Efficient Real-Time Spin Readout of Nitrogen-Vacancy Centers Based on Bayesian Estimation
This article introduces a real-time Bayesian estimation algorithm aimed at enhancing the spin readout efficiency of the nitrogen vacancy (NV) center ensemble in the diamond. By integrating both the prior probability distribution and the fluorescence likelihood function, stemming from the implementat...
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| Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 2024-10, Vol.71 (10), p.13341-13350 |
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| container_title | IEEE transactions on industrial electronics (1982) |
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| creator | Zhang, Jixing Liu, Tianzheng Yuan, Heng Xia, Sigang Bian, Guodong Fan, Pengcheng Li, Mingxin Wang, Sixian Li, Xiangyun Zhang, Chen Zhang, Shaoda |
| description | This article introduces a real-time Bayesian estimation algorithm aimed at enhancing the spin readout efficiency of the nitrogen vacancy (NV) center ensemble in the diamond. By integrating both the prior probability distribution and the fluorescence likelihood function, stemming from the implementation of the NV center dynamics model, we offered an innovative solution to surpass the Cramer-Rao lower bound of the readout variance and improve the readout efficiency. The proposed real-time Bayesian estimation readout algorithm was experimentally realized by combining high-performance acquisition and processing hardware, and the Rabi oscillation experiments divulged that the signal-to-noise ratio of our approach was improved by 28.6%. This research illustrates the potential of the Bayesian estimation readout to enhance the NV ensemble's sensing capabilities and support the development of compact and scalable quantum sensors devices on a monolithic platform. |
| doi_str_mv | 10.1109/TIE.2023.3347837 |
| format | Article |
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By integrating both the prior probability distribution and the fluorescence likelihood function, stemming from the implementation of the NV center dynamics model, we offered an innovative solution to surpass the Cramer-Rao lower bound of the readout variance and improve the readout efficiency. The proposed real-time Bayesian estimation readout algorithm was experimentally realized by combining high-performance acquisition and processing hardware, and the Rabi oscillation experiments divulged that the signal-to-noise ratio of our approach was improved by 28.6%. This research illustrates the potential of the Bayesian estimation readout to enhance the NV ensemble's sensing capabilities and support the development of compact and scalable quantum sensors devices on a monolithic platform.</description><identifier>ISSN: 0278-0046</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/TIE.2023.3347837</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Bayes methods ; Bayesian analysis ; Bayesian estimation ; Conditional probability ; Estimation ; Lower bounds ; Mathematical models ; Nitrogen ; nitrogen vacancy (NV) center ; photon shot noise ; Photonics ; Quantum sensors ; Real time ; Real-time systems ; Signal to noise ratio ; Spin dynamics ; spin readout ; Stationary state</subject><ispartof>IEEE transactions on industrial electronics (1982), 2024-10, Vol.71 (10), p.13341-13350</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c287t-7ced980c729ff188ba0fec4987c3ed4c9e18d265dadeb5f849df2c58013f96113</cites><orcidid>0000-0003-2131-6998 ; 0000-0002-4935-9300 ; 0000-0001-7829-2937 ; 0000-0002-1696-3368 ; 0000-0002-6113-8287 ; 0000-0001-8381-3960 ; 0000-0001-9177-9168 ; 0009-0007-7681-1896 ; 0000-0002-1983-5409 ; 0009-0001-7094-5080 ; 0009-0001-4564-6943</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10413893$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10413893$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhang, Jixing</creatorcontrib><creatorcontrib>Liu, Tianzheng</creatorcontrib><creatorcontrib>Yuan, Heng</creatorcontrib><creatorcontrib>Xia, Sigang</creatorcontrib><creatorcontrib>Bian, Guodong</creatorcontrib><creatorcontrib>Fan, Pengcheng</creatorcontrib><creatorcontrib>Li, Mingxin</creatorcontrib><creatorcontrib>Wang, Sixian</creatorcontrib><creatorcontrib>Li, Xiangyun</creatorcontrib><creatorcontrib>Zhang, Chen</creatorcontrib><creatorcontrib>Zhang, Shaoda</creatorcontrib><title>Efficient Real-Time Spin Readout of Nitrogen-Vacancy Centers Based on Bayesian Estimation</title><title>IEEE transactions on industrial electronics (1982)</title><addtitle>TIE</addtitle><description>This article introduces a real-time Bayesian estimation algorithm aimed at enhancing the spin readout efficiency of the nitrogen vacancy (NV) center ensemble in the diamond. By integrating both the prior probability distribution and the fluorescence likelihood function, stemming from the implementation of the NV center dynamics model, we offered an innovative solution to surpass the Cramer-Rao lower bound of the readout variance and improve the readout efficiency. The proposed real-time Bayesian estimation readout algorithm was experimentally realized by combining high-performance acquisition and processing hardware, and the Rabi oscillation experiments divulged that the signal-to-noise ratio of our approach was improved by 28.6%. This research illustrates the potential of the Bayesian estimation readout to enhance the NV ensemble's sensing capabilities and support the development of compact and scalable quantum sensors devices on a monolithic platform.</description><subject>Algorithms</subject><subject>Bayes methods</subject><subject>Bayesian analysis</subject><subject>Bayesian estimation</subject><subject>Conditional probability</subject><subject>Estimation</subject><subject>Lower bounds</subject><subject>Mathematical models</subject><subject>Nitrogen</subject><subject>nitrogen vacancy (NV) center</subject><subject>photon shot noise</subject><subject>Photonics</subject><subject>Quantum sensors</subject><subject>Real time</subject><subject>Real-time systems</subject><subject>Signal to noise ratio</subject><subject>Spin dynamics</subject><subject>spin readout</subject><subject>Stationary state</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkE1LAzEQQIMoWKt3Dx4Cnrcmm6RJjlqqFoqCVsFTSJOJpLSbmmwP_fem1IMwMDPw5oOH0DUlI0qJvlvMpqOWtGzEGJeKyRM0oELIRmuuTtGAtFI1hPDxObooZUUI5YKKAfqahhBdhK7Hb2DXzSJuAL9vY3dofdr1OAX8EvucvqFrPq2zndvjSeUhF_xgC3iculrsoUTb4Wnp48b2MXWX6CzYdYGrvzxEH4_TxeS5mb8-zSb388a1SvaNdOC1Ik62OgSq1NKSAI5rJR0Dz50Gqnw7Ft56WIqguPahdUIRyoIeU8qG6Pa4d5vTzw5Kb1Zpl7t60jAiVQ1BWaXIkXI5lZIhmG2uj-a9ocQcBJoq0BwEmj-BdeTmOBIB4B_OKVOasV_OUGxP</recordid><startdate>202410</startdate><enddate>202410</enddate><creator>Zhang, Jixing</creator><creator>Liu, Tianzheng</creator><creator>Yuan, Heng</creator><creator>Xia, Sigang</creator><creator>Bian, Guodong</creator><creator>Fan, Pengcheng</creator><creator>Li, Mingxin</creator><creator>Wang, Sixian</creator><creator>Li, Xiangyun</creator><creator>Zhang, Chen</creator><creator>Zhang, Shaoda</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | Algorithms Bayes methods Bayesian analysis Bayesian estimation Conditional probability Estimation Lower bounds Mathematical models Nitrogen nitrogen vacancy (NV) center photon shot noise Photonics Quantum sensors Real time Real-time systems Signal to noise ratio Spin dynamics spin readout Stationary state |
| title | Efficient Real-Time Spin Readout of Nitrogen-Vacancy Centers Based on Bayesian Estimation |
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