{"title":"量子传感工具表征物理,化学和生物过程与磁共振","authors":"Analia Zwick, Gonzalo A. Álvarez","doi":"10.1016/j.jmro.2023.100113","DOIUrl":null,"url":null,"abstract":"<div><p>Nuclear Magnetic Resonance (NMR) plays a central role in developing quantum information sciences and technologies. Key features such as its non-invasive nature and the ability to process information on nuclear spins by versatile quantum control designs with electromagnetic fields, have made NMR to become a powerful technique for sensing systems from atomic and molecular scales with spectroscopy to millimeters in imaging. This brief overview provides quantum sensing tools with which we are contributing from Latin America, by combining quantum dynamical control and estimation strategies with NMR methods to probe physical, chemical, and biological processes. It introduces the basic and key concepts on how controlled spin-sensors can monitor the correlation dynamics of their environment, and selectively and optimally infer its relevant parameters. Then these concepts are illustrated with state-of-the-art implementations for characterizing (i) biological tissue microstructure with diffusion weighting imaging, (ii) quantum information dynamics and scrambling in out-of-equilibrium systems with solid-state NMR quantum simulations, and (iii) molecular structures by selective estimation of spin–spin couplings and online learning control designs with experimental proposals. We expect these concepts will motivate the development of quantum dynamical control of spin sensors to monitor systems in a variety of fields, and in particular to exploit the non-invasive strength of NMR, e.g. in biomedical diagnosis.</p></div>","PeriodicalId":365,"journal":{"name":"Journal of Magnetic Resonance Open","volume":"16 ","pages":"Article 100113"},"PeriodicalIF":2.6240,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Quantum sensing tools to characterize physical, chemical and biological processes with magnetic resonance\",\"authors\":\"Analia Zwick, Gonzalo A. Álvarez\",\"doi\":\"10.1016/j.jmro.2023.100113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Nuclear Magnetic Resonance (NMR) plays a central role in developing quantum information sciences and technologies. Key features such as its non-invasive nature and the ability to process information on nuclear spins by versatile quantum control designs with electromagnetic fields, have made NMR to become a powerful technique for sensing systems from atomic and molecular scales with spectroscopy to millimeters in imaging. This brief overview provides quantum sensing tools with which we are contributing from Latin America, by combining quantum dynamical control and estimation strategies with NMR methods to probe physical, chemical, and biological processes. It introduces the basic and key concepts on how controlled spin-sensors can monitor the correlation dynamics of their environment, and selectively and optimally infer its relevant parameters. Then these concepts are illustrated with state-of-the-art implementations for characterizing (i) biological tissue microstructure with diffusion weighting imaging, (ii) quantum information dynamics and scrambling in out-of-equilibrium systems with solid-state NMR quantum simulations, and (iii) molecular structures by selective estimation of spin–spin couplings and online learning control designs with experimental proposals. We expect these concepts will motivate the development of quantum dynamical control of spin sensors to monitor systems in a variety of fields, and in particular to exploit the non-invasive strength of NMR, e.g. in biomedical diagnosis.</p></div>\",\"PeriodicalId\":365,\"journal\":{\"name\":\"Journal of Magnetic Resonance Open\",\"volume\":\"16 \",\"pages\":\"Article 100113\"},\"PeriodicalIF\":2.6240,\"publicationDate\":\"2023-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Magnetic Resonance Open\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666441023000213\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Magnetic Resonance Open","FirstCategoryId":"1","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666441023000213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantum sensing tools to characterize physical, chemical and biological processes with magnetic resonance
Nuclear Magnetic Resonance (NMR) plays a central role in developing quantum information sciences and technologies. Key features such as its non-invasive nature and the ability to process information on nuclear spins by versatile quantum control designs with electromagnetic fields, have made NMR to become a powerful technique for sensing systems from atomic and molecular scales with spectroscopy to millimeters in imaging. This brief overview provides quantum sensing tools with which we are contributing from Latin America, by combining quantum dynamical control and estimation strategies with NMR methods to probe physical, chemical, and biological processes. It introduces the basic and key concepts on how controlled spin-sensors can monitor the correlation dynamics of their environment, and selectively and optimally infer its relevant parameters. Then these concepts are illustrated with state-of-the-art implementations for characterizing (i) biological tissue microstructure with diffusion weighting imaging, (ii) quantum information dynamics and scrambling in out-of-equilibrium systems with solid-state NMR quantum simulations, and (iii) molecular structures by selective estimation of spin–spin couplings and online learning control designs with experimental proposals. We expect these concepts will motivate the development of quantum dynamical control of spin sensors to monitor systems in a variety of fields, and in particular to exploit the non-invasive strength of NMR, e.g. in biomedical diagnosis.