Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices

ArXi:2605.22097v1 Announce Type: cross Photonic quantum computing is a promising platform for scalable quantum machine learning, but designing effective hybrid architectures remains challenging under hardware and optimization constraints. Existing approaches rely on manually tuned architectures that fail to account for the collaboration between classical preprocessing, phase encoding, and photonic circuit structure, limiting both accuracy and hardware compatibility.