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We present a mapping of the nonlinear, electrostatic Vlasov equation with Krook-type collision operators, discretized on a (1+1) dimensional grid, onto a recent Carleman linearization-based quantum algorithm for solving ordinary…

Quantum Physics · Physics 2025-05-27 Tamás Vaszary , Animesh Datta , Tom Goffrey , Brian Appelbe

A novel second order family of explicit stabilized Runge-Kutta-Chebyshev methods for advection-diffusion-reaction equations is introduced. The new methods outperform existing schemes for relatively high Peclet number due to their favorable…

Numerical Analysis · Mathematics 2023-06-09 Ibrahim Almuslimani

The classical Ka\v{c}anov scheme for the solution of nonlinear variational problems can be interpreted as a fixed point iteration method that updates a given approximation by solving a linear problem in each step. Based on this observation,…

Numerical Analysis · Mathematics 2021-11-30 Pascal Heid , Thomas P. Wihler

In this study, the numerical solutions of reaction-diffusion systems are investigated via the trigonometric quintic B-spline nite element collocation method. These equations appear in various disciplines in order to describe certain…

Numerical Analysis · Mathematics 2017-01-18 Aysun Tok Onarcan , Nihat Adar , İdiris Dag

In this paper, we explore the embedding of nonlinear dynamical systems into linear ordinary differential equations (ODEs) via the Carleman linearization method. Under dissipative conditions, numerous previous works have established rigorous…

Quantum Physics · Physics 2025-02-03 Hsuan-Cheng Wu , Jingyao Wang , Xiantao Li

We present a new algorithm for finding isolated zeros of a system of real-valued functions in a bounded interval in $\mathbb{R}^n$. It uses the Chebyshev proxy method combined with a mixture of subdivision, reduction methods, and…

This paper proposes a novel reaction-diffusion system approximation tailored for singular diffusion problems, typified by the fast diffusion equation. While such approximation methods have been successfully applied to degenerate parabolic…

Analysis of PDEs · Mathematics 2026-04-01 Hideki Murakawa , Florian Salin

We examine several numerical techniques for the calculation of the dynamics of quantum systems. In particular, we single out an iterative method which is based on expanding the time evolution operator into a finite series of Chebyshev…

Strongly Correlated Electrons · Physics 2015-05-13 Holger Fehske , Jens Schleede , Gerald Schubert , Gerhard Wellein , Vladimir S. Filinov , Alan R. Bishop

Systems of reaction-diffusion equations are commonly used in biological models of food chains. The populations and their complicated interactions present numerous challenges in theory and in numerical approximation. In particular,…

Numerical Analysis · Mathematics 2015-10-28 Matthew Beauregard , Joshua Padgett , Rana Parshad

We present a method for solving the reaction-diffusion equation with general potential in free space. It is based on the approximation of the Feynman-Kac formula by a sequence of convolutions on sequentially diminishing grids. For…

Numerical Analysis · Mathematics 2015-11-17 M. S. Litsarev , I. V. Oseledets

Efficient and stable algorithms for the calculation of spectral quantities and correlation functions are some of the key tools in computational condensed matter physics. In this article we review basic properties and recent developments of…

Other Condensed Matter · Physics 2007-05-23 Alexander Weisse , Gerhard Wellein , Andreas Alvermann , Holger Fehske

The Harrow, Hassidim, Lloyd (HHL) algorithm is a quantum algorithm expected to accelerate solving large-scale linear ordinary differential equations (ODEs). To apply the HHL to non-linear problems such as chemical reactions, the system must…

Numerical Analysis · Mathematics 2022-07-06 Takaki Akiba , Youhi Morii , Kaoru Maruta

We present four quantum algorithms for solving a multidimensional drift-diffusion equation. They rely on a quantum linear system solver, a quantum Hamiltonian simulation, a quantum random walk, and the quantum Fourier transform. We compare…

Quantum Physics · Physics 2025-10-16 Ellen Devereux , Animesh Datta

Quantum algorithms offer an exponential advantage with respect to the number of dependent variables for solving certain nonlinear ordinary differential equations (ODEs). These algorithms typically begin by transforming the original…

Quantum Physics · Physics 2025-12-09 Judd Katz , Gopikrishnan Muraleedharan , Abhijeet Alase

We explore the class of exponential integrators known as exponential time differencing (ETD) method in this letter to design low complexity nonlinear Fourier transform (NFT) algorithms that compute discrete approximations of the scattering…

Computational Physics · Physics 2019-08-27 Vishal Vaibhav

Following the celebrated quantum algorithm for solving linear equations (so-called HHL algorithm), Childs, Kothari and Somma [SIAM Journal on Computing, {\bf 46}: 1920, (2017)] provided an approach to solve a linear system of equations with…

Quantum Physics · Physics 2023-12-06 Nhat A. Nghiem , Tzu-Chieh Wei

Quantum computers are known for their potential to achieve up-to-exponential speedup compared to classical computers for certain problems. To exploit the advantages of quantum computers, we propose quantum algorithms for linear stochastic…

Quantum Physics · Physics 2025-06-26 Shi Jin , Nana Liu , Wei Wei

Exponential divided differences arise in numerical linear algebra, matrix-function evaluation, and quantum Monte Carlo simulations, where they serve as kernel weights for time evolution and observable estimation. Efficient and numerically…

Computational Physics · Physics 2025-12-30 Itay Hen

Non-Markovian dynamics is ubiquitous in both quantum and classical systems, but the numerical computation of the time-delay dynamics is demanding. In this work, we propose an efficient quantum algorithm for solving linear distributed delay…

Quantum Physics · Physics 2026-03-19 Wataru Setoyama , Keisuke Fujii

We present the Fast Chebyshev Transform (FCT), a fast, randomized algorithm to compute a Chebyshev approximation of functions in high-dimensions from the knowledge of the location of its nonzero Chebyshev coefficients. Rather than sampling…

Numerical Analysis · Mathematics 2023-10-03 Dalton Jones , Pierre-David Letourneau , Matthew J. Morse , M. Harper Langston