Feedback algorithms can be efficiently applied to control the basic characteristics of quantum batteries (QBs): the ergotropy, the charging power, the storage capacity and others. We invent here two alternative approaches, target repeller and speed gradient feedback, to maximize the ergotropy for bosonic types of single-qubit based quantum batteries. We demonstrate the achievability of the control goal and discuss some pros and cons of both proposed algorithms.
Feedback algorithms can be efficiently applied to control the basic characteristics of quantum batteries (QBs): the ergotropy, the charging power, the storage capacity and others. We invent here two alternative approaches, target repeller and speed gradient feedback, to maximize the ergotropy for bosonic types of single-qubit based quantum batteries. We demonstrate the achievability of the control goal and discuss some pros and cons of both proposed algorithms.
Quantum batteries (QBs), acting as energy storage devices, have potential applications in future quantum science and technology. However, the QBs inevitably losses energy due to their interaction with environment. How to enhance the performance of the QBs in the open-system case remains an important challenge. Here we propose a scheme to realize the driven-dissipative QBs in atom-waveguide-QED systems and demonstrate significant improvements in both the stored energy and extractable work (ergotropy) of the QBs via feedback control. For a single-atom QB, we show that combining the measurement and coherent feedback controls enables nearly perfect stable charging under the weak coherent driving. For the QB array, the measurement-based feedback allows us to control different dynamical phases in the thermodynamic limit: (i) a continuous boundary time-crystal phase, where persistent periodic energy charge-discharge oscillations emerge despite the presence of the dissipation into the waveguide, and (ii) two stationary phases -- one reaches full charge while the other maintains only small energy storage. This work broadens the scope of driven-dissipative QBs and provides practical strategies for enhancing their performance.
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.
Ergotropy--a key figure of merit for quantum battery (QB) performance--plays a crucial role. However, the dynamics and physical mechanisms governing ergotropy evolution remain open challenges. Here, we investigate the ergotropy of a general QB model and find that the charging process is accompanied by the variation and inversion of the energy level populations. In the absence of population inversion, the ergotropy is fully consistent with coherent ergotropy; in local and global population inversion, it is determined by both coherent and incoherent ergotropy. Via random sampling of quantum states and Hamiltonians, we show that coherence and the participation ratio enhance coherent ergotropy, whereas incoherent ergotropy--whether enhanced, unchanged, or suppressed--depends on diagonal entropy, the participation ratio, and energy level population ordering. We demonstrate that the ergotropy lower bound is incoherent ergotropy, the upper bound is the QB stored energy, and enhanced QB purity suppresses locked energy and boosts charging efficiency. Furthermore, we use the Tavis-Cummings (TC) and Jaynes-Cummings (JC) batteries as paradigms to validate our findings. Our work elucidates ergotropy underlying mechanisms in general QBs and establishes a rigorous framework for optimizing ergotropy and charging efficiency, paving the way for high-performance quantum energy-storage devices.
The performance of open quantum batteries (QBs) is severely limited by decoherence due to the interaction with the surrounding environment. So, protecting the charging processes against decoherence is of great importance for realizing QBs. In this work we address this issue by developing a charging process of a qubit-based open QB composed of a qubit-battery and a qubit-charger, where each qubit moves inside an independent cavity reservoir. Our results show that, in both the Markovian and non-Markovian dynamics, the charging characteristics, including the charging energy, efficiency and ergotropy, regularly increase with increasing the speed of charger and battery qubits. Interestingly, when the charger and battery move with higher velocities, the initial energy of the charger is completely transferred to the battery in the Markovian dynamics. In this situation, it is possible to extract the total stored energy as work for a long time. Our findings show that open moving-qubit systems are robust and reliable QBs, thus making them a promising candidate for experimental implementations.
Quantum batteries utilize nonclassical resources to achieve charging speed and energy storage performances that surpass classical thermodynamic limits. However, the practical realization of quantum batteries is often constrained by the inevitable environment-induced dissipation of both stored ergotropy and coherence. To actively counteract these losses, we propose a dual-channel coherence framework that exploits dark-state protection to stabilize ergotropy. We conduct, for the first time, an investigation of the synergistic interplay between internal charger coherence and reservoir squeezing, the latter acting as a source of external coherence. In the resource-efficient regime where charger and battery sizes are comparable, our study shows that internal charger coherence and reservoir squeezing jointly enhance the transient charging power. Crucially, initial charger coherence is the fundamental resource for maximizing and stabilizing steady-state ergotropy through dark-state protection. Our analysis reveals that these advantages are driven by the buildup of local battery coherence, which emerges from the integration of both internal and external coherence sources. These results offer a robust pathway for high-power, stabilized energy storage in quantum architectures.
We systematically investigate the performance of many-body quantum batteries (QBs) with open boundary conditions (OBCs) and periodic boundary conditions (PBCs). Specifically, we apply a general approach to study the effects of interactions and boundary conditions on ergotropy and power in the Ising-, XXX-, XXZ-, and XYZ-type QBs. We find that the Ising and XYZ models can serve as viable candidates for illustrating the superiority of the collective charging proposal. For these two types of QBs, the interactions between the cells play an important role in the enhancement of ergotropy and power. Moreover, the boundary conditions significantly influence the performance of the QBs. For a smaller QB system, the QB with PBCs outperforms the QB with OBCs. Finally, we show the scaling relationships of the maximum power for the QBs and find that the superiority of collective charging for the Ising- and XYZ-type QBs with appropriate boundary conditions can be maintained in infinite QB systems.