Quantum-enhanced mean value estimation via adaptive measurement

• Item type: SIG Technical Reports(1)
• 公開日: 2022-10-20
• タイトル: Quantum-enhanced mean value estimation via adaptive measurement
• タイトル / 言語: en
• タイトル: Quantum-enhanced mean value estimation via adaptive measurement
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Department of Applied Physics and Physico-Informatics, Keio University
• 著者所属: Department of Applied Physics and Physico-Informatics, Keio University
• 著者所属: Department of Applied Physics and Physico-Informatics, Keio University／Quantum Computing Center, Keio University
• 著者所属(英): en
• 著者所属(英): Department of Applied Physics and Physico-Informatics, Keio University
• 著者所属(英): en
• 著者所属(英): Department of Applied Physics and Physico-Informatics, Keio University
• 著者所属(英): en
• 著者所属(英): Department of Applied Physics and Physico-Informatics, Keio University / Quantum Computing Center, Keio University
• 著者名: Kaito, Wada; Kazuma, Fukuchi; Naoki, Yamamoto
• 著者名(英): Kaito, Wada; Kazuma, Fukuchi; Naoki, Yamamoto
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Estimating the mean values of quantum observables is a fundamental task in quantum computing. In particular, efficient estimation in a noisy environment requires us to develop a sophisticated measurement strategy. Here, we propose a quantum-enhanced estimation method for the mean values, that adaptively optimizes the measurement (POVM) for each circuit; as a result of optimization, the estimation precision gets close to the quantum Cramer-Rao lower bound, that is, inverse of the quantum Fisher information. We provide a rigorous analysis for the statistical properties of the proposed adaptive estimation method such as consistency and asymptotic normality. Furthermore, several numerical simulations with large system dimension are provided to show that the estimator needs only a reasonable number of measurements to almost saturate the quantum Cramer-Rao bound.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Estimating the mean values of quantum observables is a fundamental task in quantum computing. In particular, efficient estimation in a noisy environment requires us to develop a sophisticated measurement strategy. Here, we propose a quantum-enhanced estimation method for the mean values, that adaptively optimizes the measurement (POVM) for each circuit; as a result of optimization, the estimation precision gets close to the quantum Cramer-Rao lower bound, that is, inverse of the quantum Fisher information. We provide a rigorous analysis for the statistical properties of the proposed adaptive estimation method such as consistency and asymptotic normality. Furthermore, several numerical simulations with large system dimension are provided to show that the estimator needs only a reasonable number of measurements to almost saturate the quantum Cramer-Rao bound.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA12894105
• 書誌情報: 研究報告量子ソフトウェア（QS）; 巻 2022-QS-7, 号 24, p. 1-10, 発行日 2022-10-20
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2435-6492
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会