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    Adaptive lattice-gas algorithm: Classical and quantum implementations

    Niccolò Fonio*,† and Pierre Sagaut‡

    Ljubomir Budinski§ and Valtteri Lahtinen

    • Quanscient Oy, Åkerlundinkatu 8, 33100 Tampere, Finland

    • *Contact author: niccol.fonio11@gmail.com
    • †Also at Laboratoire d'Informatique et Systèmes, Aix Marseille Univ, CNRS, LIS, Marseille, France.
    • ‡Also at Quanscient Oy, Finland.
    • §Also at Faculty of Technical Sciences, University of Novi Sad, Serbia.

    Phys. Rev. E 112, 035302 – Published 2 September, 2025

    DOI: https://doi.org/10.1103/l51d-dpb6

    Abstract

    Lattice-gas algorithms (LGA) are a class of algorithms including, in chronological order, binary lattice-gas cellular automata, integer lattice-gas algorithms (ILGA), and lattice Boltzmann method (LBM). They are largely used for simulating nonlinear systems. Starting from one-dimensional ILGA, we design an algorithm where we carry out a fraction of the possible collisions. These fractions are then adapted to reproduce LBM equilibrium distributions, resulting in an adaptive lattice-gas algorithm that achieves the same simulation results of LBM. Considering this, we develop a quantum algorithm that involves a linear collision operator capable of simulating the same phenomena, while still using a measurement and reinitialization procedure. Multi-time-step implementation is possible in some specific cases, briefly discussed.

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