Deep learning of quantum entanglement from incomplete measurements

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F23%3A73619529" target="_blank" >RIV/61989592:15310/23:73619529 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.science.org/doi/10.1126/sciadv.add7131" target="_blank" >https://www.science.org/doi/10.1126/sciadv.add7131</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1126/sciadv.add7131" target="_blank" >10.1126/sciadv.add7131</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Deep learning of quantum entanglement from incomplete measurements

Popis výsledku v původním jazyce

The quantification of the entanglement present in a physical system is of paramount importance for fundamental research and many cutting-edge applications. Now, achieving this goal requires either a priori knowledge on the system or very demanding experimental procedures such as full state tomography or collective measurements. Here, we demonstrate that, by using neural networks, we can quantify the degree of entanglement without the need to know the full description of the quantum state. Our method allows for direct quantification of the quantum correlations using an incomplete set of local measurements. Despite using undersampled measurements, we achieve a quantification error of up to an order of magnitude lower than the state-of-the-art quantum tomography. Furthermore, we achieve this result using networks trained using exclusively simulated data. Last, we derive a method based on a convolutional network input that can accept data from various measurement scenarios and perform, to some extent, independently of the measurement device.

Název v anglickém jazyce

Deep learning of quantum entanglement from incomplete measurements

Popis výsledku anglicky

The quantification of the entanglement present in a physical system is of paramount importance for fundamental research and many cutting-edge applications. Now, achieving this goal requires either a priori knowledge on the system or very demanding experimental procedures such as full state tomography or collective measurements. Here, we demonstrate that, by using neural networks, we can quantify the degree of entanglement without the need to know the full description of the quantum state. Our method allows for direct quantification of the quantum correlations using an incomplete set of local measurements. Despite using undersampled measurements, we achieve a quantification error of up to an order of magnitude lower than the state-of-the-art quantum tomography. Furthermore, we achieve this result using networks trained using exclusively simulated data. Last, we derive a method based on a convolutional network input that can accept data from various measurement scenarios and perform, to some extent, independently of the measurement device.

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

2023

Kód důvěrnosti údajů

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

Název periodika

Science Advances

ISSN

2375-2548

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

29

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

9

Strana od-do

"eadd7131-1"-"eadd7131-9"

Kód UT WoS článku

001032686800019

EID výsledku v databázi Scopus

2-s2.0-85130465710