3 papers
quant-ph2025
Reinforcement Learning for Charging Optimization of Inhomogeneous Dicke Quantum Batteries
Xiaobin Song, Siyuan Bai, Da-Wei Wang +4
Charging optimization is a key challenge to the implementation of quantum batteries, particularly under inhomogeneity and partial observability. This paper employs reinforcement le…
quant-ph2025
On the Design of Expressive and Trainable Pulse-based Quantum Machine Learning Models
Han-Xiao Tao, Xin Wang, Re-Bing Wu
Pulse-based Quantum Machine Learning (QML) has emerged as a novel paradigm in quantum artificial intelligence due to its exceptional hardware efficiency. For practical applications…
quant-ph2025
Predictive Performance of Deep Quantum Data Re-uploading Models
Xin Wang, Han-Xiao Tao, Re-Bing Wu
Quantum machine learning models incorporating data re-uploading circuits have garnered significant attention due to their exceptional expressivity and trainability. However, their…