Global optimization of spin Hamiltonians with gain-dissipative systems

Kirill P. Kalinin, Natalia G. Berloff

    Research output: Contribution to journalArticlepeer-review

    32 Citations (Scopus)


    Recently, several platforms were proposed and demonstrated a proof-of-principle for finding the global minimum of the spin Hamiltonians such as the Ising and XY models using gain-dissipative quantum and classical systems. The implementation of dynamical adjustment of the gain and coupling strengths has been established as a vital feedback mechanism for analog Hamiltonian physical systems that aim to simulate spin Hamiltonians. Based on the principle of operation of such simulators we develop a novel class of gain-dissipative algorithms for global optimisation of NP-hard problems and show its performance in comparison with the classical global optimisation algorithms. These systems can be used to study the ground state and statistical properties of spin systems and as a direct benchmark for the performance testing of the gain-dissipative physical simulators. Our theoretical and numerical estimations suggest that for large problem sizes the analog simulator when built might outperform the classical computer computations by several orders of magnitude under certain assumptions about the simulator operation.

    Original languageEnglish
    Article number17791
    JournalScientific Reports
    Issue number1
    Publication statusPublished - 1 Dec 2018


    Dive into the research topics of 'Global optimization of spin Hamiltonians with gain-dissipative systems'. Together they form a unique fingerprint.

    Cite this