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Tau leaping is a popular method for performing fast approximate simulation of certain continuous time Markov chain models typically found in chemistry and biochemistry. This method is known to perform well when the transition rates satisfy…

Probability · Mathematics 2025-12-09 Ross McVinish , Liam Hodgkinson

In this work, we aim at constructing numerical schemes, that are as efficient as possible in terms of cost and conservation of invariants, for the Vlasov--Fokker--Planck system coupled with Poisson or Amp\`ere equation. Splitting methods…

Numerical Analysis · Mathematics 2023-06-13 Ibrahim Almuslimani , Nicolas Crouseilles

For the approximation of solutions for It\^o and Stratonovich stochastic differential equations (SDEs)a new class of efficient stochastic Runge-Kutta (SRK) methods is developed. As the main novelty only two stages are necessary for the…

Numerical Analysis · Mathematics 2025-07-01 Andreas Rößler

In this paper, we develop a higher order symmetric partitioned Runge-Kutta method for a coupled system of differential equations on Lie groups. We start with a discussion on partitioned Runge-Kutta methods on Lie groups of arbitrary order.…

High Energy Physics - Lattice · Physics 2011-09-15 Michèle Wandelt , Michael Günther , Francesco Knechtli , Michael Striebel

We present a novel multiscale simulation approach for modeling stochasticity in chemical reaction networks. The approach seamlessly integrates exact-stochastic and "leaping" methodologies into a single "partitioned leaping" algorithmic…

Chemical Physics · Physics 2009-11-11 Leonard A. Harris , Paulette Clancy

High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic PDEs. These methods can advantageously be coupled with high order strong stability preserving time discretizations. The…

Numerical Analysis · Mathematics 2014-03-27 Sigal Gottlieb , Zachary J. Grant , Daniel Higgs

An optimal control for a dynamical system optimizes a certain objective function. Here we consider the construction of an optimal control for a stochastic dynamical system with a random structure, Poisson perturbations and random jumps,…

Optimization and Control · Mathematics 2023-01-24 Taras Lukashiv , Yuliia Litvinchuk , Igor Malyk , Anna Golebiewska , Petr V. Nazarov

Many HPC applications that solve differential equations rely on the Runge-Kutta family of methods for time integration. Among these methods, the fourth-order accurate RK4 scheme is especially popular. This time integration scheme requires…

General Relativity and Quantum Cosmology · Physics 2026-03-09 Lucas Timotheo Sanches , Steven Robert Brandt , Jay Kalinani , Liwei Ji , Erik Schnetter

Explicit stabilized methods are an efficient alternative to implicit schemes for the time integration of stiff systems of differential equations in large dimension. In this paper, we derive explicit stabilized integrators of orders one and…

Numerical Analysis · Mathematics 2023-06-09 Ibrahim Almuslimani , Gilles Vilmart

We investigate the strong stability preserving (SSP) property of two-step Runge-Kutta (TSRK) methods. We prove that all SSP TSRK methods belong to a particularly simple subclass of TSRK methods, in which stages from the previous step are…

Numerical Analysis · Mathematics 2012-01-13 David I. Ketcheson , Sigal Gottlieb , Colin B. Macdonald

Tau-leaping is a popular discretization method for generating approximate paths of continuous time, discrete space, Markov chains, notably for biochemical reaction systems. To compute expected values in this context, an appropriate…

Numerical Analysis · Mathematics 2014-08-04 David F. Anderson , Desmond J. Higham , Yu Sun

This work considers multirate generalized-structure additively partitioned Runge-Kutta (MrGARK) methods for solving stiff systems of ordinary differential equations (ODEs) with multiple time scales. These methods treat different partitions…

Numerical Analysis · Mathematics 2022-01-19 Steven Roberts , John Loffeld , Arash Sarshar , Carol S. Woodward , Adrian Sandu

Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms to estimate system…

Quantitative Methods · Quantitative Biology 2016-05-20 Christopher Lester , Christian A. Yates , Michael B. Giles , Ruth E. Baker

Motivated by studies on fully discrete numerical schemes for linear hyperbolic conservation laws, we present a framework on analyzing the strong stability of explicit Runge-Kutta (RK) time discretizations for semi-negative autonomous linear…

Numerical Analysis · Mathematics 2018-11-28 Zheng Sun , Chi-Wang Shu

The problem of solving stochastic differential-algebraic equations (SDAEs) of index one with a scalar driving Brownian motion is considered. Recently, the authors proposed a class of stiffly accurate stochastic Runge-Kutta (SRK) methods…

Numerical Analysis · Mathematics 2013-11-07 Dominique Küpper , Anne Kværnø , Andreas Rößler

High order strong stability preserving (SSP) time discretizations are advantageous for use with spatial discretizations with nonlinear stability properties for the solution of hyperbolic PDEs. The search for high order strong stability…

Numerical Analysis · Mathematics 2016-03-24 Andrew J. Christieb , Sigal Gottlieb , Zachary J. Grant , David C. Seal

In this paper, we present a novel explicit second order scheme with one step for solving the forward backward stochastic differential equations, with the Crank-Nicolson method as a specific instance within our proposed framework. We first…

Numerical Analysis · Mathematics 2025-11-25 Qiang Han , Shihao Lan , Quanxin Zhu

A recently developed high-order implicit shock tracking (HOIST) framework for resolving discontinuous solutions of inviscid, steady conservation laws [41, 43] is extended to the unsteady case. Central to the framework is an optimization…

Numerical Analysis · Mathematics 2022-01-26 Andrew Shi , Per-Olof Persson , Matthew Zahr

A time discretization method is called strongly stable, if the norm of its numerical solution is nonincreasing. It is known that, even for linear semi-negative problems, many explicit Runge--Kutta (RK) methods fail to preserve this…

Numerical Analysis · Mathematics 2019-12-30 Zheng Sun , Chi-Wang Shu

Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via…

Quantitative Methods · Quantitative Biology 2016-04-19 Daniel Wilson , Ruth E. Baker