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Efficient Classification of Photonic Quantum States with Quantum Kernel Method

Shintaro Ooka, Keitaro Anai, Akimoto Nakayama, Hiroko Tomoda, Yuto Morohoshi, Yohji Chin, Shigehito Miki, Masahiro Yabuno, Hirotaka Terai, Peter van Loock, Kosuke Mitarai, Shuntaro Takeda

Published Jan 1, 2026• 0 citations
Publisher

Abstract

We propose and experimentally demonstrate a quantum-kernel-based machine learning scheme to efficiently classify photonic quantum states. This scheme leads to a practical quantum advantage in analyzing large-scale quantum data in the future.
DOI
10.1364/cleo_fs.2026.fm3a.5

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