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Related papers: RAM: Rapid Advection Algorithm on Arbitrary Meshes

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In this paper, we propose a new stochastic alternating direction method of multipliers (ADMM) algorithm, which incrementally approximates the full gradient in the linearized ADMM formulation. Besides having a low per-iteration complexity as…

Machine Learning · Computer Science 2013-08-19 Leon Wenliang Zhong , James T. Kwok

Orbital advection is a significant bottleneck in disk simulations, and a particularly tricky one when used in connection with magnetohydrodynamics. We have developed an orbital advection algorithm suitable for the induction equation with…

Earth and Planetary Astrophysics · Physics 2017-09-27 Wladimir Lyra , Colin P. McNally , Tobias Heinemann , Frederic Masset

We present a new approach to Eulerian computational fluid dynamics that is designed to work at high Mach numbers encountered in astrophysical hydrodynamic simulations. The Eulerian fluid conservation equations are solved in an adaptive…

Astrophysics · Physics 2009-11-10 Hy Trac , Ue-Li Pen

The relativistic hydrodynamics (RHD) equations can give rise to solutions which have shocks, contact discontinuities, and other sharp structures, which interact and evolve over time. Capturing these sharp waves effectively requires a mesh…

Numerical Analysis · Mathematics 2026-04-23 Sujoy Basak , Arpit Babbar , Harish Kumar , Praveen Chandrashekar

Accretion disks are three-dimensional, turbulent, often self-gravitating, magnetohydrodynamic flows, which can be modeled in detail with numerical simulations. In this paper, we present a new algorithm that is based on a spectral…

Astrophysics · Physics 2009-07-22 Chi-kwan Chan , Dimitrios Psaltis , Feryal Ozel

Implicit time-stepping for advection is applied locally in space and time where Courant numbers are large, but standard explicit time-stepping is used for the remaining solution which is typically the majority. This adaptively implicit…

Fluid Dynamics · Physics 2024-06-14 Hilary Weller , Christian Kuehnlein , Piotr K. Smolarkiewicz

The vast majority of reduced-order models (ROMs) first obtain a low dimensional representation of the problem from high-dimensional model (HDM) training data which is afterwards used to obtain a system of reduced complexity. Unfortunately,…

Numerical Analysis · Mathematics 2023-09-14 Victor Zucatti , Matthew J. Zahr

In recent years, considerable attention has been devoted to the regularization models due to the presence of high-dimensional data in scientific research. Sparse support vector machine (SVM) are useful tools in high-dimensional data…

Computation · Statistics 2023-12-27 Jiawei Wen

In this paper, we present new stochastic methods for solving two important classes of nonconvex optimization problems. We first introduce a randomized accelerated proximal gradient (RapGrad) method for solving a class of nonconvex…

Optimization and Control · Mathematics 2019-08-20 Guanghui Lan , Yu Yang

Cartesian-grid methods with Adaptive Mesh Refinement (AMR) are ideally suited for simulating the breaking of waves, the formation of spray, and the entrainment of air around ships. As a result of the cartesian-grid formulation, minimal…

Explicit numerical computations of super-fast differentially rotating disks are subject to the time-step constraint imposed by the Courant condition. When the bulk orbital velocity largely exceeds any other wave speed the time step is…

Instrumentation and Methods for Astrophysics · Physics 2015-06-05 A. Mignone , M. Flock , M. Stute , S. M. Kolb , G. Muscianisi

An algorithm to estimate motion from satellite imagery is presented. Dense displacement fields are computed from time-separated images of of significant convective activity using a Bayesian formulation of the motion estimation problem.…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Sai Ravela , Virat Chatdarong

The Alternating Direction Method of Multipliers (ADMM) has gained a lot of attention for solving large-scale and objective-separable constrained optimization. However, the two-block variable structure of the ADMM still limits the practical…

Optimization and Control · Mathematics 2020-03-24 Kresimir Mihic , Mingxi Zhu , Yinyu Ye

Network management protocols often require timely and meaningful insight about per flow network traffic. This paper introduces Randomized Admission Policy (RAP) - a novel algorithm for the frequency and top-k estimation problems, which are…

Data Structures and Algorithms · Computer Science 2016-12-12 Ran Ben Basat , Gil Einziger , Roy Friedman , Yaron Kassner

The Alternating Direction Method of Multipliers (ADMM) has now days gained tremendous attentions for solving large-scale machine learning and signal processing problems due to the relative simplicity. However, the two-block structure of the…

Optimization and Control · Mathematics 2020-03-23 Mingxi Zhu , Kresimir Mihic , Yinyu Ye

Multi-group multicast beamforming in wireless systems with large antenna arrays and massive audience is investigated in this paper. Multicast beamforming design is a well-known non-convex quadratically constrained quadratic programming…

Information Theory · Computer Science 2017-03-07 Erkai Chen , Meixia Tao

High-resolution simulations often rely on the Adaptive Mesh Resolution (AMR) technique to optimize memory consumption versus attainable precision. While this technique allows for dramatic improvements in terms of computing performance, the…

Data Structures and Algorithms · Computer Science 2013-01-03 Marc Labadens , Daniel Pomarède , Damien Chapon , Romain Teyssier , Frédéric Bournaud , Florent Renaud , Nicolas Grandjouan

A new parallelized unsplit geometrical Volume of Fluid (VoF) algorithm with support for arbitrary unstructured meshes and dynamic local Adaptive Mesh Refinement (AMR), as well as for two and three dimensional computation is developed. The…

Fluid Dynamics · Physics 2013-05-16 Tomislav Maric , Holger Marschall , Dieter Bothe

High order algorithms have emerged in numerical astrophysics as a promising avenue to reduce truncation error (proportional to a power of the linear resolution $\Delta x$) with only a moderate increase to computational expense. Significant…

Instrumentation and Methods for Astrophysics · Physics 2025-02-27 Tomoyuki Hanawa , Patrick D. Mullen

Reduced-order models (ROMs) are often used to accelerate the simulation of large physical systems. However, traditional ROM techniques, such as those based on proper orthogonal decomposition (POD), often struggle with advection-dominated…

Numerical Analysis · Mathematics 2025-11-07 Toby van Gastelen , Wouter Edeling , Benjamin Sanderse