Noise-resilient nonadiabatic geometric quantum computation for bosonic binomial codes

Quantum Physics [Submitted on 18 Mar 2026] Noise-resilient nonadiabatic geometric quantum computation for bosonic binomial codes Dong-Sheng Li, Yang Xiao, Yu Wang, Yang Liu, Zhi-Cheng Shi, Ye-Hong Chen, Yi-Hao Kang, Yan Xia The binomial code is renowned for its parity-mediated loss immunity and loss-error recoverability, while geometric phases are widely recognized for their intrinsic resilience against noise. Capitalizing on their complementary merits, we propose a noise-resilient protocol to realize Nonadiabatic geometric quantum computation with binomial codes in a superconducting system composed of a microwave cavity %off-resonantly dispersively coupled to a %three-level qutrit. The control field %geometric quantum computation is designed by %combining geometric phases, integrating reverse engineering and optimal control. This design provides a customized control protocol featuring strong error-tolerance and inherent noise-resilience. Using experimentally accessible parameters in superconducting systems, numerical simulations show that the protocol yields relatively high average fidelity for geometric quantum gates based on binomial code, even in the presence of parameter fluctuations and decoherence. Thus, this protocol may provide a practical approach for realizing reliable Nonadiabatic geometric quantum computation with binomial codes in current technology. Comments: 13 pages, 7 figures Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2603.17250 [quant-ph]   (or arXiv:2603.17250v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2603.17250 Focus to learn more Submission history From: Ye-Hong Chen Dr. [view email] [v1] Wed, 18 Mar 2026 01:09:56 UTC (1,320 KB) Access Paper: view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-03 References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)