Quantum Reservoir Computing with Neutral Atoms on a Small, Complex, Medical Dataset
Centre for Quantum Information, Simulation；Algorithms, The University of Western Australia, Perth, Australia；Centre for Respiratory Health, University of Western Australia, Perth, WA, Australia；School of Medicine \& Pharmacology, University of Western Australia, Perth, Western Australia, Australia；Dept of Respiratory Medicine, Fiona Stanley Hospital, Perth, WA, Australia；Pawsey Supercomputing Research Centre, Perth, WA, 6152, Australia；QuEra Computing Inc., 1284 Soldiers Field Road, Boston, MA, 02135, USA；School of Physics, Mathematics；Computing, The University of Western Australia, 35 Stirling Hwy, Crawley WA, 6009, Australia
Luke Antoncich, Yuben Moodley, Ugo Varetto, Jingbo Wang, Jonathan Wurtz, Jing Chen, Pascal Jahan Elahi, Casey R. Myers
Biomarker-based prediction of clinical outcomes is challenging due to nonlinear relationships, correlated features, and the limited size of many medical datasets. Classical machine-learning methods can struggle under these conditions, motivating the search for alternatives. In this work, we investigate quantum reservoir computing (QRC), using both noiseless emulation and hardware execution on the neutral-atom Rydberg processor \textit{Aquila}. We evaluate performance with six classical machine-learning models and use SHAP to generate feature subsets. We find that models trained on emulated quantum features achieve mean test accuracies comparable to those trained on classical features, but have higher training accuracies and greater variability over data splits, consistent with overfitting. When comparing hardware execution of QRC to noiseless emulation, the models are more robust over different data splits and often exhibit statistically significant improvements in mean test accuracy. This combination of improved accuracy and increased stability is suggestive of a regularising effect induced by hardware execution. To investigate the origin of this behaviour, we examine the statistical differences between hardware and emulated quantum feature distributions. We find that hardware execution applies a structured, time-dependent transformation characterised by compression toward the mean and a progressive reduction in mutual information relative to emulation.
Medical Imaging Classification with Cold-Atom Reservoir Computing using Auto-Encoders and Surrogate-Driven Training
Instituto de Telecomunicações, Dept. of Electrical and Computer Engineering, University of Coimbra, Portugal（葡萄牙科英布拉大学电信研究所，电气与计算机工程系）；ISR - Institute of Systems and Robotics, Dept. of Electrical and Computer Engineering, University of Coimbra, Portugal（葡萄牙科英布拉大学系统与机器人研究所，电气与计算机工程系）；CFisUC, Department of Physics, University of Coimbra, Portugal（葡萄牙科英布拉大学物理系，CFisUC）
Quantum Reservoir Computing: Recent Advances and Future Directions
Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg（安全、可靠性与信任跨学科中心（SnT），卢森堡大学）；School of Computing, Engineering and Digital Technologies, Teesside University（计算、工程与数字技术学院，泰赛大学）
Analog neutral-atom for in-memory processing in quantum reservoir computing
Università degli Studi di Milano（米兰大学）；Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) UIB-CSIC（跨学科物理与复杂系统研究所（IFISC）巴利阿里群岛大学-西班牙国家研究委员会）；Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche（意大利国家研究委员会光子学与纳米技术研究所）
Transforming Traditional Neural Networks into Neuromorphic Quantum-Cognitive Models: A Tutorial with Applications
Artificial Intelligence and Cyber Futures Institute, Charles Sturt University（查尔斯斯特大学人工智能与网络未来学院）；Cyber Futures Institute, Charles Sturt University（查尔斯斯特大学网络未来学院）
Reservoir-independent lossless charging and protected storage of an open quantum battery
Qatar Center for Quantum Computing, College of Science and Engineering, Hamad Bin Khalifa University（卡塔尔量子计算中心，科学与工程学院，哈马德·本·哈利法大学）；The University of Adelaide（阿德莱德大学）
A scalable chip-integrated single-photon source array based on 50 individually addressable neutral atoms
University of Science and Technology of China（中国科学技术大学）；CAS Center for Excellence in Quantum Information and Quantum Physics（中国科学院量子信息与量子物理学前沿卓越中心）；Laboratory of Quantum Information（量子信息实验室）
