5 papers
Quantum machine learning for the quantum lattice Boltzmann method: Trainability of variational quantum circuits for the nonlinear collision operator across multiple time steps
Antonio David Bastida Zamora, Ljubomir Budinski, Pierre Sagaut +1
This study investigates the application of quantum machine learning (QML) to approximate the nonlinear component of the collision operator within the quantum lattice Boltzmann meth…
Quantum algorithm for the lattice Boltzmann method with applications on real quantum devices
Antonio Bastida-Zamora, Ljubomir Budinski, Oskari Kerppo +8
We introduce a novel quantum algorithm for the lattice Boltzmann method (LBM) based on the one-step simplified LBM. The structure of the algorithm allows for more flexibility in mo…
Quantum Orthogonal Separable Physics-Informed Neural Networks
Pietro Zanotta, Ljubomir Budinski, Caglar Aytekin +1
This paper introduces Quantum Orthogonal Separable Physics-Informed Neural Networks (QO-SPINNs), a novel architecture for solving Partial Differential Equations, integrating quantu…
Quantum lattice Boltzmann method for several time steps: A local Carleman linearization algorithm
Antonio David Bastida Zamora, Ljubomir Budinski, Valtteri Lahtinen +1
This article presents a novel encoding for quantum Lattice Boltzmann method algorithm using Carleman linearization. In contrast to previous articles \cite{Sanavio2024LatticeBC,sana…
Adaptive Lattice Gas Algorithm: Classical and Quantum implementations
Niccolò Fonio, Ljubomir Budinski, Valtteri Lahtinen +1
Lattice gas algorithms (LGA) are a class of algorithms including, in chronological order, binary lattice gas cellular automata (LGCA), integer lattice gas algorithms (ILGA) and lat…