Probe optimization for quantum metrology via closed-loop learning control
Experimentally achieving the precision that standard quantum metrology schemes promise is always challenging. Recently, additional controls were applied to design feasible quantum metrology schemes. However, these approaches generally does not consider ease of implementation, raising technological b...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2021
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| Online Access: | https://hdl.handle.net/10356/146595 |
| _version_ | 1811679538335186944 |
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| author | Yang, Xiaodong Thompson, Jayne Wu, Ze Gu, Mile Peng, Xinhua Du, Jiangfeng |
| author2 | School of Physical and Mathematical Sciences |
| author_facet | School of Physical and Mathematical Sciences Yang, Xiaodong Thompson, Jayne Wu, Ze Gu, Mile Peng, Xinhua Du, Jiangfeng |
| author_sort | Yang, Xiaodong |
| collection | NTU |
| description | Experimentally achieving the precision that standard quantum metrology schemes promise is always challenging. Recently, additional controls were applied to design feasible quantum metrology schemes. However, these approaches generally does not consider ease of implementation, raising technological barriers impeding its realization. In this paper, we circumvent this problem by applying closed-loop learning control to propose a practical controlled sequential scheme for quantum metrology. Purity loss of the probe state, which relates to quantum Fisher information, is measured efficiently as the fitness to guide the learning loop. We confirm its feasibility and certain superiorities over standard quantum metrology schemes by numerical analysis and proof-of-principle experiments in a nuclear magnetic resonance system. |
| first_indexed | 2024-10-01T03:10:45Z |
| format | Journal Article |
| id | ntu-10356/146595 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:10:45Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1465952023-02-28T19:54:56Z Probe optimization for quantum metrology via closed-loop learning control Yang, Xiaodong Thompson, Jayne Wu, Ze Gu, Mile Peng, Xinhua Du, Jiangfeng School of Physical and Mathematical Sciences Science::Physics Quantum Information Quantum Metrology Experimentally achieving the precision that standard quantum metrology schemes promise is always challenging. Recently, additional controls were applied to design feasible quantum metrology schemes. However, these approaches generally does not consider ease of implementation, raising technological barriers impeding its realization. In this paper, we circumvent this problem by applying closed-loop learning control to propose a practical controlled sequential scheme for quantum metrology. Purity loss of the probe state, which relates to quantum Fisher information, is measured efficiently as the fitness to guide the learning loop. We confirm its feasibility and certain superiorities over standard quantum metrology schemes by numerical analysis and proof-of-principle experiments in a nuclear magnetic resonance system. Ministry of Education (MOE) National Research Foundation (NRF) Published version This work was supported by National Key Research and Development Program of China (Grant No. 2018YFA0306600), National Natural Science Foundation of China (Grants Nos. 11661161018 and 11927811), Anhui Initiative in Quantum Information Technologies (Grant No. AHY050000), the National Research Foundation (NRF) Singapore, under its NRFF Fellow programme (Award No. NRF-NRFF2016-02), the Singapore Ministry of Education Tier 1 Grant 2017-T1-002-043 and 2019-T1-002-015, the NRF-ANR Grant NRF2017-NRF-ANR004 VanQuTe, and the FQXi large grant: FQXi-RFP-1809 the role of quantum effects in simplifying adaptive agents, and FQXi-RFP-IPW-1903 are quantum agents more energetically efficient at making predictions. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore. 2021-03-02T06:48:49Z 2021-03-02T06:48:49Z 2020 Journal Article Yang, X., Thompson, J., Wu, Z., Gu, M., Peng, X., & Du, J. (2020). Probe optimization for quantum metrology via closed-loop learning control. npj Quantum Information, 6(1), 62-. doi:10.1038/s41534-020-00292-z 2056-6387 0000-0003-4509-6045 0000-0002-3746-244X 0000-0002-5459-4313 0000-0001-5260-2976 0000-0001-8085-8012 https://hdl.handle.net/10356/146595 10.1038/s41534-020-00292-z 2-s2.0-85088123665 1 6 en NRF-NRFF2016-02 2017-T1-002-043 2019-T1-002-015 NRF2017-NRF-ANR004 npj Quantum Information © 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visithttp://creativecommons.org/licenses/by/4.0/. application/pdf |
| spellingShingle | Science::Physics Quantum Information Quantum Metrology Yang, Xiaodong Thompson, Jayne Wu, Ze Gu, Mile Peng, Xinhua Du, Jiangfeng Probe optimization for quantum metrology via closed-loop learning control |
| title | Probe optimization for quantum metrology via closed-loop learning control |
| title_full | Probe optimization for quantum metrology via closed-loop learning control |
| title_fullStr | Probe optimization for quantum metrology via closed-loop learning control |
| title_full_unstemmed | Probe optimization for quantum metrology via closed-loop learning control |
| title_short | Probe optimization for quantum metrology via closed-loop learning control |
| title_sort | probe optimization for quantum metrology via closed loop learning control |
| topic | Science::Physics Quantum Information Quantum Metrology |
| url | https://hdl.handle.net/10356/146595 |
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