Highly accurate Gaussian process tomography with geometrical sets of coherent states

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F21%3A73607276" target="_blank" >RIV/61989592:15310/21:73607276 - isvavai.cz</a>

Výsledek na webu

<a href="https://iopscience.iop.org/article/10.1088/1367-2630/abf702" target="_blank" >https://iopscience.iop.org/article/10.1088/1367-2630/abf702</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1367-2630/abf702" target="_blank" >10.1088/1367-2630/abf702</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Highly accurate Gaussian process tomography with geometrical sets of coherent states

Popis výsledku v původním jazyce

We propose a practical strategy for choosing sets of input coherent states that are near-optimal for reconstructing single-mode Gaussian quantum processes with output-state heterodyne measurements. We first derive analytical expressions for the mean squared-error that quantifies the reconstruction accuracy for general process tomography and large data. Using such expressions, upon relaxing the trace-preserving (TP) constraint, we introduce an error-reducing set of input coherent states that is independent of the measurement data or the unknown true process-the geometrical set. We numerically show that process reconstruction from such input coherent states is nearly as accurate as that from the best possible set of coherent states chosen with the complete knowledge about the process. This allows us to efficiently characterize Gaussian processes even with reasonably low-energy coherent states. We numerically observe that the geometrical strategy without trace preservation beats all nonadaptive strategies for arbitrary TP Gaussian processes of typical parameter ranges so long as the displacement components are not too large.

Název v anglickém jazyce

Highly accurate Gaussian process tomography with geometrical sets of coherent states

Popis výsledku anglicky

We propose a practical strategy for choosing sets of input coherent states that are near-optimal for reconstructing single-mode Gaussian quantum processes with output-state heterodyne measurements. We first derive analytical expressions for the mean squared-error that quantifies the reconstruction accuracy for general process tomography and large data. Using such expressions, upon relaxing the trace-preserving (TP) constraint, we introduce an error-reducing set of input coherent states that is independent of the measurement data or the unknown true process-the geometrical set. We numerically show that process reconstruction from such input coherent states is nearly as accurate as that from the best possible set of coherent states chosen with the complete knowledge about the process. This allows us to efficiently characterize Gaussian processes even with reasonably low-energy coherent states. We numerically observe that the geometrical strategy without trace preservation beats all nonadaptive strategies for arbitrary TP Gaussian processes of typical parameter ranges so long as the displacement components are not too large.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10306 - Optics (including laser optics and quantum optics)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

New Journal of Physics

ISSN

1367-2630

e-ISSN

—

Svazek periodika

23

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

16

Strana od-do

"063024-1"-"063024-16"

Kód UT WoS článku

000659670600001

EID výsledku v databázi Scopus

2-s2.0-85108027658