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Discrete variational methods show excellent performance in numerical simulations of mechanical systems. In this paper, we adapt discrete variational integrators for the case of mechanical systems with double-bracket dissipation. In…

Numerical Analysis · Mathematics 2026-04-30 Anthony Bloch , Sebastián J. Ferraro , David Martín de Diego , Shreyas Bharadwaj

The optimal layout of a complex system such as aerospace vehicles consists in placing a given number of components in a container in order to minimize one or several objectives under some geometrical or functional constraints. This paper…

Artificial Intelligence · Computer Science 2022-12-22 Juliette Gamot , Mathieu Balesdent , Arnault Tremolet , Romain Wuilbercq , Nouredine Melab , El-Ghazali Talbi

As a phase space language for quantum mechanics, the Wigner function approach bears a close analogy to classical mechanics and has been drawing growing attention, especially in simulating quantum many-body systems. However, deterministic…

Computational Physics · Physics 2016-11-30 Yunfeng Xiong , Zhenzhu Chen , Sihong Shao

In this manuscript, we extend the variational multiscale enrichment (VME) method to model the dynamic response of hyperelastic materials undergoing large deformations. This approach enables the simulation of wave propagation under…

Computational Engineering, Finance, and Science · Computer Science 2025-11-19 Abhishek Arora , Caglar Oskay

We present a new asymptotic strategy for general micro-macro models which analyze complex viscoelastic fluids governed by coupled multiscale dynamics. In such models, the elastic stress appearing in the macroscopic continuum equation is…

Mathematical Physics · Physics 2025-12-22 Xuenan Li , Chun Liu , Di Qi

Large-scale unconstrained optimization is a fundamental and important class of, yet not well-solved problems in numerical optimization. The main challenge in designing an algorithm is to require a few storage locations or very inexpensive…

Optimization and Control · Mathematics 2020-01-24 Zheng Li , Shi Shu , Jian-Ping Zhang

Adhesive joints are increasingly used in industry for a wide variety of applications because of their favorable characteristics such as high strength-to-weight ratio, design flexibility, limited stress concentrations, planar force transfer,…

We devise the fast adjoint response algorithm for the gradient of physical measures (long-time-average statistics) of discrete-time hyperbolic chaos with respect to many system parameters. Its cost is independent of the number of…

Dynamical Systems · Mathematics 2022-09-13 Angxiu Ni

We study an inverse design problem for the linear multiple fragmentation equation arising in particle dynamics. Our objective is to reconstruct an unknown initial size distribution that evolves, under a prescribed fragmentation law, into a…

Optimization and Control · Mathematics 2026-02-20 Arijit Das

Flexible slender structures such as rods, ribbons, plates, and shells exhibit extreme nonlinear responses bending, twisting, buckling, wrinkling, and self contact, that defy conventional simulation frameworks. Discrete Differential Geometry…

Combining discrete and continuous data is an important capability for generative models. We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that provides the missing link in enabling flow-based generative models…

Machine Learning · Statistics 2024-06-07 Andrew Campbell , Jason Yim , Regina Barzilay , Tom Rainforth , Tommi Jaakkola

Distributed model fitting refers to the process of fitting a mathematical or statistical model to the data using distributed computing resources, such that computing tasks are divided among multiple interconnected computers or nodes, often…

Computation · Statistics 2024-06-04 Xiaofei Wu , Rongmei Liang , Fabio Roli , Marcello Pelillo , Jing Yuan

The fully discrete adjoint equations and the corresponding adjoint method are derived for a globally high- order accurate discretization of conservation laws on parametrized, deforming domains. The conservation law on the deforming domain…

Optimization and Control · Mathematics 2016-09-20 Matthew J. Zahr , Per-Olof Persson

Most real optimization problems are defined over a mixed search space where the variables are both discrete and continuous. In engineering applications, the objective function is typically calculated with a numerically costly black-box…

Optimization and Control · Mathematics 2022-05-04 Jhouben Cuesta-Ramirez , Rodolphe Le Riche , Olivier Roustant , Guillaume Perrin , Cedric Durantin , Alain Gliere

This paper presents a multicomponent topology optimization method for designing structures assembled from additively-manufactured components, considering anisotropic material behavior for each component due to its build orientation,…

Computational Engineering, Finance, and Science · Computer Science 2019-11-26 Yuqing Zhou , Tsuyoshi Nomura , Kazuhiro Saitou

The isometric embedding of surfaces in three-dimensional space is fundamental to various physical systems, from elastic sheets to programmable materials. While continuous surfaces typically admit unique solutions under suitable boundary…

Disordered Systems and Neural Networks · Physics 2025-05-13 Kyungeun Kim , Christian D. Santangelo

A recent paper [J. A. Evans, D. Kamensky, Y. Bazilevs, "Variational multiscale modeling with discretely divergence-free subscales", Computers & Mathematics with Applications, 80 (2020) 2517-2537] introduced a novel stabilized finite element…

Numerical Analysis · Mathematics 2021-12-21 Sajje Lee Calfy , John A. Evans , David Kamensky

We develop a space-time spectral element method for topology optimization of transient heat conduction. The forward problem is discretized with summation-by-parts (SBP) operators, and interface/boundary and initial/terminal conditions are…

Numerical Analysis · Mathematics 2026-01-15 Sarah Nataj , Magnus Appel , Joe Alexandersen

Sparse variable selection improves interpretability and generalization in high-dimensional learning by selecting a small subset of informative features. Recent advances in Mixed Integer Programming (MIP) have enabled solving large-scale…

Machine Learning · Statistics 2025-10-28 Petros Prastakos , Kayhan Behdin , Rahul Mazumder

Consider the macroscale modelling of microscale spatiotemporal dynamics. Here we develop a new approach to ensure coarse scale discrete models preserve important self-adjoint properties of the fine scale dynamics. The first part explores…

Cellular Automata and Lattice Gases · Physics 2008-11-06 A. J. Roberts
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