High-dimensional non-Abelian holonomy in integrated photonics
Non-Abelian holonomy is known for the robust holonomic unitary behavior exhibited. The associated non-Abelian geometric phase is a promising approach for implementing topologically protected computation. But its realization in application-abundant platforms has been largely elusive. In particular, the observation of universal high-order matrices is difficult due to challenges from increasing the dimensions of degenerate subspace. Here we realize a high-dimensional non-Abelian holonomic device on an integrated multilayer silicon nitride platform, which is compatible with the complementary-metal-oxide-semiconductor process. High dimensional (up to 6), broadband (> 100 nm operating bandwidth), and ultra-compact volume non-Abelian holonomy unitary matrices of arbitrary special orthogonal group are observed, and M × N linear holonomic computation architecture is experimentally realized through singular value decomposition. Our work provides a paradigm for versatile applications of non-Abelian geometric phase for both classical and quantum realms.
Authors
- Guancong Ma (ORCID: https://orcid.org/0000-0003-3652-4351)
- Qiang Zhou (ORCID: https://orcid.org/0000-0001-7099-1995)
- Yikai Su (ORCID: https://orcid.org/0000-0002-1526-8187)
- Guang‐Can Guo (ORCID: https://orcid.org/0000-0003-3771-9185)
- Youlve Chen
- Guo-Huai Wang
- Jinlong Xiang (ORCID: https://orcid.org/0000-0002-3047-3461)
- Xuhan Guo (ORCID: https://orcid.org/0000-0002-4891-0201)
- Yunru Fan (ORCID: https://orcid.org/0009-0003-8830-6636)
- An He (ORCID: https://orcid.org/0000-0001-9103-633X)
- Gulliver Larsonneur
- Xu‐Lin Zhang (ORCID: https://orcid.org/0000-0001-5238-8885)
Institutions
- Hong Kong Baptist University (HK)
- University of Electronic Science and Technology of China (CN)
- Shanghai Jiao Tong University (CN)
- Jilin University (CN)
- Henan Tianguan Group (China) (CN)
- State Key Laboratory on Integrated Optoelectronics (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1038/s41467-025-58794-3
- Citations
- 4
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 9.92
Funders
- Hong Kong Baptist University
- National Natural Science Foundation of China
- Shanghai Jiao Tong University