Bayesian Quantum Multiphase Estimation Algorithm

Year: 2021

Authors: Gebhart V., Smerzi A., Pezzè L.

Autors Affiliation: QSTAR, Largo Enrico Fermi 2, I-50125 Florence, Italy; CNR, INO, Largo Enrico Fermi 2, I-50125 Florence, Italy; LENS, Largo Enrico Fermi 2, I-50125 Florence, Italy; Univ Napoli Federico II, Via Cinthia 21, I-80126 Naples, Italy.

Abstract: Quantum phase estimation (QPE) is the key subroutine of several quantum computing algorithms as well as a central ingredient in quantum computational chemistry and quantum simulation. While QPE strategies have focused on the estimation of a single phase, applications to the simultaneous estimation of several phases may bring substantial advantages; for instance, in the presence of spatial or temporal constraints. In this work, we study a Bayesian algorithm for the parallel (simultaneous) estimation of multiple arbitrary phases. The protocol gives access to correlations in the Bayesian multiphase distribution resulting in covariance matrix elements scaling as O(NT-2), with respect to the total number of quantum resources NT. The parallel estimation allows to surpass the sensitivity of sequential single-phase estimation strategies for optimal linear combinations of phases. Furthermore, the algorithm proves a certain noise resilience and can be implemented using single photons and standard optical elements in currently accessible experiments.

Journal/Review: PHYSICAL REVIEW APPLIED

Volume: 16 (1)      Pages from: 014035-1  to: 014035-12

More Information: We acknowledge financial support from the European Union´s Horizon 2020 research and innovation program-Qombs Project, FET Flagship on Quantum Technologies Grant No. 820419.
KeyWords: realization
DOI: 10.1103/PhysRevApplied.16.014035

Citations: 19
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-10-27
References taken from IsiWeb of Knowledge: (subscribers only)
Connecting to view paper tab on IsiWeb: Click here
Connecting to view citations from IsiWeb: Click here