arXiv AI By Yifei Zhang, Dong Chen, Fan Wang, Wenrui Zhang, Yan Chen, Dingding Han, Jianmin Yuan, Xiangjin Kong, Yu-Gang Ma

Program-Synthesis-Driven Autodesign of Universal Unitary Operators

Read the original on arXiv AI →

arXiv:2607. 10295v1 Announce Type: cross Abstract: We demonstrate that AI-driven program synthesis can autonomously discover fundamental strategies for decomposing unitary matrices in photonic networks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Machine Learning
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Efficient learning of bosonic Gaussian unitaries

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Universal Quantum Transformer

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COREM: Cosine-Relation Momentum Reshaping with Stateful Writeback

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

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