Bayesian Quantum Multiphase Estimation Algorithm

Anno: 2021

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

Affiliazione autori: QSTAR, INO-CNR, LENS, Largo Enrico Fermi 2, Firenze, 50125, Italy; Universita Degli Studi di Napoli Federico II, Via Cinthia 21, Napoli, 80126, 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.


Volume: 16 (1)      Da Pagina: 014035-1  A: 014035-12

Maggiori informazioni: 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.
Parole chiavi: realization
DOI: 10.1103/PhysRevApplied.16.014035