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The Black-Scholes (B-S) equation has been recently extended as a kind of tempered time-fractional B-S equations, which becomes an interesting mathematical model in option pricing. In this study, we provide a fast numerical method to…

Numerical Analysis · Mathematics 2023-07-21 Jinfeng Zhou , Xian-Ming Gu , Yong-Liang Zhao , Hu Li

We present the full approximation scheme constraint decomposition (FASCD) multilevel method for solving variational inequalities (VIs). FASCD is a common extension of both the full approximation scheme (FAS) multigrid technique for…

Numerical Analysis · Mathematics 2024-08-13 Ed Bueler , Patrick E. Farrell

This work presents the windowed space-time least-squares Petrov-Galerkin method (WST-LSPG) for model reduction of nonlinear parameterized dynamical systems. WST-LSPG is a generalization of the space-time least-squares Petrov-Galerkin method…

Numerical Analysis · Mathematics 2020-12-14 Yukiko S. Shimizu , Eric J. Parish

In this paper, a two-sided variable-coefficient space-fractional diffusion equation with fractional Neumann boundary condition is considered. To conquer the weak singularity caused by nonlocal space-fractional differential operators, a…

Numerical Analysis · Mathematics 2024-10-07 Meijie Kong , Hongfei Fu

This paper establishes and analyzes a second-order accurate numerical scheme for the nonlinear partial integrodifferential equation with a weakly singular kernel. In the time direction, we apply the Crank-Nicolson method for the time…

Numerical Analysis · Mathematics 2022-09-07 Wenlin Qiu , Xu Xiao , Kexin Li

This paper presents an efficient high-order sharp-interface method for solving the three-dimensional (3D) Poisson equation with Dirichlet boundary conditions on a nonuniform Cartesian grid with irregular domain boundaries. The new approach…

Computational Physics · Physics 2024-12-20 Shirzad Hosseinverdi , Hermann F. Fasel

The Projected Gradient Descent (PGD) algorithm is a widely used and efficient first-order method for solving constrained optimization problems due to its simplicity and scalability in large design spaces. Building on recent advancements in…

Optimization and Control · Mathematics 2025-06-18 Lucka Barbeau , Marc-Étienne Lamarche-Gagnon , Florin Ilinca

In this paper, a new family of implicit compact finite difference schemes for computation of unsteady convection-diffusion equation with variable convection coefficient is proposed. The schemes are fourth order accurate in space and second…

Mathematical Physics · Physics 2012-01-17 Shuvam Sen

In this paper, a non-uniform time-stepping convex-splitting numerical algorithm for solving the widely used time-fractional Cahn-Hilliard equation is introduced. The proposed numerical scheme employs the $L1^+$ formula for discretizing the…

Numerical Analysis · Mathematics 2020-06-04 Jun Zhang , Jia Zhao , JinRong Wang

In this work, we use the spectral Galerkin method to prove the existence of a pathwise unique mild solution of a fractional stochastic partial differential equation of Burgers type in a H\"older space. We get the temporal regularity and…

Analysis of PDEs · Mathematics 2017-12-29 Zineb Arab , Latifa Debbi

Inspired by the structure of spherical harmonics, we propose the truncated kernel stochastic gradient descent (T-kernel SGD) algorithm with a least-square loss function for spherical data fitting. T-kernel SGD introduces a novel…

Machine Learning · Computer Science 2025-07-17 Jinhui Bai , Lei Shi

The article focuses on error estimates as well as stability analysis of deep learning methods for stationary and non-stationary viscous Burgers equation in two and three dimensions. The local well-posedness of homogeneous boundary value…

Numerical Analysis · Mathematics 2025-08-19 Wasim Akram , Sagar Gautam , Deepanshu Verma , Manil T. Mohan

Modern dense Flash memory devices operate at very low error rates, which require powerful error correcting coding (ECC) techniques. An emerging class of graph-based ECC techniques that has broad applications is the class of…

Information Theory · Computer Science 2019-09-25 Ahmed Hareedy , Homa Esfahanizadeh , Lara Dolecek

For the two-layer shallow water equations, a high-order compact gas-kinetic scheme (GKS) on triangular mesh is proposed. The two-layer shallow water equations have complex source terms in comparison with the single layer equations. The main…

Numerical Analysis · Mathematics 2023-06-08 Fengxiang Zhao , Jianping Gan , Kun Xu

Many relevant problems in the area of systems and control, such as controller synthesis, observer design and model reduction, can be viewed as optimization problems involving dynamical systems: for instance, maximizing performance in the…

Optimization and Control · Mathematics 2023-11-15 Pascal Den Boef , Jos Maubach , Wil Schilders , Nathan van de Wouw

We apply logic-based Benders decomposition (LBBD) to two-stage stochastic planning and scheduling problems in which the second-stage is a scheduling task. We solve the master problem with mixed integer/linear programming and the subproblem…

Optimization and Control · Mathematics 2020-12-29 Ozgun Elci , J. N. Hooker

A low-dissipation numerical method for compressible gas-liquid two-phase flow with phase change on unstructured grids is proposed. The governing equations adopt the six-equation model. The non-conservative terms included in the volume…

Fluid Dynamics · Physics 2024-11-13 Hiro Wakimura , Takayuki Aoki , Feng Xiao

Calculating dynamical diffraction patterns for X-ray topography and similar x-ray scattering-imaging techniques require the numerical integration of the Takagi-Taupin equations. This is usually performed with a simple second order finite…

Computational Physics · Physics 2022-02-24 Mads Carlsen , Hugh Simons

In this paper, we develop an EXCMG method to solve the three-dimensional Poisson equation on rectangular domains by using the compact finite difference (FD) method with unequal meshsizes in different coordinate directions. The resulting…

Numerical Analysis · Mathematics 2016-09-04 Kejia Pan , Dongdong He , Hongling Hu

Stochastic Gradient Descent (SGD) is a known stochastic iterative method popular for large-scale convex optimization problems due to its simple implementation and scalability. Some objectives, such as those found in complex-valued neural…

Machine Learning · Computer Science 2026-05-26 Natanael Alpay , Emeric Battaglia