Deep Learning for Low-Latency, Quantum-Ready RF Sensing

arXiv:2404.17962v1 Announce Type: cross
Abstract: Recent work has shown the promise of applying deep learning to enhance software processing of radio frequency (RF) signals. In parallel, hardware developments with quantum RF sensors based on Rydberg atoms are breaking longstanding barriers in frequency range, resolution, and sensitivity. In this paper, we describe our implementations of quantum-ready machine learning approaches for RF signal classification. Our primary objective is latency: while deep learning offers a more powerful computational paradigm, it also traditionally incurs …

abstract arxiv breaking cs.ai cs.lg cs.pf cs.sy deep learning eess.sy hardware latency low paper processing quant-ph quantum radio resolution sensing sensitivity sensors software type work