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STUDY OF NANOSTRUCTURES COUPLED WITH A SUPERCONDUCTING LEAD VIA THE NEURAL-NETWORK QUANTUM STATES METHODS

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10506264" target="_blank" >RIV/00216208:11320/25:10506264 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.37904/metal.2025.5156" target="_blank" >https://doi.org/10.37904/metal.2025.5156</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.37904/metal.2025.5156" target="_blank" >10.37904/metal.2025.5156</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    STUDY OF NANOSTRUCTURES COUPLED WITH A SUPERCONDUCTING LEAD VIA THE NEURAL-NETWORK QUANTUM STATES METHODS

  • Original language description

    The Neural-Network Quantum States (NNQS) method is rapidly emerging as a powerful tool for investigating quantum many-body physics. By combining variational Monte Carlo techniques with neural network-based variational functions, this approach leverages the remarkable advancements in deep learning achieved in recent years. While substantial progress has been made in simulating magnetic systems on lattices, simple molecules, and even continuous systems, the ab initio simulation of complex strongly correlated electron systems continues to pose significant challenges. With the help of the generalized atomic limit (GAL) - a recently developed model describing a system of quantum dots coupled to a superconducting lead - we attempt to show the efficiency and accuracy of NNQS, mainly the Restricted Boltzmann Machine, by comparing the acquired results to other available methods such as exact diagonalization. The simultaneous study of the system&apos;s properties such as the energy spectrum and quantum phase transitions could bring advancements in electronics, sensors or the design of high-quality qubits used in quantum computers.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10302 - Condensed matter physics (including formerly solid state physics, supercond.)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings 34th International Conference on Metallurgy and Materials

  • ISBN

    978-80-88365-27-3

  • ISSN

    2694-9296

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    464-469

  • Publisher name

    Tanger ltd.

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    May 21, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article