Quantum state estimation when qubits are lost: a nodataleftbehind approach
We present an approach to Bayesian mean estimation of quantum states using hyperspherical parametrization and an experimentspecific likelihood which allows utilization of all available data, even when qubits are lost. With this method, we report the first closedform Bayesian mean and maximum likelihood estimates for the ideal single qubit. Due to computational constraints, we utilize numerical sampling to determine the Bayesian mean estimate for a photonic twoqubit experiment in which our novel analysis reduces burdens associated with experimental asymmetries and inefficiencies. This method can be applied to quantum states of any dimension and experimental complexity.
 Authors:

^{[1]}
;
^{[1]}
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Quantum Information Science Group
 Publication Date:
 Grant/Contract Number:
 AC0500OR22725; Contract No. DEAC0500OR22725
 Type:
 Published Article
 Journal Name:
 New Journal of Physics
 Additional Journal Information:
 Journal Volume: 19; Journal Issue: 4; Journal ID: ISSN 13672630
 Publisher:
 IOP Publishing
 Research Org:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 Sponsoring Org:
 USDOE
 Country of Publication:
 United States
 Language:
 English
 Subject:
 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; quantum state estimation; Bayesian; qubit; inference; slice sampling; Monte Carlo
 OSTI Identifier:
 1349952
 Alternate Identifier(s):
 OSTI ID: 1352764
Williams, Brian P., and Lougovski, Pavel. Quantum state estimation when qubits are lost: a nodataleftbehind approach. United States: N. p.,
Web. doi:10.1088/13672630/aa65de.
Williams, Brian P., & Lougovski, Pavel. Quantum state estimation when qubits are lost: a nodataleftbehind approach. United States. doi:10.1088/13672630/aa65de.
Williams, Brian P., and Lougovski, Pavel. 2017.
"Quantum state estimation when qubits are lost: a nodataleftbehind approach". United States.
doi:10.1088/13672630/aa65de.
@article{osti_1349952,
title = {Quantum state estimation when qubits are lost: a nodataleftbehind approach},
author = {Williams, Brian P. and Lougovski, Pavel},
abstractNote = {We present an approach to Bayesian mean estimation of quantum states using hyperspherical parametrization and an experimentspecific likelihood which allows utilization of all available data, even when qubits are lost. With this method, we report the first closedform Bayesian mean and maximum likelihood estimates for the ideal single qubit. Due to computational constraints, we utilize numerical sampling to determine the Bayesian mean estimate for a photonic twoqubit experiment in which our novel analysis reduces burdens associated with experimental asymmetries and inefficiencies. This method can be applied to quantum states of any dimension and experimental complexity.},
doi = {10.1088/13672630/aa65de},
journal = {New Journal of Physics},
number = 4,
volume = 19,
place = {United States},
year = {2017},
month = {4}
}