Abstracts Archive

Due to the fact that quantum computers have the potential to produce a significant gain in computational performance, their features have been used to develop several solution strategies for partial differential equations (PDEs). Among the different types of PDEs, the advection equation is of partic...

The lattice Boltzmann method (LBM) is widely used for simulating fluid dynamics due to its simplicity and strong parallelizability. However, its collision operator inherently contains nonlinear terms, which pose a fundamental obstacle to efficient implementation on quantum computers. Quantum computa...

Many real-world scientific and engineering problems-particularly in computational fluid dynamics (CFD), heat transfer, and nonlinear dynamics-reduce to solving large, sparse systems of linear equations or their time-evolution counterparts. Examples include discretized partial differential equations ...

The simulations of fluid dynamics play an important role in many areas of research and engineering, including climate prediction [1], biomedical applications [2], and the optimization of aircraft designs [3]. Among the available numerical methods, direct numerical simulation (DNS) provides the highe...

This submission is about matrix inversion with quantum computers, a foundational subroutine in quantum algorithms.A large variety of real-world problems can be described by linear algebra. Even non-linear systems can be described by linear algebra by a process called linearisation. Whenever a system...

We propose a quantum algorithm for fluid simulation based on the Lattice Boltzmann method (LBM). LBM is widely used in computational fluid dynamics because it evolves particle distribution functions on a discrete lattice through local collision and streaming steps. This structure combines simple upd...

Accurate treatment of boundary conditions is a central requirement in computational fluid dynamics (CFD). For flows at the macroscale, the no-slip condition at the wall is well established. However, this assumption breaks down in microscale or rarefied flow regimes, where the mean free path of fluid...

Accurate climate prediction requires the numerical simulation of nonlinear, multiscale, and often chaotic dynamical systems over long time periods. Despite major progress in climate modelling, substantial uncertainty persists in key quantities such as climate sensitivity, extremes, and long-time var...

High-fidelity computational fluid dynamics (CFD) requires a massive number of degrees of freedom, leading to prohibitive memory consumption even on modern supercomputers. Quantum computing is attracting increasing attention as a potential solution to this limitation. However, most existing studies o...

In this work, we introduce a reduced-basis algorithm (RBA) for solving polynomial nonlinear differential equations on quantum computers. Solving these types of equations remains one of the most challenging tasks in developing quantum algorithms that can be useful for real-world applications. This is...

Quantum lattice Boltzmann methods (QLBM) offer a promising framework for simulating Computational Fluid Dynamics (CFD) using quantum circuits. Recent work has introduced a zone-agnostic (ZA) method for implementing boundary conditions for complex shapes, without iterating through each segment of the...

The lattice Boltzmann method (LBM) is an established explicit time-marching scheme in computational fluid dynamics (CFD). Its success is rooted to the fact that it is relatively simple, resulting in flexibility for the implementation and the advantage that it is relatively easy to parallelize on cla...

Approximately solving complex nonlinear partial differential equations of industrial relevance remains a computational challenge. In the field of computational fluid dynamics (CFD), an established tool in academia, research and industry, nonlinear compressible transport equations arise, for example,...

Aeroacoustic noise prediction is a standard industrial computation. Jet noise, airframe noise, fan noise, and combustion noise are all predicted within the Lighthill framework. A separately computed turbulent flow acts as a prescribed monopole, dipole, or quadrupole source, and the radiated sound pr...

We employ a variational quantum algorithm (VQA) to numerically simulate hydroxide-ion transport across a two-layer anion exchange membrane (AEM). An AEM electrolyzer, depicted in Fig. 1(a), uses the AEM to efficiently convert electrical energy into chemical energy stored in hydrogen, while safely se...

High-fidelity simulation of complex transport phenomena remains a central challenge in computational fluid dynamics. Direct Numerical Simulation (DNS) can resolve fluid behaviour with high accuracy, but its extremely large computational and memory requirements make it impractical for large-scale or ...

Solving partial differential equations (PDEs) is a cornerstone of computational physics and engineering. One important class of PDEs are parabolic PDEs that can be used to model transient diffusion processes. In fluid mechanics, diffusion processes describe the transport of a physical quantity (such...

Recent works on quantum lattice Boltzmann methods (QLBM) have begun to move beyond model constructions [1, 2] toward optimization-oriented scientific-computing applications [3]. In particular, the emerging perspective of quantum search based on QLBM, treats multiple lattice configurations as candida...

The simulation of fluid flow using Computational Fluid Dynamics (CFD) is a central tool in many areas of science and engineering, including aerodynamics, energy systems, and climate modeling. For numerical simulations, the underlying partial differential equations, such as the Navier–Stokes equati...

Nonlinear partial differential equations (PDEs) are fundamental descriptions of the physical world and are key to science and engineering. Examples include compressible Navier-Stokes equations for fluids and reaction-diffusion equations for population dynamics and chemical reactions. However, for qu...

Electrochemical energy storage systems are a cornerstone of the global transition towards renewable energies. Lithium-ion batteries are used in portable electronical devices, electric vehicles and grid-scale renewable energy systems. Their internal dynamics are described by complex physical processe...

Thermodynamic and fluid dynamic phenomena occur in a wide range of applications in both industry and academia [2, 10, 13, 14]. However, detailed analysis requires resolution on smaller length scales [12], for which Quantum Computers (QCs) offer significantly greater computational resources compared ...

The Lattice Boltzmann Method (LBM) offers a robust, highly parallelizable kinetic framework for computational fluid dynamics, with strengths in resolving complex transport phenomena in intricate geometries. Yet scaling Direct Numerical Simulation (DNS) to large three-dimensional grids quickly runs i...