Optimal repetitive readout of single solid-state spins determined by Fisher information
Quantum systems, including superconducting circuits, trapped ions, quantum dots, solid-state defects, etc., have achieved considerable advancements in readout fidelity. However, the widely used threshold method disregards the importance of temporal characteristics of the signal during continuous measurements, leading to information loss. Here, we applied Fisher information to quantify the potential enhancement by using the temporal information. We proposed an optimal data processing method and derived the condition for equality to the error constrained by Fisher information. Applying this method to the single-shot readout of a [Formula: see text] nuclear spin of nitrogen-vacancy center marks a 33.8 ± 1.2% error reduction compared to the threshold method, improving the fidelity to 99.649(5)%. The versatility of our method is further demonstrated through the single-shot readout of charge states. This work illustrates the advantage of using photon arrival time for improving readout fidelity without upgrading experimental hardware. The method of using Fisher information to analyze readout fidelity also holds promise for broad applicability to other systems.
Authors
- Zhiyuan Zhao (ORCID: https://orcid.org/0000-0003-1465-0269)
- Pei Yu (ORCID: https://orcid.org/0000-0002-7884-3214)
- Shaoyi Xu (ORCID: https://orcid.org/0000-0002-8672-2471)
- Fazhan Shi (ORCID: https://orcid.org/0000-0003-3312-5566)
- Zhiping Yang (ORCID: https://orcid.org/0000-0003-0622-2117)
- Tianyu Xie (ORCID: https://orcid.org/0000-0002-2563-2974)
- Xiangyu Ye (ORCID: https://orcid.org/0000-0002-8309-2101)
- Ya Wang (ORCID: https://orcid.org/0000-0001-6232-7234)
- Mengqi Wang (ORCID: https://orcid.org/0000-0003-3167-0464)
- Jiangfeng Du (ORCID: https://orcid.org/0000-0001-8085-8012)
- Qian Shi (ORCID: https://orcid.org/0000-0002-2535-8119)
- Yuyao CHEN (ORCID: https://orcid.org/0000-0002-3025-1228)
- Xi Kong (ORCID: https://orcid.org/0009-0008-6993-3251)
Institutions
- University of Science and Technology of China (CN)
- Suzhou University of Science and Technology (CN)
- Zhejiang University (CN)
- Nanjing University (CN)
Publication Details
- Journal
- Science Advances
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1126/sciadv.adp9228
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Fundamental Research Funds for the Central Universities