All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Revealing nonclassicality of multiphoton optical beams via artificial neural networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F24%3A00598466" target="_blank" >RIV/68378271:_____/24:00598466 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989592:15310/24:73626520

  • Result on the web

    <a href="https://hdl.handle.net/11104/0356130" target="_blank" >https://hdl.handle.net/11104/0356130</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1103/PhysRevApplied.22.034048" target="_blank" >10.1103/PhysRevApplied.22.034048</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Revealing nonclassicality of multiphoton optical beams via artificial neural networks

  • Original language description

    The identification of nonclassical features of multiphoton quantum states represents a task of the utmost importance in the development of many quantum photonic technologies. Under realistic experimental conditions, a photonic quantum state gets affected by its interaction with several nonideal opto-electronic devices, including those used to guide, detect or characterize it. The result of such noisy interaction is that the nonclassical features of the original quantum state get considerably reduced or are completely absent in the detected, final state. In this work, the self-learning features of artificial neural networks are exploited to experimentally show that the nonclassicality of multiphoton quantum states can be assessed and fully characterized, even in the cases in which the nonclassical features are concealed by the measuring devices. Our work paves the way toward artificial-intelligence-assisted experimental-setup characterization, as well as smart quantum-state nonclassicality identification.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10306 - Optics (including laser optics and quantum optics)

Result continuities

  • Project

    <a href="/en/project/EH22_008%2F0004596" target="_blank" >EH22_008/0004596: Sensors and Detectors for Future Information Society</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Physical Review Applied

  • ISSN

    2331-7019

  • e-ISSN

    2331-7019

  • Volume of the periodical

    22

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    11

  • Pages from-to

    034048

  • UT code for WoS article

    001329205400001

  • EID of the result in the Scopus database

    2-s2.0-85204797914