based quantum battery strongly coupled to a highly non-Markovian thermal reservoir via the quantum charger described by the Caldeira–Leggett model. The coupling between the reservoir and the battery serves as a control parameter for the system. We consider the system to stay in the strongly underdamped regime. Within the framework of the open-loop approach, we determine the optimal shape of control for the battery charging work and then restore the control coupling characteristics of QB in the Hamiltonian for the alternative cases of low and high temperatures. Ultimately, we discuss some possible ways to develop our model for the feedback algorithms.
We discuss the case of a harmonic oscillator-based quantum battery strongly coupled to a highly non-Markovian thermal reservoir via the quantum charger described by the Caldeira–Leggett model. The coupling between the reservoir and the battery serves as a control parameter for the system. We consider the system to stay in the strongly underdamped regime. Within the framework of the open-loop approach, we determine the optimal shape of control for the battery charging work and then restore the control coupling characteristics of QB in the Hamiltonian for the alternative cases of low and high temperatures. Ultimately, we discuss some possible ways to develop our model for the feedback algorithms.
Abstract We propose a scheme to achieve a nonreciprocal quantum battery (QB) in the non-Hermitian (NH) system, which can overcome the intrinsic dissipation and reverse flow constraints. The design is based on a charger and a battery, which are coherently coupled and jointly interact with a bad cavity. By introducing the auxiliary bad cavity and exploiting the nonreciprocal condition, this model can harness the environmental dissipation to suppress the reverse energy transfer. Under resonant conditions, we have achieved a four ratio of the battery energy to the charger energy; in contrast, this ratio is significantly reduced under large detuning. Through damping optimization, high efficiency of the short-time charging power is attained. In comparison to the fully nonreciprocal scheme, the QB operating at the exceptional point (EP) exhibits greater resilience to parameter fluctuations. These findings highlight the potential of NH quantum engineering for advancing QB technology, particularly in regimes involving directional energy transfer, controlled dissipation, and entropy management in open quantum systems.
Quantum batteries, as highly efficient energy storage devices, have garnered significant research interest. A key challenge in their development is to maximize the extractable energy (ergotropy) when operating within a finite-temperature reservoir. To address this, we applied quantum feedback control to the charger and investigated the effects of fermionic and bosonic thermal reservoirs on the performance of quantum batteries, including stored energy, ergotropy, and charging efficiency, in an open environment. Our findings reveal that, regardless of the type of thermal reservoir, the system exhibits optimal charging parameters. In particular, in a fermionic thermal reservoir, increasing the environmental temperature enhances battery performance, enabling stable and efficient charging. In contrast, within a bosonic thermal reservoir, higher temperatures hinder energy storage and extraction, significantly reducing charging efficiency. Additionally, we explored the impact of battery size and found that, under a fermionic reservoir, increasing the battery size appropriately can further improve performance.
In the field of quantum thermodynamics, optimizing the performance of quantum battery (QB) under environmental effects remains a primary research interest. However, environmental control remains challenging due to its high-dimensional degrees of freedom, particularly in the non-Markovian regimes. This work investigates the charging dynamics of a QB model subjected to a tunable non-Markovian environment. We show that a controllable non-Markovian setting can be exploited to improve the QB's primary figure of merit. Specifically, we show that by tuning the relative ratio of QB-charger coupling strength and charger-bath coupling strength, the maximum dynamic values of the charging power, energy storage, and work extraction of QB can be significantly increased. Our findings suggest that employing non-Markovian effects in a tunable way offers a promising avenue for enhancing the performance of quantum thermodynamic devices, and sheds new light on the intersection between the reservior engneering and quantum thermodynamics.
Abstract Quantum control allows us to address the problem of engineering quantum dynamics for special purposes. While recently the field of quantum batteries has attracted much attention, optimization of their charging has not benefited from the quantum control methods. Here we fill this gap by using an optimization method. We apply for the first time the convergent iterative method for the control of the population of a bipartite quantum system in two cases, starting with a qubit-qubit case. The quantum charger-battery system is considered here, where the energy is pumped into the charger by an external classical electromagnetic field. Secondly, we systematically extend our investigation to a second case involving two harmonic oscillators in the Gaussian regime, presenting an original formulation of the method. In both cases, the charger is considered to be an open dissipative system, as its interaction with the drive may require a more pronounced exposure to general interaction with environment. A key consideration in our optimization strategy is the practical concern of turning the charging external field on and off. We find that optimizing the pulse shape yields a substantial enhancement in both the power and efficiency of the charging process compared to a sinusoidal drive. The harmonic oscillator configuration of quantum batteries is particularly intriguing, as the optimal driving pulse remains effective regardless of the environmental temperature. This study introduces a novel approach to quantum battery charging optimization, opening avenues for enhanced performance in real-world applications.
We propose a scheme to achieve a nonreciprocal quantum battery (QB) in the non-Hermitian (NH) system, which can overcome the intrinsic dissipation and reverse flow constraints. The design is based on a charger and a battery, which are coherently coupled and jointly interact with a bad cavity. By introducing the auxiliary bad cavity and exploiting the nonreciprocal condition, this model can harness the environmental dissipation to suppress the reverse energy transfer. Under resonant conditions, we have achieved a four ratio of the battery energy to the charger energy; in contrast, this ratio is significantly reduced under large detuning. Through damping optimization, high efficiency of the short-time charging power is attained. In comparison to the fully nonreciprocal scheme, the QB operating at the exceptional point (EP) exhibits greater resilience to parameter fluctuations. These findings highlight the potential of NH quantum engineering for advancing QB technology, particularly in regimes involving directional energy transfer, controlled dissipation, and entropy management in open quantum systems.
Controlling the charging process of a quantum battery involves strategies to efficiently transfer, store, and retain energy, while mitigating decoherence, energy dissipation, and inefficiencies caused by surrounding interactions. We develop a model to study the charging process of a quantum battery in an open quantum setting, where the battery interacts with a charger and a structured reservoir. To overcome the limitations of static charging protocols, a reinforcement learning (RL) charging strategy is proposed, which utilizes the deep deterministic policy gradient algorithm alongside long short-term memory (LSTM) networks. The LSTM networks enable the RL model to capture temporal correlations driven by non-Markovian dynamics, facilitating a continuous, adaptive charging strategy. The RL protocols consistently outperform conventional fixed heuristic strategies by real-time controlling the driving field amplitude and coupling parameters. By penalizing battery-to-charger backflow in the reward function, the RL-optimized charging strategy promotes efficient unidirectional energy transfer from charger to battery, achieving higher and more stable extractable work. The proposed RL controller would provide a framework for designing efficient charging schemes in broader configurations and multi-cell quantum batteries.