Adaptive Variational Quantum Dynamics (AVQD) algorithms offer a promising approach to providing quantum‐enabled solutions for systems treated within the purview of open quantum dynamical evolution. In this study, the unrestricted‐vectorization variant of AVQD is employed to simulate and benchmark various non‐unitarily evolving systems. Exemplification of how construction of an expressible ansatz unitary and the associated operator pool can be implemented to analyze examples such as the Fenna–Matthews–Olson complex (FMO) and even the permutational invariant Dicke model of quantum optics. Furthermore, an efficient decomposition scheme is shown for the ansatz used, which can extend its applications to a wide range of other open quantum system scenarios in near future. In all cases the results obtained are in excellent agreement with exact numerical computations that bolsters the effectiveness of this technique. The successful demonstrations pave the way for utilizing this adaptive variational technique to study complex systems in chemistry and physics, like light‐harvesting devices, thermal, and opto‐mechanical switches, to name a few.
{"title":"Designing Variational Ansatz for Quantum‐Enabled Simulation of Non‐Unitary Dynamical Evolution ‐ An Excursion into Dicke Supperradiance","authors":"Saurabh Shivpuje, Manas Sajjan, Yuchen Wang, Zixuan Hu, Sabre Kais","doi":"10.1002/qute.202400088","DOIUrl":"https://doi.org/10.1002/qute.202400088","url":null,"abstract":"Adaptive Variational Quantum Dynamics (AVQD) algorithms offer a promising approach to providing quantum‐enabled solutions for systems treated within the purview of open quantum dynamical evolution. In this study, the unrestricted‐vectorization variant of AVQD is employed to simulate and benchmark various non‐unitarily evolving systems. Exemplification of how construction of an expressible ansatz unitary and the associated operator pool can be implemented to analyze examples such as the Fenna–Matthews–Olson complex (FMO) and even the permutational invariant Dicke model of quantum optics. Furthermore, an efficient decomposition scheme is shown for the ansatz used, which can extend its applications to a wide range of other open quantum system scenarios in near future. In all cases the results obtained are in excellent agreement with exact numerical computations that bolsters the effectiveness of this technique. The successful demonstrations pave the way for utilizing this adaptive variational technique to study complex systems in chemistry and physics, like light‐harvesting devices, thermal, and opto‐mechanical switches, to name a few.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140841836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Julian Heckötter, Binodbihari Panda, Katharina Brägelmann, Marc Aßmann, Manfred Bayer
The temperature dependence of Rydberg excitons in with principal quantum numbers is investigated for bath temperatures between 1.3 and 50 K. The energy shift of Rydberg exciton lines allows us to perform a precise measurement of the band gap as a function of temperature. The phonon shows a dominant contribution to the temperature shift of the band gap. The optical properties of Rydberg excitons are analyzed for different temperatures and discussed in the context of phonon scattering as well as thermal ionization of impurities and compared to earlier descriptions in Ref. [1]. The maximum principal quantum number as a function of temperature in crystals of different quality is studied and compared. The observations are correlated to photoluminescence spectra of impurities at different temperatures.
{"title":"A Temperature Study of High‐n$n$ Rydberg States in Cu2O${rm Cu}_2{rm O}$","authors":"Julian Heckötter, Binodbihari Panda, Katharina Brägelmann, Marc Aßmann, Manfred Bayer","doi":"10.1002/qute.202300426","DOIUrl":"https://doi.org/10.1002/qute.202300426","url":null,"abstract":"The temperature dependence of Rydberg excitons in with principal quantum numbers is investigated for bath temperatures between 1.3 and 50 K. The energy shift of Rydberg exciton lines allows us to perform a precise measurement of the band gap as a function of temperature. The phonon shows a dominant contribution to the temperature shift of the band gap. The optical properties of Rydberg excitons are analyzed for different temperatures and discussed in the context of phonon scattering as well as thermal ionization of impurities and compared to earlier descriptions in Ref. [1]. The maximum principal quantum number as a function of temperature in crystals of different quality is studied and compared. The observations are correlated to photoluminescence spectra of impurities at different temperatures.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140635676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carlos Hernani‐Morales, Gabriel Alvarado, Francisco Albarrán‐Arriagada, Yolanda Vives‐Gilabert, Enrique Solano, José D. Martín‐Guerrero
Machine learning (ML) methods are proposed to characterize the memristive properties of single and coupled quantum memristors. It is shown that maximizing the memristivity leads to large values in the degree of entanglement of two quantum memristors, unveiling the close relationship between quantum correlations and memory. The results strengthen the possibility of using quantum memristors as key components of neuromorphic quantum computing.
{"title":"Machine Learning for Maximizing the Memristivity of Single and Coupled Quantum Memristors","authors":"Carlos Hernani‐Morales, Gabriel Alvarado, Francisco Albarrán‐Arriagada, Yolanda Vives‐Gilabert, Enrique Solano, José D. Martín‐Guerrero","doi":"10.1002/qute.202300294","DOIUrl":"https://doi.org/10.1002/qute.202300294","url":null,"abstract":"Machine learning (ML) methods are proposed to characterize the memristive properties of single and coupled quantum memristors. It is shown that maximizing the memristivity leads to large values in the degree of entanglement of two quantum memristors, unveiling the close relationship between quantum correlations and memory. The results strengthen the possibility of using quantum memristors as key components of neuromorphic quantum computing.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140595598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leonardo Banchi, Jason Luke Pereira, Sharu Theresa Jose, Osvaldo Simeone
Learning problems involve settings in which an algorithm has to make decisions based on data, and possibly side information such as expert knowledge. This study has two main goals. First, it reviews and generalizes different results on the data and model complexity of quantum learning, where the data and/or the algorithm can be quantum, focusing on information‐theoretic techniques. Second, it introduces the notion of copy complexity, which quantifies the number of copies of a quantum state required to achieve a target accuracy level. Copy complexity arises from the destructive nature of quantum measurements, which irreversibly alter the state to be processed, limiting the information that can be extracted about quantum data. As a result, empirical risk minimization is generally inapplicable. The paper presents novel results on the copy complexity for both training and testing. To make the paper self‐contained and approachable by different research communities, an extensive background material is provided on classical results from statistical learning theory, as well as on the distinguishability of quantum states. Throughout, the differences between quantum and classical learning are highlighted by addressing both supervised and unsupervised learning, and extensive pointers are provided to the literature.
{"title":"Statistical Complexity of Quantum Learning","authors":"Leonardo Banchi, Jason Luke Pereira, Sharu Theresa Jose, Osvaldo Simeone","doi":"10.1002/qute.202300311","DOIUrl":"https://doi.org/10.1002/qute.202300311","url":null,"abstract":"Learning problems involve settings in which an algorithm has to make decisions based on data, and possibly side information such as expert knowledge. This study has two main goals. First, it reviews and generalizes different results on the data and model complexity of quantum learning, where the data and/or the algorithm can be quantum, focusing on information‐theoretic techniques. Second, it introduces the notion of copy complexity, which quantifies the number of copies of a quantum state required to achieve a target accuracy level. Copy complexity arises from the destructive nature of quantum measurements, which irreversibly alter the state to be processed, limiting the information that can be extracted about quantum data. As a result, empirical risk minimization is generally inapplicable. The paper presents novel results on the copy complexity for both training and testing. To make the paper self‐contained and approachable by different research communities, an extensive background material is provided on classical results from statistical learning theory, as well as on the distinguishability of quantum states. Throughout, the differences between quantum and classical learning are highlighted by addressing both supervised and unsupervised learning, and extensive pointers are provided to the literature.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"96 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140595778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Madeline Hennessey, Benjamin Whitefield, Angus Gale, Mehran Kianinia, John A. Scott, Igor Aharonovich, Milos Toth
Hexagonal boron nitride (hBN) is gaining interest as a wide bandgap van der Waals host of optically active spin defects for quantum technologies. Most studies of the spin‐photon interface in hBN focus on the negatively charged boron vacancy (VB−) defect, which is typically fabricated by ion irradiation. However, the applicability and wide deployment of VB− defects is limited by VB− fabrication methods which lack robustness and reproducibility, particularly when applied to thin flakes (≲10 nm) of hBN. Here, two key factors are elucidated that underpin the formation and quenching of VB− centers by ion irradiation—density of defects generated in the hBN lattice and recoil‐implantation of foreign atoms into hBN. Critically, it is shown that the latter is extremely efficient at inhibiting the generation of optically‐active VB− centers. This is significant because foreign atoms such as carbon are commonplace on both the top and bottom surfaces of hBN during ion irradiation, in the form of hydrocarbon contaminants, polymer residues from hBN transfer methods, protective capping layers and substrates. Recoil implantation must be accounted for when selecting ion beam parameters such as ion mass, energy, fluence, incidence angle, and sputter/span yield, which are discussed in the context of a framework for VB− generation by high‐resolution focused ion beam (FIB) systems.
{"title":"Framework for Engineering of Spin Defects in Hexagonal Boron Nitride by Focused Ion Beams","authors":"Madeline Hennessey, Benjamin Whitefield, Angus Gale, Mehran Kianinia, John A. Scott, Igor Aharonovich, Milos Toth","doi":"10.1002/qute.202300459","DOIUrl":"https://doi.org/10.1002/qute.202300459","url":null,"abstract":"Hexagonal boron nitride (hBN) is gaining interest as a wide bandgap van der Waals host of optically active spin defects for quantum technologies. Most studies of the spin‐photon interface in hBN focus on the negatively charged boron vacancy (V<jats:sub>B</jats:sub><jats:sup>−</jats:sup>) defect, which is typically fabricated by ion irradiation. However, the applicability and wide deployment of V<jats:sub>B</jats:sub><jats:sup>−</jats:sup> defects is limited by V<jats:sub>B</jats:sub><jats:sup>−</jats:sup> fabrication methods which lack robustness and reproducibility, particularly when applied to thin flakes (≲10 nm) of hBN. Here, two key factors are elucidated that underpin the formation and quenching of V<jats:sub>B</jats:sub><jats:sup>−</jats:sup> centers by ion irradiation—density of defects generated in the hBN lattice and recoil‐implantation of foreign atoms into hBN. Critically, it is shown that the latter is extremely efficient at inhibiting the generation of optically‐active V<jats:sub>B</jats:sub><jats:sup>−</jats:sup> centers. This is significant because foreign atoms such as carbon are commonplace on both the top and bottom surfaces of hBN during ion irradiation, in the form of hydrocarbon contaminants, polymer residues from hBN transfer methods, protective capping layers and substrates. Recoil implantation must be accounted for when selecting ion beam parameters such as ion mass, energy, fluence, incidence angle, and sputter/span yield, which are discussed in the context of a framework for V<jats:sub>B</jats:sub><jats:sup>−</jats:sup> generation by high‐resolution focused ion beam (FIB) systems.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140198863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Helen Urgelles, Shivam Maheshwari, Swaraj Shekhar Nande, Riccardo Bassoli, Frank H.P. Fitzek, Jose F. Monserrat
In light of the imperative for expeditious data processing and enhanced global connectivity, the domain of communication technology is experiencing a rapid progression from the Fifth Generation (5G) to the forthcoming Sixth Generation (6G) within the research community. Furthermore, 6G promises to significantly augment the synergy between the human, digital, and physical realms, thereby necessitating the formulation of novel Key Performance Indicators (KPIs) as well as Key Values Indicators (KVIs), and the assimilation of commensurate technologies. Among these technologies, quantum computing is evolving rapidly due to its inherent advantages from quantum mechanics. Nevertheless, scant attention is directed toward a comprehensive exploration of the consequences attendant to its present‐day application. The principal objective of this article resides in its endeavor to underscore, from a compensatory perspective, the convergence of 6G and quantum computing while concurrently considering the Sustainable Development Goals and its KVIs.
{"title":"In‐Network Quantum Computing for Future 6G Networks","authors":"Helen Urgelles, Shivam Maheshwari, Swaraj Shekhar Nande, Riccardo Bassoli, Frank H.P. Fitzek, Jose F. Monserrat","doi":"10.1002/qute.202300334","DOIUrl":"https://doi.org/10.1002/qute.202300334","url":null,"abstract":"In light of the imperative for expeditious data processing and enhanced global connectivity, the domain of communication technology is experiencing a rapid progression from the Fifth Generation (5G) to the forthcoming Sixth Generation (6G) within the research community. Furthermore, 6G promises to significantly augment the synergy between the human, digital, and physical realms, thereby necessitating the formulation of novel Key Performance Indicators (KPIs) as well as Key Values Indicators (KVIs), and the assimilation of commensurate technologies. Among these technologies, quantum computing is evolving rapidly due to its inherent advantages from quantum mechanics. Nevertheless, scant attention is directed toward a comprehensive exploration of the consequences attendant to its present‐day application. The principal objective of this article resides in its endeavor to underscore, from a compensatory perspective, the convergence of 6G and quantum computing while concurrently considering the Sustainable Development Goals and its KVIs.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140108322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Silicon photonics is promising for quantum photonics applications owing to its large-scale and high-performance circuitry enabled by complementary-metal-oxide-semiconductor fabrication processes. However, there is a lack of bright single-photon sources (SPSs) capable of deterministic operation on Si platforms, which largely limits their applications. To this end, on-Si integration of high-performance solid-state quantum emitters, such as semiconductor quantum dots (QDs), is greatly desired. In particular, it is preferable to integrate SPSs emitting at telecom wavelengths for fully leveraging the power of silicon photonics, including efficient chip-to-fiber coupling. In this review, recent progress and challenges in the integration of telecom QD SPSs onto silicon photonic platforms are discussed.
{"title":"Telecom-Band Quantum Dots Compatible with Silicon Photonics for Photonic Quantum Applications","authors":"Ryota Katsumi, Yasutomo Ota, Mohamed Benyoucef","doi":"10.1002/qute.202300423","DOIUrl":"https://doi.org/10.1002/qute.202300423","url":null,"abstract":"Silicon photonics is promising for quantum photonics applications owing to its large-scale and high-performance circuitry enabled by complementary-metal-oxide-semiconductor fabrication processes. However, there is a lack of bright single-photon sources (SPSs) capable of deterministic operation on Si platforms, which largely limits their applications. To this end, on-Si integration of high-performance solid-state quantum emitters, such as semiconductor quantum dots (QDs), is greatly desired. In particular, it is preferable to integrate SPSs emitting at telecom wavelengths for fully leveraging the power of silicon photonics, including efficient chip-to-fiber coupling. In this review, recent progress and challenges in the integration of telecom QD SPSs onto silicon photonic platforms are discussed.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139969033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Massimiliano Incudini, Francesco Martini, Alessandra Di Pierro
Supervised machine learning is a popular approach to the solution of many real-life problems. This approach is characterized by the use of labeled datasets to train algorithms for classifying data or predicting outcomes accurately. The question of the extent to which quantum computation can help improve existing classical supervised learning methods is the subject of intense research in the area of quantum machine learning. The debate centers on whether an advantage can be achieved already with current noisy quantum computer prototypes or it is strictly dependent on the full power of a fault-tolerant quantum computer. The current proposals can be classified into methods that can be suitably implemented on near-term quantum computers but are essentially empirical, and methods that use quantum algorithms with a provable advantage over their classical counterparts but only when implemented on the still unavailable fault-tolerant quantum computer.
{"title":"Toward Useful Quantum Kernels","authors":"Massimiliano Incudini, Francesco Martini, Alessandra Di Pierro","doi":"10.1002/qute.202300298","DOIUrl":"https://doi.org/10.1002/qute.202300298","url":null,"abstract":"Supervised machine learning is a popular approach to the solution of many real-life problems. This approach is characterized by the use of labeled datasets to train algorithms for classifying data or predicting outcomes accurately. The question of the extent to which quantum computation can help improve existing classical supervised learning methods is the subject of intense research in the area of quantum machine learning. The debate centers on whether an advantage can be achieved already with current noisy quantum computer prototypes or it is strictly dependent on the full power of a fault-tolerant quantum computer. The current proposals can be classified into methods that can be suitably implemented on near-term quantum computers but are essentially empirical, and methods that use quantum algorithms with a provable advantage over their classical counterparts but only when implemented on the still unavailable fault-tolerant quantum computer.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139902148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The coordination between distance and the secure key rate is one of the main challenges in the practical application of quantum key distribution (QKD). Mode‐pairing quantum key distribution is one of the schemes that can surpass the secret key capacity for repeaterless QKD. However, the protocol utilizes phase to encode the information, which leads to the problem of active stabilization in the interferometer. In this paper, a reference‐frame‐independent mode‐pairing quantum key distribution (RFI‐MP‐QKD) is proposed as an effective scheme to solve this problem. Moreover, the performance of the RFI‐MP‐QKD protocol is improved by applying the Advantage Distillation (AD) method in data post‐processing, which separates the highly correlated raw key bits from the weakly correlated information. The simulation results show that the secure key rate of RFI‐MP‐QKD has almost no degradation for reference frame deviation angles of . Compared to RFI‐MP‐QKD without AD method, the AD method decreases the quantum bit error rate from 0.04 to 0.012 and increases the maximum transmission distance from 406 to 450 km. The scheme proposed is expected to facilitate the practical implementation of RFI‐MP‐QKD, especially in cases of concerning reference frame alignment and high channel loss.
{"title":"Reference‐Frame‐Independent Mode‐Pairing Quantum Key Distribution with Advantage Distillation","authors":"Yuemei Li, Zhongqi Sun, Xinhe Liu, Zhenhua Li, Jiaao Li, Haoyang Wang, Kaiyi Shi, Chang Liu, Haiqiang Ma","doi":"10.1002/qute.202300387","DOIUrl":"https://doi.org/10.1002/qute.202300387","url":null,"abstract":"The coordination between distance and the secure key rate is one of the main challenges in the practical application of quantum key distribution (QKD). Mode‐pairing quantum key distribution is one of the schemes that can surpass the secret key capacity for repeaterless QKD. However, the protocol utilizes phase to encode the information, which leads to the problem of active stabilization in the interferometer. In this paper, a reference‐frame‐independent mode‐pairing quantum key distribution (RFI‐MP‐QKD) is proposed as an effective scheme to solve this problem. Moreover, the performance of the RFI‐MP‐QKD protocol is improved by applying the Advantage Distillation (AD) method in data post‐processing, which separates the highly correlated raw key bits from the weakly correlated information. The simulation results show that the secure key rate of RFI‐MP‐QKD has almost no degradation for reference frame deviation angles of . Compared to RFI‐MP‐QKD without AD method, the AD method decreases the quantum bit error rate from 0.04 to 0.012 and increases the maximum transmission distance from 406 to 450 km. The scheme proposed is expected to facilitate the practical implementation of RFI‐MP‐QKD, especially in cases of concerning reference frame alignment and high channel loss.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139866010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiahao Huang, Min Zhuang, Jungeng Zhou, Yi Shen, Chaohong Lee
Quantum metrology aims to measure physical quantities based on fundamental quantum principles, enhancing measurement precision through resources like quantum entanglement and quantum correlations. This field holds promise for advancing quantum-enhanced sensors, including atomic clocks and magnetometers. However, practical constraints exist in the four fundamental steps of quantum metrology, including initialization, sensing, readout, and estimation. Valuable resources, such as coherence time, impose limitations on the performance of quantum sensors. Machine learning, enabling learning and prediction without explicit knowledge, provides a powerful tool in optimizing quantum metrology with limited resources. This article reviews the fundamental principles, potential applications, and recent advancements in quantum metrology assisted by machine learning.
{"title":"Quantum Metrology Assisted by Machine Learning","authors":"Jiahao Huang, Min Zhuang, Jungeng Zhou, Yi Shen, Chaohong Lee","doi":"10.1002/qute.202300329","DOIUrl":"https://doi.org/10.1002/qute.202300329","url":null,"abstract":"Quantum metrology aims to measure physical quantities based on fundamental quantum principles, enhancing measurement precision through resources like quantum entanglement and quantum correlations. This field holds promise for advancing quantum-enhanced sensors, including atomic clocks and magnetometers. However, practical constraints exist in the four fundamental steps of quantum metrology, including initialization, sensing, readout, and estimation. Valuable resources, such as coherence time, impose limitations on the performance of quantum sensors. Machine learning, enabling learning and prediction without explicit knowledge, provides a powerful tool in optimizing quantum metrology with limited resources. This article reviews the fundamental principles, potential applications, and recent advancements in quantum metrology assisted by machine learning.","PeriodicalId":501028,"journal":{"name":"Advanced Quantum Technologies","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139588958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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