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Stochastic reaction networks governed by Chemical Langevin Equations (CLE) exhibit pronounced multiscale dynamics spanning fast molecular reactions, intermediate transport, and slow cellular regulation, posing significant challenges for…

Numerical Analysis · Mathematics 2026-04-02 Yuming Zeng , Wei Xie , Keqi Wang

Many applications involve partial differential equations which admits nontrivial steady state solutions. The design of schemes which are able to describe correctly these equilibrium states may be challenging for numerical methods, in…

Analysis of PDEs · Mathematics 2016-02-09 Lorenzo Pareschi , Thomas Rey

An adaptive finite difference scheme for variable-order fractional-time subdiffusion equations in the Caputo form is studied. The fractional time derivative is discretized by the L1 procedure but using nonhomogeneous timesteps. The size of…

Numerical Analysis · Mathematics 2024-09-20 Joaquín Quintana-Murillo , Santos Bravo Yuste

We present in this paper algorithms for solving stiff PDEs on the unit sphere with spectral accuracy in space and fourth-order accuracy in time. These are based on a variant of the double Fourier sphere method in coefficient space with…

Numerical Analysis · Mathematics 2017-12-27 Hadrien Montanelli , Yuji Nakatsukasa

In this paper, we develop a second-order accurate time-stepping scheme for the tempered time-fractional advection-dispersion equation based on a sum-of-exponentials (SOE) approximation to the convolution kernel involved in the fractional…

Numerical Analysis · Mathematics 2026-02-10 Liangcai Huang , Lin Li , Shujuan Lü

Splitting methods constitute a well-established class of numerical schemes for solving convection-diffusion-reaction problems. They have been shown to be effective in solving problems with periodic boundary conditions. However, in the case…

Numerical Analysis · Mathematics 2025-02-14 Thi Tam Dang , Lukas Einkemmer , Alexander Ostermann

The efficiency of exact simulation methods for the reaction-diffusion master equation (RDME) is severely limited by the large number of diffusion events if the mesh is fine or if diffusion constants are large. Furthermore, inherent…

Numerical Analysis · Computer Science 2015-06-15 Andreas Hellander , Michael Lawson , Brian Drawert , Linda Petzold

We develop adaptive time-stepping strategies for It\^o-type stochastic differential equations (SDEs) with jump perturbations. Our approach builds on adaptive strategies for SDEs. Adaptive methods can ensure strong convergence of nonlinear…

Numerical Analysis · Mathematics 2024-01-17 Cónall Kelly , Gabriel Lord , Fandi Sun

Multiscale and multiphysics problems need novel numerical methods in order for them to be solved correctly and predictively. To that end, we develop a wavelet based technique to solve a coupled system of nonlinear partial differential…

Numerical Analysis · Mathematics 2023-03-22 Cale Harnish , Luke Dalessandro , Karel Matous , Daniel Livescu

We propose a variational splitting technique for the generalized-$\alpha$ method to solve hyperbolic partial differential equations. We use tensor-product meshes to develop the splitting method, which has a computational cost that grows…

Numerical Analysis · Mathematics 2019-11-12 Pouria Behnoudfar , Quanling Deng , Victor M. Calo

This paper deals with the application of probabilistic time integration methods to semi-explicit partial differential-algebraic equations of parabolic type and its semi-discrete counterparts, namely semi-explicit differential-algebraic…

Numerical Analysis · Mathematics 2024-12-02 R. Altmann , A. Moradi

In this research work, we propose a high-order time adapted scheme for pricing a coupled system of fixed-free boundary constant elasticity of variance (CEV) model on both equidistant and locally refined space-grid. The performance of our…

Computational Finance · Quantitative Finance 2023-09-12 Chinonso Nwankwo , Weizhong Dai , Tony Ware

In this paper, we propose a new adaptive technique, named adaptive trajectories sampling (ATS), which is used to select training points for the numerical solution of partial differential equations (PDEs) with deep learning methods. The key…

Numerical Analysis · Mathematics 2023-03-29 Xingyu Chen , Jianhuan Cen , Qingsong Zou

This paper explores adaptive variance reduction methods for stochastic optimization based on the STORM technique. Existing adaptive extensions of STORM rely on strong assumptions like bounded gradients and bounded function values, or suffer…

Optimization and Control · Mathematics 2024-10-24 Wei Jiang , Sifan Yang , Yibo Wang , Lijun Zhang

New implicit and implicit-explicit time-stepping methods for the wave equation in second-order form are described with application to two and three-dimensional problems discretized on overset grids. The implicit schemes are single step,…

Numerical Analysis · Mathematics 2024-04-24 Allison M. Carson , Jeffrey W. Banks , William D. Henshaw , Donald W. Schwendeman

Synchronizations of processing elements (PEs) in massively parallel simulations, which arise due to communication or load imbalances between PEs, significantly affect the scalability of scientific applications. We have recently proposed a…

Computational Physics · Physics 2018-08-16 Konduri Aditya , Diego A. Donzis

This paper investigates the use of stratified sampling as a variance reduction technique for approximating integrals over large dimensional spaces. The accuracy of this method critically depends on the choice of the space partition, the…

Probability · Mathematics 2009-09-15 Pierre Etoré , Gersende Fort , Benjamin Jourdain , Eric Moulines

We study solution techniques for an evolution equation involving second order derivative in time and the spectral fractional powers, of order $s \in (0,1)$, of symmetric, coercive, linear, elliptic, second-order operators in bounded domains…

Numerical Analysis · Mathematics 2018-06-18 Lehel Banjai , Enrique Otarola

Learning the evolutionary dynamics of Partial Differential Equations (PDEs) is critical in understanding dynamic systems, yet current methods insufficiently learn their representations. This is largely due to the multi-scale nature of the…

Machine Learning · Computer Science 2024-10-16 Aoming Liang , Zhaoyang Mu , Pengxiao Lin , Cong Wang , Mingming Ge , Ling Shao , Dixia Fan , Hao Tang

Time-fractional parabolic equations with a Caputo time derivative of order $\alpha\in(0,1)$ are discretised in time using collocation methods, which assume that the Caputo derivative of the computed solution is piecewise-polynomial. For…

Numerical Analysis · Mathematics 2026-02-23 Sebastian Franz , Natalia Kopteva
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