Proper error bars for self-calibrating quantum tomography

Jun Yan Sim, Jiangwei Shang, Hui Khoon Ng, and Berthold-Georg Englert
Phys. Rev. A 100, 022333 – Published 26 August 2019

Abstract

Self-calibrating quantum state tomography aims at reconstructing the unknown quantum state and certain properties of the measurement devices from the same data. Since the estimates of the state and device parameters come from the same data, one should employ a joint estimation scheme, including the construction and reporting of joint state-device error regions, to quantify uncertainty. We explain how to do this naturally within the framework of optimal error regions. As an illustrative example, we apply our procedure to the double-crosshair measurement of the BB84 scenario in quantum cryptography and so reconstruct the state and estimate the detection efficiencies simultaneously and reliably. We also discuss the practical situation of a satellite-based quantum key distribution scheme, for which self-calibration and proper treatment of the data are necessities.

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  • Received 6 May 2019

DOI:https://doi.org/10.1103/PhysRevA.100.022333

©2019 American Physical Society

Physics Subject Headings (PhySH)

  1. Research Areas
Quantum Information, Science & Technology

Authors & Affiliations

Jun Yan Sim1,2,*, Jiangwei Shang3,1,4,†, Hui Khoon Ng5,1,6,‡, and Berthold-Georg Englert1,2,6,§

  • 1Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543, Singapore
  • 2Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117551, Singapore
  • 3Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement, Ministry of Education and School of Physics, Beijing Institute of Technology, Beijing 100081, China
  • 4Naturwissenschaftlich-Technische Fakultät, Universität Siegen, Walter-Flex-Straße 3, 57068 Siegen, Germany
  • 5Yale-NUS College, 16 College Avenue West, Singapore 138527, Singapore
  • 6MajuLab, International Joint Research Unit UMI 3654, Centre National de la Recherche Scientifique, Université Côte d'Azur, Sorbonne Université, National University of Singapore, Nanyang Technological University, Singapore

  • *e0012429@u.nus.edu
  • jiangwei.shang@bit.edu.cn
  • cqtnhk@nus.edu.sg
  • §cqtebg@nus.edu.sg

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Issue

Vol. 100, Iss. 2 — August 2019

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