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In this paper, we propose a domain decomposition dynamical low-rank method to solve high-dimensional radiative transfer problems and similar kinetic equations. The algorithm uses a separate low-rank approximation on each spatial subdomain,…

Numerical Analysis · Mathematics 2026-02-17 Stefan Brunner , Lukas Einkemmer , Terry Haut

We propose an inexact low-rank source iteration with diffusion synthetic acceleration (SI-DSA) for solving the multidimensional steady-state radiative transfer equation (RTE) in the second-order formulation. The angular flux is represented…

Numerical Analysis · Mathematics 2025-09-03 Wei Guo , Zhichao Peng

The spectral bundle method proposed by Helmberg and Rendl is well established for solving large-scale semidefinite programs (SDP) thanks to its low per iteration computational complexity and strong practical performance. In this paper, we…

Optimization and Control · Mathematics 2022-11-08 Lijun Ding , Benjamin Grimmer

We present the two-dimensional unstructured grids extension of the a posteriori local subcell correction of discontinuous Galerkin (DG) schemes introduced in [52]. The technique is based on the reformulation of DG scheme as a finite volume…

Numerical Analysis · Mathematics 2022-12-23 François Vilar , Rémi Abgrall

In this paper, we show that the bundle method can be applied to solve semidefinite programming problems with a low rank solution without ever constructing a full matrix. To accomplish this, we use recent results from randomly sketching…

Optimization and Control · Mathematics 2021-02-02 Lijun Ding , Benjamin Grimmer

A rank-adaptive integrator for the approximate solution of high-order tensor differential equations by tree tensor networks is proposed and analyzed. In a recursion from the leaves to the root, the integrator updates bases and then evolves…

Numerical Analysis · Mathematics 2022-07-26 Gianluca Ceruti , Christian Lubich , Dominik Sulz

In this work, we consider two types of large-scale quadratic matrix equations: Continuous-time algebraic Riccati equations, which play a central role in optimal and robust control, and unilateral quadratic matrix equations, which arise from…

Numerical Analysis · Mathematics 2019-03-07 Daniel Kressner , Patrick Kürschner , Stefano Massei

We present a new line-based discontinuous Galerkin (DG) discretization scheme for first- and second-order systems of partial differential equations. The scheme is based on fully unstructured meshes of quadrilateral or hexahedral elements,…

Numerical Analysis · Mathematics 2015-06-04 Per-Olof Persson

Boolean quadratic optimization problems occur in a number of applications. Their mixed integer-continuous nature is challenging, since it is inherently NP-hard. For this motivation, semidefinite programming relaxations (SDR's) are proposed…

Optimization and Control · Mathematics 2020-03-20 V. Cerone , S. M. Fosson , D. Regruto

The high-order numerical solution of the non-linear shallow water equations (and of hyperbolic systems in general) is susceptible to unphysical Gibbs oscillations that form in the proximity of strong gradients. The solution to this problem…

Numerical Analysis · Mathematics 2016-07-18 Simone Marras , Michal A. Kopera , Emil M. Constantinescu , Jenny Suckale , Francis X. Giraldo

In this paper, we develop a Discontinuous Galerkin (DG) method for solving H(curl)-elliptic hemivariational inequalities. By selecting an appropriate numerical flux, we construct an Interior Penalty Discontinuous Galerkin (IPDG) scheme. A…

Numerical Analysis · Mathematics 2026-04-21 Xiajie Huang , Fei Wang , Weimin Han , Min Ling

Stellar convection poses two main gargantuan challenges for astrophysical fluid solvers: low-Mach number flows and minuscule perturbations over steeply stratified hydrostatic equilibria. Most methods exhibit excessive numerical diffusion…

Fluid Dynamics · Physics 2026-04-09 D. A. Velasco-Romero , R. Teyssier

Low-rank optimization has emerged as a promising direction in training large language models (LLMs) to improve running time and reduce the memory usage of adaptive optimizers by constraining learning to a lower-dimensional space. Prior work…

Machine Learning · Computer Science 2025-10-09 Ionut-Vlad Modoranu , Mher Safaryan , Erik Schultheis , Max Ryabinin , Artem Chumachenko , Dan Alistarh

We propose an efficient approach to semidefinite spectral clustering (SSC), which addresses the Frobenius normalization with the positive semidefinite (p.s.d.) constraint for spectral clustering. Compared with the original Frobenius norm…

Machine Learning · Computer Science 2014-02-25 Yan Yan , Chunhua Shen , Hanzi Wang

The main goal of this paper is to investigate the order reduction phenomenon that appears in the integral deferred correction (InDC) methods based on implicit-explicit (IMEX) Runge-Kutta (R-K) schemes when applied to a class of stiff…

Numerical Analysis · Mathematics 2017-01-18 S. Boscarino , J. Qiu , G. Russo

Sliding mode control (SMC) is a robust and computationally efficient solution for tracking control problems of highly nonlinear systems with a great deal of uncertainty. High frequency oscillations due to chattering phenomena and…

Optimization and Control · Mathematics 2017-06-08 Mohammad Reza Amini , Mahdi Shahbakhti , Selina Pan , J. Karl Hedrick

As supercomputers grow in hardware complexity, their susceptibility to faults increases and measures need to be taken to ensure the correctness of results. Some numerical algorithms have certain characteristics that allow them to recover…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-16 Thomas Saupe , Sebastian Götschel , Thibaut Lunet , Daniel Ruprecht , Robert Speck

Damped wave equations have been used in many real-world fields. In this paper, we study a low-rank solution of the strongly damped wave equation with the damping term, visco-elastic damping term and mass term. Firstly, a second-order finite…

Numerical Analysis · Mathematics 2023-10-10 Yong-Liang Zhao , Xian-Ming Gu

High order methods are often desired for the evolution of ordinary differential equations, in particular those arising from the semi-discretization of partial differential equations. In prior work in we investigated the interplay between…

Numerical Analysis · Mathematics 2019-12-10 Adi Ditkowski , Sigal Gottlieb , Zachary J. Grant

In this paper, we propose SubLoRA, a rank determination method for Low-Rank Adaptation (LoRA) based on submodular function maximization. In contrast to prior approaches, such as AdaLoRA, that rely on first-order (linearized) approximations…

Machine Learning · Computer Science 2025-07-03 Yihang Gao , Vincent Y. F. Tan