Quantum state-agnostic work extraction (almost) without dissipation

We investigate work extraction protocols designed to transfer the maximum possible energy to a battery using sequential access to $N$ copies of an unknown pure qubit state. The core challenge is designing interactions to optimally balance two competing goals: charging of the battery optimally using the qubit in hand, and acquiring more information by qubit to improve energy harvesting in subsequent rounds. Here, we leverage exploration-exploitation trade-off in reinforcement learning to develop adaptive strategies achieving energy dissipation that scales only poly-logarithmically in $N$. This represents an exponential improvement over current protocols based on full state tomography.

@article{lumbreras2025_2505.09456,
  title={ Quantum state-agnostic work extraction (almost) without dissipation },
  author={ Josep Lumbreras and Ruo Cheng Huang and Yanglin Hu and Mile Gu and Marco Tomamichel },
  journal={arXiv preprint arXiv:2505.09456},
  year={ 2025 }
}