2023-03-23T19:32:02Zhttps://ipsj.ixsq.nii.ac.jp/ej/?action=repository_oaipmhoai:ipsj.ixsq.nii.ac.jp:002117882021-06-23T15:00:00Z01164:10193:10565:10617
Classical Shadow with Decision DiagramsClassical Shadow with Decision Diagramsenghttp://id.nii.ac.jp/1001/00211682/Technical Reporthttps://ipsj.ixsq.nii.ac.jp/ej/?action=repository_action_common_download&item_id=211788&item_no=1&attribute_id=1&file_no=1Copyright (c) 2021 by the Information Processing Society of JapanIBM Quantum, IBM Japan／Quantum Computing Center, Keio UniversityJohannes Kepler University LinzIBM Quantum, IBM T.J. Watson Research CenterIBM Quantum, IBM T.J. Watson Research CenterJohannes Kepler University Linz／Software Competence Center Hagenberg (SCCH) GmbHRudy, RaymondStefan, HillmichCharles, HadfieldAntonio, MezzacapoRobert, WilleWe consider the problem of estimating quantum observables on a collection of qubits, given as a linear combination of Pauli operators, with shallow quantum circuits consisting of single-qubit rotations. We introduce estimators based on classical shadow, which use decision diagrams to sample from probability distributions on measurement bases. This approach generalises previously known uniform and locally-biased classical shadows. The decision diagrams are constructed given target quantum operators and can be optimised considering different strategies. We show numerically that the estimators introduced here can produce more precise estimates on some quantum chemistry Hamiltonians, compared to previously known randomised protocols and Pauli grouping methods. The details are given at [Hillmich et al., arXiv:2105.06932]We consider the problem of estimating quantum observables on a collection of qubits, given as a linear combination of Pauli operators, with shallow quantum circuits consisting of single-qubit rotations. We introduce estimators based on classical shadow, which use decision diagrams to sample from probability distributions on measurement bases. This approach generalises previously known uniform and locally-biased classical shadows. The decision diagrams are constructed given target quantum operators and can be optimised considering different strategies. We show numerically that the estimators introduced here can produce more precise estimates on some quantum chemistry Hamiltonians, compared to previously known randomised protocols and Pauli grouping methods. The details are given at [Hillmich et al., arXiv:2105.06932]AA12894105量子ソフトウェア（QS）2021-QS-313182021-06-242435-64922021-06-22