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We propose a quantum algorithm for the Lattice Boltzmann (LB) method to simulate fluid flows in the low Reynolds number regime. First, we encode the particle distribution functions (PDFs) as probability amplitudes of the quantum state and…

Quantum Physics · Physics 2025-02-20 E. Dinesh Kumar , Steven H. Frankel

Despite their high predictive performance, random forest and gradient boosting are often considered as black boxes or uninterpretable models which has raised concerns from practitioners and regulators. As an alternative, we propose in this…

Machine Learning · Statistics 2022-03-23 Emmanuel Flachaire , Gilles Hacheme , Sullivan Hué , Sébastien Laurent

A condensed history and theoretical development of lattice-gas automata in the Boltzmann limit is presented. This is provided as background to set up the context for understanding the implementation of the lattice-gas method on two parallel…

comp-gas · Physics 2008-02-03 Jeffrey Yepez , Guy P. Seeley , Norman Margolus

The lattice Boltzmann method (LBM) has experienced tremendous advances and been well accepted as a popular method of simulation of various fluid flow mechanisms on pore scale in tight formations. With the introduction of an effective…

Fluid Dynamics · Physics 2016-01-07 Junjian Wang , Li Chen , Qinjun Kang , Sheik S Rahman

A Lattice Boltzmann scheme has been applied to the problem of heat and mass transport in packagings of cut flowers. The LB scheme, simulating convection-diffusion processes and heat and mass transfer between flowers and air flow, is…

comp-gas · Physics 2008-02-03 R. G. M. van der Sman , M. F. M. Janssens

The Lattice Boltzmann method (LBM) offers a powerful and versatile approach to simulating diverse hydrodynamic phenomena, spanning microfluidics to aerodynamics. The vast range of spatiotemporal scales inherent in these systems currently…

The implementation of adaptive genetic algorithms (AGA) for optimization problems has proven to be superior than many other methods due to its nature of producing more robust and high quality solutions. Considering the complexity involved…

Computational Physics · Physics 2024-11-28 Brandon Willnecker , Mervlyn Moodley

A recent reformulation [1] of the problem of Coulomb gases in the presence of a dynamical dielectric medium showed that finite temperature simulations of such systems can be accomplished on the basis of completely local Hamiltonians on a…

Soft Condensed Matter · Physics 2009-11-11 A. Duncan , R. D. Sedgewick

While universal quantum computers remain under development, analog quantum simulators offer a powerful alternative for understanding complex systems in condensed matter, chemistry, and high-energy physics. One compelling application is the…

In the future, ab initio quantum simulations of heavy ion collisions may become possible with large-scale fault-tolerant quantum computers. We propose a quantum algorithm for studying these collisions by looking at a class of observables…

High Energy Physics - Lattice · Physics 2021-12-08 Thomas D. Cohen , Henry Lamm , Scott Lawrence , Yukari Yamauchi

Several cellular automata (CA) models have been developed to simulate self-organization of multiple levels of structures. However, they do not obey microscopic reversibility and conservation laws. In this paper, we describe the construction…

Cellular Automata and Lattice Gases · Physics 2015-05-13 Takayuki Nozawa , Toshiyuki Kondo

Layered Cellular Automata (LCA) extends the concept of traditional cellular automata (CA) to model complex systems and phenomena. In LCA, each cell's next state is determined by the interaction of two layers of computation, allowing for…

Cellular Automata and Lattice Gases · Physics 2023-08-15 Abhishek Dalai

We attempt the use of a unitary operator to approximate the lattice Boltzmann collision operator. We use a modified amplitude encoding to bypass the renormalization that would have required classical processing at every step (thus eroding…

Quantum Physics · Physics 2026-01-08 Wael Itani , Katepalli R. Sreenivasan

We present a quantum computing algorithm for fluid flows based on the Carleman-linearization of the Lattice Boltzmann (LB) method. First, we demonstrate the convergence of the classical Carleman procedure at moderate Reynolds numbers,…

Quantum Physics · Physics 2024-05-21 Claudio Sanavio , Sauro Succi

The simulation of geometrically resolved rigid particles in a fluid relies on coupling algorithms to transfer momentum both ways between the particles and the fluid. In this article, the fluid flow is modeled with a parallel Lattice…

Fluid Dynamics · Physics 2021-03-22 Lukas Werner , Christoph Rettinger , Ulrich Rüde

In this paper, for the first time a theory is formulated that predicts velocity and spatial correlations between occupation numbers that occur in lattice gas automata violating semi-detailed balance. Starting from a coupled BBGKY hierarchy…

comp-gas · Physics 2009-10-22 H. J. Bussemaker , M. H. Ernst , J. W. Dufty

A GPU-accelerated version of the lattice Boltzmann method for efficient simulation of soft materials is introduced. Unlike standard approaches, this method reconstructs the distribution functions from available hydrodynamic variables…

In this study a new numerical approach of the fluid dynamic, the lattice Boltzmann method (LBM), is used to solved the stream in a atmospheric Argon-nitrogen plasma jet. The axial symmetry and the variation of density, viscosity and…

Materials Science · Physics 2010-02-17 Ridha Djebeli , Nicolas Calve , Bernard Pateyron , Mohamed El Ganaoui , Habib Sammouda

Variational quantum algorithms provide feasible approaches for simulating quantum systems and are applied widely. For lattice gauge theory, however, variational quantum simulation faces a challenge as local gauge invariance enforces a…

Quantum Physics · Physics 2024-09-02 Lang-Xing Cheng , Dan-Bo Zhang

Cellular automata (CA) are a class of computational models that exhibit rich dynamics emerging from the local interaction of cells arranged in a regular lattice. In this work we focus on a generalised version of typical CA, called graph…

Machine Learning · Computer Science 2021-10-28 Daniele Grattarola , Lorenzo Livi , Cesare Alippi