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Numerical methods that preserve geometric invariants of the system, such as energy, momentum or the symplectic form, are called geometric integrators. In this paper we present a method to construct symplectic-momentum integrators for…

Numerical Analysis · Mathematics 2014-11-07 Leonardo Colombo , Sebastián Ferraro , David Martín de Diego

In this paper we analyze several inexact fast augmented Lagrangian methods for solving linearly constrained convex optimization problems. Mainly, our methods rely on the combination of excessive-gap-like smoothing technique developed in…

Optimization and Control · Mathematics 2015-05-14 Andrei Patrascu , Ion Necoara , Quoc Tran-Dinh

This work introduces an unconventional inexact augmented Lagrangian method where the augmenting term is a Euclidean norm raised to a power between one and two. The proposed algorithm is applicable to a broad class of constrained nonconvex…

Optimization and Control · Mathematics 2025-11-25 Alexander Bodard , Konstantinos Oikonomidis , Emanuel Laude , Panagiotis Patrinos

In this paper, we revisit the augmented Lagrangian method for a class of nonsmooth convex optimization. We present the Lagrange optimality system of the augmented Lagrangian associated with the problems, and establish its connections with…

Optimization and Control · Mathematics 2020-01-14 Bangti Jin , Tomoya Takeuchi

Distributed asynchronous SGD has become widely used for deep learning in large-scale systems, but remains notorious for its instability when increasing the number of workers. In this work, we study the dynamics of distributed asynchronous…

Machine Learning · Computer Science 2018-05-23 Joeri Hermans , Gilles Louppe

Our approach is part of the close link between continuous dissipative dynamical systems and optimization algorithms. We aim to solve convex minimization problems by means of stochastic inertial differential equations which are driven by the…

Optimization and Control · Mathematics 2025-06-06 Rodrigo Maulen-Soto , Jalal Fadili , Hedy Attouch , Peter Ochs

We devise and evaluate numerically a Hybrid High-Order (HHO) method for incremental associative plasticity with small deformations. The HHO method uses as discrete unknowns piecewise polynomials of order $k\ge1$ on the mesh skeleton,…

Computational Engineering, Finance, and Science · Computer Science 2019-02-20 Mickaël Abbas , Alexandre Ern , Nicolas Pignet

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

Total Lagrangian Smoothed Particle Hydrodynamics (TLSPH) is one variant of SPH where the variables are described using the fixed reference configuration and a Lagrangian smoothing kernel. TLSPH elevates the computational efficiency of the…

Numerical Analysis · Mathematics 2024-09-05 I. M. Wiragunarsa , L. R. Zuhal , T. Dirgantara , I. S. Putra , E. Febrianto

Since its inception, the full Lagrangian meshless smoothed particle hydrodynamics (SPH) method has experienced a tremendous enhancement in methodology and impacted a range of multi-physics applications in science and engineering. The paper…

Computational Physics · Physics 2024-05-24 Chi Zhang , Yujie Zhu , Dong Wu , Xiangyu Hu

The H2 guaranteed cost decentralized control problem is investigated in this work. More specifically, on the basis of an appropriate H2 re-formulation that we put in place, the optimal control problem in the presence of parameter…

Optimization and Control · Mathematics 2021-01-13 Jun Ma , Zilong Cheng , Xiaoxue Zhang , Masayoshi Tomizuka , Tong Heng Lee

We introduce some sparse grids interpolations used in Semi-Lagrangian schemes for linear and fully non-linear diffusion Hamilton Jacobi Bellman equations arising in stochastic control. We prove that the method introduced converges toward…

Optimization and Control · Mathematics 2014-08-20 Xavier Warin

We are interested in optimally controlling a discrete time dynamical system that can be influenced by exogenous uncertainties. This is generally called a Stochas-tic Optimal Control (SOC) problem and the Dynamic Programming (DP) principle…

Optimization and Control · Mathematics 2017-05-25 François Pacaud , Pierre Carpentier , Jean-Philippe Chancelier , Vincent Leclère

We introduce a new computational method for embedding Lagrangian sink particles into an Eulerian calculation. Simulations of gravitational collapse or accretion generally produce regions whose density greatly exceeds the mean density in the…

Astrophysics · Physics 2009-11-10 Mark R. Krumholz , Christopher F. McKee , Richard I. Klein

The aim of the present text is twofold: to provide a compendium of Lagrangian and Hamiltonian geometries and to introduce and investigate new analytical Mechanics: Finslerian, Lagrangian and Hamiltonian. The fundamental equations (or…

Differential Geometry · Mathematics 2012-03-20 Radu Miron

The aim of this work is to study, from an intrinsic and geometric point of view, second-order constrained variational problems on Lie algebroids, that is, optimization problems defined by a cost functional which depends on higher-order…

Mathematical Physics · Physics 2017-01-18 Leonardo Colombo

We develop a high-order hybridized discontinuous Galerkin (HDG) method for a linear degenerate elliptic equation arising from a two-phase mixture of mantle convection or glacier dynamics. We show that the proposed HDG method is well-posed…

Computational Engineering, Finance, and Science · Computer Science 2019-05-01 Shinhoo Kang , Tan Bui-Thanh , Todd Arbogast

Recovering high quality surfaces from noisy triangulated surfaces is a fundamental important problem in geometry processing. Sharp features including edges and corners can not be well preserved in most existing denoising methods except the…

Computational Geometry · Computer Science 2021-01-07 Zheng Liu , Rongjie Lai , Huayan Zhang , Chunlin Wu

Lagrangian-based methods are classical methods for solving convex optimization problems with equality constraints. We present novel prediction-correction frameworks for such methods and their variants, which can achieve $O(1/k)$ non-ergodic…

Optimization and Control · Mathematics 2023-04-06 Tao Zhang , Yong Xia , Shiru Li

In this paper we present a formally fourth-order accurate hybrid-variable method for the Euler equations in the context of method of lines. The hybrid-variable (HV) method seeks numerical approximations to both cell-averages and nodal…

Numerical Analysis · Mathematics 2023-08-22 Xianyi Zeng
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