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Dissipation and irreversibility are central to most physical processes, yet they lead to non-unitary dynamics that are challenging to realise on quantum processors. High-order operator splitting is an attractive approach for simulating…

Quantum Physics · Physics 2026-02-17 Peter Brearley , Philipp Pfeffer

We discuss systematic extensions of the standard (St{\"o}rmer-Verlet) splitting method for differential equations of Hamiltonian mechanics, with relative accuracy of order $\tau^2$ for a timestep of length $\tau$, to higher orders in…

Numerical Analysis · Mathematics 2013-10-09 Asif Mushtaq , Anne Kværnø , Kåre Olaussen

One of the most fascinating phenomena observed in reaction-diffusion systems is the emergence of segregated solutions, i.e. population densities with disjoint supports. We analyse such a reaction cross-diffusion system. In order to prove…

Analysis of PDEs · Mathematics 2017-11-16 José A. Carrillo , Simone Fagioli , Filippo Santambrogio , Markus Schmidtchen

It is demonstrated is this letter that linear multistep methods for integrating ordinary differential equations can be used to develop a family of fast forward scattering algorithms with higher orders of convergence. Excluding the cost of…

Computational Physics · Physics 2018-03-28 Vishal Vaibhav

In this paper, we present a class of high-order and efficient compact difference schemes for nonlinear convection diffusion equations, which can preserve both bounds and mass. For the one-dimensional problem, we first introduce a high-order…

Numerical Analysis · Mathematics 2025-03-20 Baolin Kuang , Shusen Xie , Hongfei Fu

Diffusion-based inverse algorithms have shown remarkable performance across various inverse problems, yet their reliance on numerous denoising steps incurs high computational costs. While recent developments of fast diffusion ODE solvers…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Jiawei Zhang , Ziyuan Liu , Leon Yan , Gen Li , Yuantao Gu

We describe an exact and highly efficient numerical algorithm for solving a special but important class of convection-diffusion equations. These equations occur in many problems in physics, chemistry, or biology, and they are usually hard…

Computational Physics · Physics 2019-03-27 Narain Karedla , Jan Christoph Thiele , Ingo Gregor , Jörg Enderlein

We describe an algorithm for the numerical solution of second order linear differential equations in the highly-oscillatory regime. It is founded on the recent observation that the solutions of equations of this type can be accurately…

Numerical Analysis · Mathematics 2015-06-23 James Bremer

We consider the Vlasov-Poisson equation in a Hamiltonian framework and derive new time splitting methods based on the decomposition of the Hamiltonian functional between the kinetic and electric energy. Assuming smoothness of the solutions,…

Numerical Analysis · Mathematics 2015-10-08 Fernando Casas , Nicolas Crouseilles , Erwan Faou , Michel Mehrenberger

Strang splitting is a widely used second-order method for solving diffusion-reaction problems. However, its convergence order is often reduced to order $1$ for Dirichlet boundary conditions and to order $1.5$ for Neumann and Robin boundary…

Numerical Analysis · Mathematics 2025-11-12 Thi Tam Dang , Lukas Einkemmer , Alexander Ostermann

The accurate numerical simulation of high Reynolds number incompressible flows is a challenging topic in computational fluid dynamics. Classical inf-sup stable methods like the Taylor-Hood element or only $L^2$-conforming discontinuous…

Numerical Analysis · Mathematics 2019-12-24 Marian Piatkowski , Peter Bastian

We explore the utilization of higher-order discretization techniques in optimizing the gate count needed for quantum computer based solutions of partial differential equations. To accomplish this, we present an efficient approach for…

Quantum Physics · Physics 2024-12-30 Boris Arseniev , Dmitry Guskov , Richik Sengupta , Igor Zacharov

We present a number of new contributions to the topic of constructing efficient higher-order splitting methods for the numerical integration of evolution equations. Particular schemes are constructed via setup and solution of polynomial…

Numerical Analysis · Mathematics 2016-04-06 Winfried Auzinger , Harald Hofstätter , David Ketcheson , Othmar Koch

Splitting methods constitute a widely used class of numerical integrators for ordinary and partial differential equations, particularly well suited to problems that can be decomposed into simpler subproblems. High-order splitting schemes…

Numerical Analysis · Mathematics 2026-04-02 Fernando Casas , Ander Murua

Recent diffusion models provide a promising zero-shot solution to noisy linear inverse problems without retraining for specific inverse problems. In this paper, we reveal that recent methods can be uniformly interpreted as employing a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Xinyu Peng , Ziyang Zheng , Wenrui Dai , Nuoqian Xiao , Chenglin Li , Junni Zou , Hongkai Xiong

These lectures introduce the method of nonlinear steepest descent for Riemann-Hilbert problems. This method finds use in studying asymptotics associated to a variety of special functions such as the Painlev\'{e} equations and orthogonal…

Mathematical Physics · Physics 2019-03-21 Percy Deift

A technique is described in this paper to avoid order reduction when integrating reaction-diffusion initial boundary value problems with explicit exponential Rosenbrock methods. The technique is valid for any Rosenbrock method, without…

Numerical Analysis · Mathematics 2023-07-25 Begoña Cano , María Jesús Moreta

We present directional operator splitting schemes for the numerical solution of a fourth-order, nonlinear partial differential evolution equation which arises in image processing. This equation constitutes the $H^{-1}$-gradient flow of the…

Numerical Analysis · Mathematics 2015-09-04 Luca Calatroni , Bertram Düring , Carola-Bibiane Schönlieb

We present the first framework to solve linear inverse problems leveraging pre-trained latent diffusion models. Previously proposed algorithms (such as DPS and DDRM) only apply to pixel-space diffusion models. We theoretically analyze our…

Machine Learning · Computer Science 2023-07-04 Litu Rout , Negin Raoof , Giannis Daras , Constantine Caramanis , Alexandros G. Dimakis , Sanjay Shakkottai

Linearly implicit Runge-Kutta methods with approximate matrix factorization can solve efficiently large systems of differential equations that have a stiff linear part, e.g. reaction-diffusion systems. However, the use of approximate…

Numerical Analysis · Computer Science 2014-08-19 Hong Zhang , Adrian Sandu , Paul Tranquilli
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