Photonics Breakthroughs 2024: Scalable Quantum Computing on a Single Photon Using Spatial Modes

High-dimensional quantum gates based on spatial mode of photons hold promise for advancing quantum computation. We demonstrate high-fidelity spatial mode quantum gates with fidelities up to 99.6%, using diffractive neural networks (DNNs). These gates are experimentally implemented with programmable phase layers in a compact and scalable device, enabling demonstrations like the Deutsch algorithm. Our approach showcases high reliability, adaptability, and potential for integration in quantum computation.

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Publication Details

Journal
IEEE photonics journal
Published
2025-10-15
DOI
https://doi.org/10.1109/jphot.2025.3621698
Citations
1
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
2.48
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article

Photonics Breakthroughs 2024: Scalable Quantum Computing on a Single Photon Using Spatial Modes

1 citations
IEEE photonics journal
Neural Networks and Reservoir Computing
2.48
article

Photonics Breakthroughs 2024: Scalable Quantum Computing on a Single Photon Using Spatial Modes

article en
1 citations

Abstract

High-dimensional quantum gates based on spatial mode of photons hold promise for advancing quantum computation. We demonstrate high-fidelity spatial mode quantum gates with fidelities up to 99.6%, using diffractive neural networks (DNNs). These gates are experimentally implemented with programmable phase layers in a compact and scalable device, enabling demonstrations like the Deutsch algorithm. Our approach showcases high reliability, adaptability, and potential for integration in quantum computation.

IEEE photonics journalVol. 17(6)
Wuhan National Laboratory for Optoelectronics (CN), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 6%
Neural Networks and Reservoir Computing
2.48
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Photonics Breakthroughs 2024: Scalable Quantum Computing on a Single Photon Using Spatial Modes · IEEE photonics journal (2025) | TGRS Research Map | TGRS