Measurement-Informed Safe Reinforcement Learning for Quantum Battery Charging via Harmonic-Syndrome Diagnostics and BMS Constraints
Abstract: Quantum batteries promise ultrafast energy storage but are highly sensitive to noise, drift, and hardware constraints, making safe high-performance charging a central challenge for noisy intermediate-scale quantum devices. We propose a measurement-informed safe control framework that couples harmonic-spectrum-based syndrome diagnostics—H2/H1, H3/H1, and frequency drift—with a battery management system (BMS)-constrained curriculum reinforcement learning (RL) policy. […]