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Sparsity-based methods are widely used in machine learning, statistics, and signal processing. There is now a rich class of structured sparsity approaches that expand the modeling power of the sparsity paradigm and incorporate constraints…

Data Structures and Algorithms · Computer Science 2017-12-22 Aleksander Mądry , Slobodan Mitrović , Ludwig Schmidt

A Lagrangian numerical scheme for solving nonlinear degenerate Fokker-Planck equations in space dimensions $d\ge2$ is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies…

Numerical Analysis · Mathematics 2018-06-18 José A. Carrillo , Bertram Düring , Daniel Matthes , David S. McCormick

This paper presents a millisecond-level look-ahead control algorithm for energy storage with constant space complexity and worst-case linear run-time complexity. The algorithm connects the optimal control with the Lagrangian multiplier…

Optimization and Control · Mathematics 2019-12-13 Bolun Xu , Magnus Korpas , Audun Botterud , Francis O'Sullivan

In this work, we study and extend a class of semi-Lagrangian exponential methods, which combine exponential time integration techniques, suitable for integrating stiff linear terms, with a semi-Lagrangian treatment of nonlinear advection…

Numerical Analysis · Mathematics 2025-04-25 João Guilherme Caldas Steinstraesser , Martin Schreiber , Pedro da Silva Peixoto

In this paper, we propose a distributed algorithm for solving large-scale separable convex problems using Lagrangian dual decomposition and the interior-point framework. By adding self-concordant barrier terms to the ordinary Lagrangian, we…

Optimization and Control · Mathematics 2013-02-14 I. Necoara , J. A. K. Suykens

The Eulerian-Lagrangian approach based on Large-Eddy Simulation (LES) is one of the most promising and viable numerical tools to study turbulent dispersed flows when the computational cost of Direct Numerical Simulation (DNS) becomes too…

Fluid Dynamics · Physics 2017-06-02 Alessio Innocenti , Cristian Marchioli , Sergio Chibbaro

Semi-Lagrangian (SL) schemes are known as a major numerical tool for solving transport equations with many advantages and have been widely deployed in the fields of computational fluid dynamics, plasma physics modeling, numerical weather…

Numerical Analysis · Mathematics 2023-08-09 Yongsheng Chen , Wei Guo , Xinghui Zhong

In this paper, we propose an energy decomposition method combined with an HLL Riemann solver that includes an additional dissipation term in the energy equation to improve the numerical stability of the fully implicit, time-evolving coronal…

The explicit semi-Lagrangian method method for solution of Lagrangian transport equations as developed in [Natarajan and Jacobs, Computer and Fluids, 2020] is adopted for the solution of stochastic differential equations that is consistent…

Computational Physics · Physics 2021-07-07 H. Natarajan , P. P. Popov , G. B. Jacobs

Pore-scale simulations accurately describe transport properties of fluids in the subsurface. These simulations enhance our understanding of applications such as assessing hydrogen storage efficiency and forecasting CO$_2$ sequestration…

We propose a new splitting and successively solving augmented Lagrangian (SSAL) method for solving an optimization problem with both semicontinuous variables and a cardinality constraint. This optimization problem arises in several contexts…

Optimization and Control · Mathematics 2015-06-16 Yanqin Bai , Renli Liang , Zhouwang Yang

Background and Objective: Processing electrophysiological signals often requires blind source separation (BSS) due to the nature of mixing source signals. However, its complex computational demands make real-time BSS challenging. The…

Human-Computer Interaction · Computer Science 2024-11-28 Yao Li , Haowen Zhao , Yunfei Liu , Xu Zhang

As a mathematical model of high-speed flow and shock wave propagation in a complex multimaterial setting, Lagrangian hydrodynamics is characterized by moving meshes, advection-dominated solutions, and moving shock fronts with sharp…

Numerical Analysis · Mathematics 2021-11-24 Dylan Matthew Copeland , Siu Wun Cheung , Kevin Huynh , Youngsoo Choi

A significant drawback of Lagrangian (particle-tracking) reactive transport models has been their inability to properly simulate interactions between solid and liquid chemical phases, such as dissolution and precipitation reactions. This…

An explicit high order semi-Lagrangian method is developed for solving Lagrangian transport equations in Eulerian-Lagrangian formulations. To ensure a semi-Lagrangian approximation that is consistent with an explicit Eulerian, discontinuous…

Numerical Analysis · Mathematics 2019-10-16 Hareshram Natarajan , Gustaaf B. Jacobs

We describe an efficient numerical method for simulating the dynamics and steady states of collective spin systems in the presence of dephasing and decay. The method is based on the Schwinger boson representation of spin operators and uses…

Quantum Physics · Physics 2021-05-18 Julian Huber , Peter Kirton , Peter Rabl

Lagrangian particle methods based on detailed atomic and molecular models are powerful computational tools for studying the dynamics of microscale and nanoscale systems. However, the maximum time step is limited by the smallest oscillation…

Computational Physics · Physics 2019-06-26 Ansel L. Blumers , Zhen Li , George Em Karniadakis

Several Lagrangian methodologies have been proposed in recent years to simulate advection-dispersion of solutes in fluids as a mass exchange between numerical particles carrying the fluid. In this paper, we unify these methodologies,…

Computational Physics · Physics 2019-02-26 Guillem Sole-Mari , Michael J. Schmidt , Stephen D. Pankavich , David A. Benson

We present a hybrid particle/grid approach for simulating incompressible fluids on collocated velocity grids. We interchangeably use particle and grid representations of transported quantities to balance efficiency and accuracy. A novel…

For optimization problems with nonlinear constraints, linearly constrained Lagrangian (LCL) methods sequentially minimize a Lagrangian function subject to linearized constraints. These methods converge rapidly near a solution but may not be…

Optimization and Control · Mathematics 2007-05-23 Michael P. Friedlander , Michael A Saunders