VSE knjižnice (vzajemna bibliografsko-kataložna baza podatkov COBIB.SI)
  • Boosting the performance of quantum annealers using machine learning [Elektronski vir]
    Brence, Jure ...
    Noisy intermediate-scale quantum (NISQ) devices are spearheading the second quantum revolution. Of these, quantum annealers are the only ones currently offering real world, commercial applications on ... as many as 5000 qubits. The size of problems that can be solved by quantum annealers is limited mainly by errors caused by environmental noise and intrinsic imperfections of the processor. We address the issue of intrinsic imperfections with a novel error correction approach, based on machine learning methods. Our approach adjusts the input Hamiltonian to maximize the probability of finding the solution. In our experiments, the proposed error correction method improved the performance of annealing by up to three orders of magnitude and enabled the solving of a previously intractable, maximally complex problem.
    Vir: Quantum machine intelligence. - ISSN 2524-4914 (Vol. 5, iss. 1, article no. 4, Jun. 2023, str. 1-11)
    Vrsta gradiva - e-članek ; neleposlovje za odrasle
    Leto - 2023
    Jezik - angleški
    COBISS.SI-ID - 138944003
    DOI

Vnos na polico