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Strong approximation errors of both finite element semi-discretization and spatio-temporal full discretization are analyzed for the stochastic Allen-Cahn equation driven by additive noise in space dimension $d \leq 3$. The full…

Numerical Analysis · Mathematics 2020-08-04 Ruisheng Qi , Xiaojie Wang

In this paper, we introduce and analyze a lowest-order locking-free weak Galerkin (WG) finite element scheme for the grad-div formulation of linear elasticity problems. The scheme uses linear functions in the interior of mesh elements and…

Numerical Analysis · Mathematics 2023-09-12 Fuchang Huo , Ruishu Wang , Yanqiu Wang , Ran Zhang

In this work, we introduce a generalization of the enriched Galerkin (EG) method. The key feature of our scheme is an adaptive two-mesh approach that, in addition to the standard enrichment of a conforming finite element discretization via…

Numerical Analysis · Mathematics 2020-06-17 Andreas Rupp , Moritz Hauck , Vadym Aizinger

This paper presents a primal-dual weak Galerkin (PD-WG) finite element method for a class of second order elliptic equations of Fokker-Planck type. The method is based on a variational form where all the derivatives are applied to the test…

Numerical Analysis · Mathematics 2017-04-20 Chunmei Wang , Junping Wang

A reduced model for large deformations of prestrained plates consists of minimizing a second order bending energy subject to a nonconvex metric constraint. The former involves the second fundamental form of the middle plate and the later is…

Numerical Analysis · Mathematics 2020-11-03 Andrea Bonito , Diane Guignard , Ricardo H. Nochetto , Shuo Yang

In this work, we introduce a quadratically convergent and dynamically consistent integrator specifically designed for the replicator dynamics. The proposed scheme combines a two-stage rational approximation with a normalization step to…

Numerical Analysis · Mathematics 2025-11-03 Mario Pezzella

In recent times, a variety of Reinforcement Learning (RL) algorithms have been proposed for optimal tracking problem of continuous time nonlinear systems with input constraints. Most of these algorithms are based on the notion of uniform…

Systems and Control · Electrical Eng. & Systems 2020-06-16 Amardeep Mishra , Satadal Ghosh

We analyze a family of Runge-Kutta based quadrature algorithms for the approximation of the gramians of linear time invariant dynamical systems. The approximated gramians are used to obtain an approximate balancing transformation similar to…

Numerical Analysis · Mathematics 2020-03-09 Christian Bertram , Heike Faßbender

In this work we present an a priori error analysis for solving the unsteady advection equation on cut cell meshes along a straight ramp in two dimensions. The space discretization uses a lowest order upwind-type discontinuous Galerkin…

Numerical Analysis · Mathematics 2024-11-18 Gunnar Birke , Christian Engwer , Jan Giesselmann , Sandra May

This work focuses on the development of a new class of high-order accurate methods for multirate time integration of systems of ordinary differential equations. The proposed methods are based on a specific subset of explicit one-step…

Numerical Analysis · Mathematics 2019-04-16 Vu Thai Luan , Rujeko Chinomona , Daniel R. Reynolds

In this paper, we present a predictor-corrector strategy for constructing rank-adaptive dynamical low-rank approximations (DLRAs) of matrix-valued ODE systems. The strategy is a compromise between (i) low-rank step-truncation approaches…

Numerical Analysis · Mathematics 2022-09-09 Cory Hauck , Stefan Schnake

Policy gradient methods are a powerful family of reinforcement learning algorithms for continuous control that optimize a policy directly. However, standard first-order methods often converge slowly. Second-order methods can accelerate…

Systems and Control · Electrical Eng. & Systems 2025-11-05 Amirreza Valaei , Arash Bahari Kordabad , Sadegh Soudjani

In this paper, a two-grid temporal second-order scheme for the two-dimensional nonlinear Volterra integro-differential equation with weakly singular kernel is proposed to reduce the computation time and improve the accuracy of the scheme…

Numerical Analysis · Mathematics 2022-09-02 Hao Chen , Mahmoud A. Zaky , Ahmed S. Hendy , Wenlin Qiu

The novel idea of weak Galerkin (WG) finite element methods is on the use of weak functions and their weak derivatives defined as distributions. Weak functions and weak derivatives can be approximated by polynomials with various degrees.…

Numerical Analysis · Mathematics 2013-04-25 Lin Mu , Junping Wang , Xiu Ye

We present an arbitrary order discontinuous Galerkin finite element method for solving the fourth-order curl problem using a reconstructed discontinuous approximation method. It is based on an arbitrarily high-order approximation space with…

Numerical Analysis · Mathematics 2024-06-11 Ruo Li , Qicheng Liu , Shuhai Zhao

Optimization in machine learning, both theoretical and applied, is presently dominated by first-order gradient methods such as stochastic gradient descent. Second-order optimization methods, that involve second derivatives and/or second…

Machine Learning · Computer Science 2021-03-08 Rohan Anil , Vineet Gupta , Tomer Koren , Kevin Regan , Yoram Singer

In this work, the authors introduce a generalized weak Galerkin (gWG) finite element method for the time-dependent Oseen equation. The generalized weak Galerkin method is based on a new framework for approximating the gradient operator.…

Numerical Analysis · Mathematics 2022-09-14 Wenya Qi , Padmanabhan Seshaiyer , Junping Wang

This paper presents a rank-adaptive implicit-explicit integrator for the tensor approximation of three-dimensional convection-diffusion equations. In particular, the recently developed Reduced Augmentation Implicit Low-rank (RAIL)…

Numerical Analysis · Mathematics 2025-08-25 Joseph Nakao , Gianluca Ceruti , Lukas Einkemmer

This paper introduces an efficient stabilizer-free weak Galerkin (WG) finite element method for solving the three-dimensional quad-curl problem. Leveraging bubble functions as a key analytical tool, the method extends the applicability of…

Numerical Analysis · Mathematics 2025-02-13 Chunmei Wang , Shangyou Zhang

In this work, the Parareal algorithm is applied to evolution problems that admit good low-rank approximations and for which the dynamical low-rank approximation (DLRA) can be used as time stepper. Many discrete integrators for DLRA have…

Numerical Analysis · Mathematics 2022-09-14 Benjamin Carrel , Martin J. Gander , Bart Vandereycken