biostudies-literatureUnknown15(1)Yang ZPhotonics is promising to handle extensive vector multiplications in artificial intelligence (AI) techniques due to natural bosonic parallelism and high-speed information transmission. However, the dimensionality of current photonic linear operation is limited and tough to improve due to the complex beam interaction for implementing optical matrix operation and digital-analog conversions. Here, we propose a programmable and reconfigurable photonic linear vector machine with extreme scalability formed by a series of emitter-detector pairs as the independent basic computing units. The elemental values of two high-dimensional vectors are prepared on emitter-detector pairs by bit encoding and analog detecting method without requiring large-scale analog-to-digital converter or digital-to-analogLight, science & applications16https://www.ebi.ac.uk/biostudies/studies/S-EPMC12756334biostudies-literatureSUANPAN: scalable photonic linear vector machine.PMC12756334Qiao FLi CCui KFeng XRan YYe YWang JZhang WYang ZLi YNing CZChang-Hasnain CJHuang YSun HLiu FfalseSUANPAN: scalable photonic linear vector machine.Photonics is promising to handle extensive vector multiplications in artificial intelligence (AI) techniques due to natural bosonic parallelism and high-speed information transmission. However, the dimensionality of current photonic linear operation is limited and tough to improve due to the complex beam interaction for implementing optical matrix operation and digital-analog conversions. Here, we propose a programmable and reconfigurable photonic linear vector machine with extreme scalability formed by a series of emitter-detector pairs as the independent basic computing units. The elemental values of two high-dimensional vectors are prepared on emitter-detector pairs by bit encoding and analog detecting method without requiring large-scale analog-to-digital converter or digital-to-analog2026-01-01T00:00:00Z2026 Jan2026-06-09T05:11:30.906Z2026-06-09T03:08:00.89ZS-EPMC127563344147605110.1038/s41377-025-02059-7