Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor
[Display omitted] Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale...
Gespeichert in:
| Veröffentlicht in: | Science bulletin 2023-05, Vol.68 (9), p.906-912 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 912 |
|---|---|
| container_issue | 9 |
| container_start_page | 906 |
| container_title | Science bulletin |
| container_volume | 68 |
| creator | Gong, Ming Huang, He-Liang Wang, Shiyu Guo, Chu Li, Shaowei Wu, Yulin Zhu, Qingling Zhao, Youwei Guo, Shaojun Qian, Haoran Ye, Yangsen Zha, Chen Chen, Fusheng Ying, Chong Yu, Jiale Fan, Daojin Wu, Dachao Su, Hong Deng, Hui Rong, Hao Zhang, Kaili Cao, Sirui Lin, Jin Xu, Yu Sun, Lihua Guo, Cheng Li, Na Liang, Futian Sakurai, Akitada Nemoto, Kae Munro, William J. Huo, Yong-Heng Lu, Chao-Yang Peng, Cheng-Zhi Zhu, Xiaobo Pan, Jian-Wei |
| description | [Display omitted]
Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here, we propose a new approach called quantum neuronal sensing. Utilizing a 61-qubit superconducting quantum processor, we show that our scheme can efficiently classify two different types of many-body phenomena: namely the ergodic and localized phases of matter. Our quantum neuronal sensing process allows us to extract the necessary information coming from the statistical characteristics of the eigenspectrum to distinguish these phases of matter by measuring only one qubit and offers better phase resolution than conventional methods, such as measuring the imbalance. Our work demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems. |
| doi_str_mv | 10.1016/j.scib.2023.04.003 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2805031927</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S2095927323002359</els_id><sourcerecordid>2805031927</sourcerecordid><originalsourceid>FETCH-LOGICAL-c400t-6ca3f38c6b10626efee0c8c06d3db838e27521ec9dd475ecc89abb4aef6b91c83</originalsourceid><addsrcrecordid>eNp9kE1r3DAQhkVoacI2f6CHoGMvdkaSP2TopYS2CQRKoT0LfYyDFlvalazC_vva7DbHnGZg3nmGeQj5xKBmwLr7fZ2tNzUHLmpoagBxRW44DG01cMnevfa9uCa3Oe8BgDUDb6D_QK5FD7IVQ39D_K-iw1JmGrCkGPREM4bswwuNIz1eZrMOp8pEd6J50QtmGgPVtGPVsRi_0EOKL0nPszYT0lwOmGwMrthlw6xDiznH9JG8H_WU8fZSd-TP92-_Hx6r558_nh6-Ple2AViqzmoxCmk7w6DjHY6IYKWFzglnpJDI-5YztINzTd-itXLQxjQax84MzEqxI5_P3PXysWBe1OyzxWnSAWPJiktoQbDNzI7wc9SmmHPCUR2Sn3U6KQZqs6z2arOsNssKGrVaXpfuLvxiZnSvK_-droEv5wCuX_71mDYGBovOJ7SLctG_xf8HNAmQaQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2805031927</pqid></control><display><type>article</type><title>Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor</title><source>Alma/SFX Local Collection</source><creator>Gong, Ming ; Huang, He-Liang ; Wang, Shiyu ; Guo, Chu ; Li, Shaowei ; Wu, Yulin ; Zhu, Qingling ; Zhao, Youwei ; Guo, Shaojun ; Qian, Haoran ; Ye, Yangsen ; Zha, Chen ; Chen, Fusheng ; Ying, Chong ; Yu, Jiale ; Fan, Daojin ; Wu, Dachao ; Su, Hong ; Deng, Hui ; Rong, Hao ; Zhang, Kaili ; Cao, Sirui ; Lin, Jin ; Xu, Yu ; Sun, Lihua ; Guo, Cheng ; Li, Na ; Liang, Futian ; Sakurai, Akitada ; Nemoto, Kae ; Munro, William J. ; Huo, Yong-Heng ; Lu, Chao-Yang ; Peng, Cheng-Zhi ; Zhu, Xiaobo ; Pan, Jian-Wei</creator><creatorcontrib>Gong, Ming ; Huang, He-Liang ; Wang, Shiyu ; Guo, Chu ; Li, Shaowei ; Wu, Yulin ; Zhu, Qingling ; Zhao, Youwei ; Guo, Shaojun ; Qian, Haoran ; Ye, Yangsen ; Zha, Chen ; Chen, Fusheng ; Ying, Chong ; Yu, Jiale ; Fan, Daojin ; Wu, Dachao ; Su, Hong ; Deng, Hui ; Rong, Hao ; Zhang, Kaili ; Cao, Sirui ; Lin, Jin ; Xu, Yu ; Sun, Lihua ; Guo, Cheng ; Li, Na ; Liang, Futian ; Sakurai, Akitada ; Nemoto, Kae ; Munro, William J. ; Huo, Yong-Heng ; Lu, Chao-Yang ; Peng, Cheng-Zhi ; Zhu, Xiaobo ; Pan, Jian-Wei</creatorcontrib><description>[Display omitted]
Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here, we propose a new approach called quantum neuronal sensing. Utilizing a 61-qubit superconducting quantum processor, we show that our scheme can efficiently classify two different types of many-body phenomena: namely the ergodic and localized phases of matter. Our quantum neuronal sensing process allows us to extract the necessary information coming from the statistical characteristics of the eigenspectrum to distinguish these phases of matter by measuring only one qubit and offers better phase resolution than conventional methods, such as measuring the imbalance. Our work demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems.</description><identifier>ISSN: 2095-9273</identifier><identifier>EISSN: 2095-9281</identifier><identifier>DOI: 10.1016/j.scib.2023.04.003</identifier><identifier>PMID: 37085397</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Quantum many-body state ; Quantum neural network ; Superconducting qubit ; Variational quantum eigensolver</subject><ispartof>Science bulletin, 2023-05, Vol.68 (9), p.906-912</ispartof><rights>2023 Science China Press</rights><rights>Copyright © 2023 Science China Press. Published by Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-6ca3f38c6b10626efee0c8c06d3db838e27521ec9dd475ecc89abb4aef6b91c83</citedby><cites>FETCH-LOGICAL-c400t-6ca3f38c6b10626efee0c8c06d3db838e27521ec9dd475ecc89abb4aef6b91c83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37085397$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gong, Ming</creatorcontrib><creatorcontrib>Huang, He-Liang</creatorcontrib><creatorcontrib>Wang, Shiyu</creatorcontrib><creatorcontrib>Guo, Chu</creatorcontrib><creatorcontrib>Li, Shaowei</creatorcontrib><creatorcontrib>Wu, Yulin</creatorcontrib><creatorcontrib>Zhu, Qingling</creatorcontrib><creatorcontrib>Zhao, Youwei</creatorcontrib><creatorcontrib>Guo, Shaojun</creatorcontrib><creatorcontrib>Qian, Haoran</creatorcontrib><creatorcontrib>Ye, Yangsen</creatorcontrib><creatorcontrib>Zha, Chen</creatorcontrib><creatorcontrib>Chen, Fusheng</creatorcontrib><creatorcontrib>Ying, Chong</creatorcontrib><creatorcontrib>Yu, Jiale</creatorcontrib><creatorcontrib>Fan, Daojin</creatorcontrib><creatorcontrib>Wu, Dachao</creatorcontrib><creatorcontrib>Su, Hong</creatorcontrib><creatorcontrib>Deng, Hui</creatorcontrib><creatorcontrib>Rong, Hao</creatorcontrib><creatorcontrib>Zhang, Kaili</creatorcontrib><creatorcontrib>Cao, Sirui</creatorcontrib><creatorcontrib>Lin, Jin</creatorcontrib><creatorcontrib>Xu, Yu</creatorcontrib><creatorcontrib>Sun, Lihua</creatorcontrib><creatorcontrib>Guo, Cheng</creatorcontrib><creatorcontrib>Li, Na</creatorcontrib><creatorcontrib>Liang, Futian</creatorcontrib><creatorcontrib>Sakurai, Akitada</creatorcontrib><creatorcontrib>Nemoto, Kae</creatorcontrib><creatorcontrib>Munro, William J.</creatorcontrib><creatorcontrib>Huo, Yong-Heng</creatorcontrib><creatorcontrib>Lu, Chao-Yang</creatorcontrib><creatorcontrib>Peng, Cheng-Zhi</creatorcontrib><creatorcontrib>Zhu, Xiaobo</creatorcontrib><creatorcontrib>Pan, Jian-Wei</creatorcontrib><title>Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor</title><title>Science bulletin</title><addtitle>Sci Bull (Beijing)</addtitle><description>[Display omitted]
Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here, we propose a new approach called quantum neuronal sensing. Utilizing a 61-qubit superconducting quantum processor, we show that our scheme can efficiently classify two different types of many-body phenomena: namely the ergodic and localized phases of matter. Our quantum neuronal sensing process allows us to extract the necessary information coming from the statistical characteristics of the eigenspectrum to distinguish these phases of matter by measuring only one qubit and offers better phase resolution than conventional methods, such as measuring the imbalance. Our work demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems.</description><subject>Quantum many-body state</subject><subject>Quantum neural network</subject><subject>Superconducting qubit</subject><subject>Variational quantum eigensolver</subject><issn>2095-9273</issn><issn>2095-9281</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kE1r3DAQhkVoacI2f6CHoGMvdkaSP2TopYS2CQRKoT0LfYyDFlvalazC_vva7DbHnGZg3nmGeQj5xKBmwLr7fZ2tNzUHLmpoagBxRW44DG01cMnevfa9uCa3Oe8BgDUDb6D_QK5FD7IVQ39D_K-iw1JmGrCkGPREM4bswwuNIz1eZrMOp8pEd6J50QtmGgPVtGPVsRi_0EOKL0nPszYT0lwOmGwMrthlw6xDiznH9JG8H_WU8fZSd-TP92-_Hx6r558_nh6-Ple2AViqzmoxCmk7w6DjHY6IYKWFzglnpJDI-5YztINzTd-itXLQxjQax84MzEqxI5_P3PXysWBe1OyzxWnSAWPJiktoQbDNzI7wc9SmmHPCUR2Sn3U6KQZqs6z2arOsNssKGrVaXpfuLvxiZnSvK_-droEv5wCuX_71mDYGBovOJ7SLctG_xf8HNAmQaQ</recordid><startdate>20230515</startdate><enddate>20230515</enddate><creator>Gong, Ming</creator><creator>Huang, He-Liang</creator><creator>Wang, Shiyu</creator><creator>Guo, Chu</creator><creator>Li, Shaowei</creator><creator>Wu, Yulin</creator><creator>Zhu, Qingling</creator><creator>Zhao, Youwei</creator><creator>Guo, Shaojun</creator><creator>Qian, Haoran</creator><creator>Ye, Yangsen</creator><creator>Zha, Chen</creator><creator>Chen, Fusheng</creator><creator>Ying, Chong</creator><creator>Yu, Jiale</creator><creator>Fan, Daojin</creator><creator>Wu, Dachao</creator><creator>Su, Hong</creator><creator>Deng, Hui</creator><creator>Rong, Hao</creator><creator>Zhang, Kaili</creator><creator>Cao, Sirui</creator><creator>Lin, Jin</creator><creator>Xu, Yu</creator><creator>Sun, Lihua</creator><creator>Guo, Cheng</creator><creator>Li, Na</creator><creator>Liang, Futian</creator><creator>Sakurai, Akitada</creator><creator>Nemoto, Kae</creator><creator>Munro, William J.</creator><creator>Huo, Yong-Heng</creator><creator>Lu, Chao-Yang</creator><creator>Peng, Cheng-Zhi</creator><creator>Zhu, Xiaobo</creator><creator>Pan, Jian-Wei</creator><general>Elsevier B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20230515</creationdate><title>Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor</title><author>Gong, Ming ; Huang, He-Liang ; Wang, Shiyu ; Guo, Chu ; Li, Shaowei ; Wu, Yulin ; Zhu, Qingling ; Zhao, Youwei ; Guo, Shaojun ; Qian, Haoran ; Ye, Yangsen ; Zha, Chen ; Chen, Fusheng ; Ying, Chong ; Yu, Jiale ; Fan, Daojin ; Wu, Dachao ; Su, Hong ; Deng, Hui ; Rong, Hao ; Zhang, Kaili ; Cao, Sirui ; Lin, Jin ; Xu, Yu ; Sun, Lihua ; Guo, Cheng ; Li, Na ; Liang, Futian ; Sakurai, Akitada ; Nemoto, Kae ; Munro, William J. ; Huo, Yong-Heng ; Lu, Chao-Yang ; Peng, Cheng-Zhi ; Zhu, Xiaobo ; Pan, Jian-Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-6ca3f38c6b10626efee0c8c06d3db838e27521ec9dd475ecc89abb4aef6b91c83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Quantum many-body state</topic><topic>Quantum neural network</topic><topic>Superconducting qubit</topic><topic>Variational quantum eigensolver</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gong, Ming</creatorcontrib><creatorcontrib>Huang, He-Liang</creatorcontrib><creatorcontrib>Wang, Shiyu</creatorcontrib><creatorcontrib>Guo, Chu</creatorcontrib><creatorcontrib>Li, Shaowei</creatorcontrib><creatorcontrib>Wu, Yulin</creatorcontrib><creatorcontrib>Zhu, Qingling</creatorcontrib><creatorcontrib>Zhao, Youwei</creatorcontrib><creatorcontrib>Guo, Shaojun</creatorcontrib><creatorcontrib>Qian, Haoran</creatorcontrib><creatorcontrib>Ye, Yangsen</creatorcontrib><creatorcontrib>Zha, Chen</creatorcontrib><creatorcontrib>Chen, Fusheng</creatorcontrib><creatorcontrib>Ying, Chong</creatorcontrib><creatorcontrib>Yu, Jiale</creatorcontrib><creatorcontrib>Fan, Daojin</creatorcontrib><creatorcontrib>Wu, Dachao</creatorcontrib><creatorcontrib>Su, Hong</creatorcontrib><creatorcontrib>Deng, Hui</creatorcontrib><creatorcontrib>Rong, Hao</creatorcontrib><creatorcontrib>Zhang, Kaili</creatorcontrib><creatorcontrib>Cao, Sirui</creatorcontrib><creatorcontrib>Lin, Jin</creatorcontrib><creatorcontrib>Xu, Yu</creatorcontrib><creatorcontrib>Sun, Lihua</creatorcontrib><creatorcontrib>Guo, Cheng</creatorcontrib><creatorcontrib>Li, Na</creatorcontrib><creatorcontrib>Liang, Futian</creatorcontrib><creatorcontrib>Sakurai, Akitada</creatorcontrib><creatorcontrib>Nemoto, Kae</creatorcontrib><creatorcontrib>Munro, William J.</creatorcontrib><creatorcontrib>Huo, Yong-Heng</creatorcontrib><creatorcontrib>Lu, Chao-Yang</creatorcontrib><creatorcontrib>Peng, Cheng-Zhi</creatorcontrib><creatorcontrib>Zhu, Xiaobo</creatorcontrib><creatorcontrib>Pan, Jian-Wei</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Science bulletin</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gong, Ming</au><au>Huang, He-Liang</au><au>Wang, Shiyu</au><au>Guo, Chu</au><au>Li, Shaowei</au><au>Wu, Yulin</au><au>Zhu, Qingling</au><au>Zhao, Youwei</au><au>Guo, Shaojun</au><au>Qian, Haoran</au><au>Ye, Yangsen</au><au>Zha, Chen</au><au>Chen, Fusheng</au><au>Ying, Chong</au><au>Yu, Jiale</au><au>Fan, Daojin</au><au>Wu, Dachao</au><au>Su, Hong</au><au>Deng, Hui</au><au>Rong, Hao</au><au>Zhang, Kaili</au><au>Cao, Sirui</au><au>Lin, Jin</au><au>Xu, Yu</au><au>Sun, Lihua</au><au>Guo, Cheng</au><au>Li, Na</au><au>Liang, Futian</au><au>Sakurai, Akitada</au><au>Nemoto, Kae</au><au>Munro, William J.</au><au>Huo, Yong-Heng</au><au>Lu, Chao-Yang</au><au>Peng, Cheng-Zhi</au><au>Zhu, Xiaobo</au><au>Pan, Jian-Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor</atitle><jtitle>Science bulletin</jtitle><addtitle>Sci Bull (Beijing)</addtitle><date>2023-05-15</date><risdate>2023</risdate><volume>68</volume><issue>9</issue><spage>906</spage><epage>912</epage><pages>906-912</pages><issn>2095-9273</issn><eissn>2095-9281</eissn><abstract>[Display omitted]
Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here, we propose a new approach called quantum neuronal sensing. Utilizing a 61-qubit superconducting quantum processor, we show that our scheme can efficiently classify two different types of many-body phenomena: namely the ergodic and localized phases of matter. Our quantum neuronal sensing process allows us to extract the necessary information coming from the statistical characteristics of the eigenspectrum to distinguish these phases of matter by measuring only one qubit and offers better phase resolution than conventional methods, such as measuring the imbalance. Our work demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>37085397</pmid><doi>10.1016/j.scib.2023.04.003</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2095-9273 |
| ispartof | Science bulletin, 2023-05, Vol.68 (9), p.906-912 |
| issn | 2095-9273 2095-9281 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2805031927 |
| source | Alma/SFX Local Collection |
| subjects | Quantum many-body state Quantum neural network Superconducting qubit Variational quantum eigensolver |
| title | Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T21%3A47%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Quantum%20neuronal%20sensing%20of%20quantum%20many-body%20states%20on%20a%2061-qubit%20programmable%20superconducting%20processor&rft.jtitle=Science%20bulletin&rft.au=Gong,%20Ming&rft.date=2023-05-15&rft.volume=68&rft.issue=9&rft.spage=906&rft.epage=912&rft.pages=906-912&rft.issn=2095-9273&rft.eissn=2095-9281&rft_id=info:doi/10.1016/j.scib.2023.04.003&rft_dat=%3Cproquest_cross%3E2805031927%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2805031927&rft_id=info:pmid/37085397&rft_els_id=S2095927323002359&rfr_iscdi=true |