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This work presents algorithms for the efficient implementation of discontinuous Galerkin methods with explicit time stepping for acoustic wave propagation on unstructured meshes of quadrilaterals or hexahedra. A crucial step towards…

Numerical Analysis · Computer Science 2019-03-06 Svenja Schoeder , Katharina Kormann , Wolfgang Wall , Martin Kronbichler

While symplectic integration methods based on operator splitting are well established in many branches of science, high order methods for Hamiltonian systems that split in more than two parts have not been studied in great detail. Here, we…

Computational Physics · Physics 2015-06-15 Ch. Skokos , E. Gerlach , J. D. Bodyfelt , G. Papamikos , S. Eggl

We consider the numerical integration of non-autonomous separable parabolic equations using high order splitting methods with complex coefficients (methods with real coefficients of order greater than two necessarily have negative…

Numerical Analysis · Mathematics 2014-05-20 Muaz Seydaoğlu , Sergio Blanes

Temporal difference (TD) methods constitute a class of methods for learning predictions in multi-step prediction problems, parameterized by a recency factor lambda. Currently the most important application of these methods is to temporal…

Artificial Intelligence · Computer Science 2008-02-03 P. Cichosz

When dealing with stiff conservation laws, explicit time integration forces to employ very small time steps, due to the restrictive CFL stability condition. Implicit methods offer an alternative, yielding the possibility to choose the time…

Numerical Analysis · Mathematics 2026-03-26 Alessandra Zappa , Matteo Semplice

Fully implicit timestepping methods have several potential advantages for atmosphere/ocean simulation. First, being unconditionally stable, they degrade more gracefully as the Courant number increases, typically requiring more solver…

Numerical Analysis · Mathematics 2025-10-16 Werner Bauer , Colin J. Cotter

This paper introduces a new robust interior point method analysis for semidefinite programming (SDP). This new robust analysis can be combined with either logarithmic barrier or hybrid barrier. Under this new framework, we can improve the…

Optimization and Control · Mathematics 2021-11-22 Baihe Huang , Shunhua Jiang , Zhao Song , Runzhou Tao , Ruizhe Zhang

Many estimators of dynamic discrete choice models with persistent unobserved heterogeneity have desirable statistical properties but are computationally intensive. In this paper we propose a method to quicken estimation for a broad class of…

Econometrics · Economics 2025-04-09 Jackson Bunting , Takuya Ura

Recent applications (e.g. active gels and self-assembly of elastic sheets) motivate the need to efficiently simulate the dynamics of thin elastic sheets. We present semi-implicit time stepping algorithms to improve the time step constraints…

Computational Physics · Physics 2019-10-23 Silas Alben , Alex A. Gorodetsky , Donghak Kim , Robert D. Deegan

The choice of numerical integrator in approximating solutions to dynamic partial differential equations depends on the smallest time-scale of the problem at hand. Large-scale deformations in elastic solids contain both shear waves and bulk…

Numerical Analysis · Mathematics 2025-02-21 Edward M. Terrell , Boyce E. Griffith

Automatic differentiation (autodiff) has revolutionized machine learning. It allows to express complex computations by composing elementary ones in creative ways and removes the burden of computing their derivatives by hand. More recently,…

In previous papers, explicit symplectic integrators were designed for nonrotating black holes, such as a Schwarzschild black hole. However, they fail to work in the Kerr spacetime because not all variables can be separable, or not all…

General Relativity and Quantum Cosmology · Physics 2021-06-24 Xin Wu , Ying Wang , Wei Sun , Fuyao Liu

We present an algorithm for the rapid numerical integration of smooth, time-periodic differential equations with small nonlinearity, particularly suited to problems with small dissipation. The emphasis is on speed without compromising…

Numerical Analysis · Mathematics 2015-06-23 Michele V. Bartuccelli , Jonathan H. B. Deane , Guido Gentile

Splitting methods are widely used for solving initial value problems (IVPs) due to their ability to simplify complicated evolutions into more manageable subproblems which can be solved efficiently and accurately. Traditionally, these…

Numerical Analysis · Mathematics 2024-11-15 L. M. Kreusser , H. E. Lockyer , E. H. Müller , P. Singh

The aim of this work is to design implicit and semi-implicit high-order well-balanced finite-volume numerical methods for 1D systems of balance laws. The strategy introduced by two of the authors in a previous paper for explicit schemes…

Numerical Analysis · Mathematics 2022-08-31 Irene Gómez-Bueno , Sebastiano Boscarino , Manuel Jesús Castro , Carlos Parés , Giovanni Russo

We present and analyze a new iterative solver for implicit discretizations of a simplified Boltzmann-Poisson system. The algorithm builds on recent work that incorporated a sweeping algorithm for the Vlasov-Poisson equations as part of…

Numerical Analysis · Mathematics 2020-09-15 Victor P. DeCaria , Cory D. Hauck , M. Paul Laiu

Computational chemical combustion problems are known to be stiff, and are typically solved with implicit time integration methods. A novel exponential time integrator, EPI3V, is introduced and applied to a spatially homogeneous isobaric…

Numerical Analysis · Mathematics 2023-07-04 Jared Stewart , Mayya Tokman , Fabrizio Bisetti , Valentin Dallerit , Oscar Diaz-Ibarra

Accurately simulating long-time dynamics of many-body systems is a challenge in both classical and quantum computing due to the accumulation of Trotter errors. While low-order Trotter-Suzuki decompositions are straightforward to implement,…

Quantum Physics · Physics 2026-01-27 Marko Maležič , Johann Ostmeyer

This paper investigates connections between discrete and continuous approaches for decomposable submodular function minimization. We provide improved running time estimates for the state-of-the-art continuous algorithms for the problem…

Machine Learning · Computer Science 2017-03-07 Alina Ene , Huy L. Nguyen , László A. Végh

This paper is concerned with the adaptive numerical treatment of stochastic partial differential equations. Our method of choice is Rothe's method. We use the implicit Euler scheme for the time discretization. Consequently, in each step, an…

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