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Extreme events are ubiquitous in a wide range of dynamical systems, including turbulent fluid flows, nonlinear waves, large scale networks and biological systems. Here, we propose a variational framework for probing conditions that trigger…

Fluid Dynamics · Physics 2018-07-10 Mohammad Farazmand , Themistoklis P. Sapsis

We develop a framework to give upper bounds on the "practical" computational complexity of stability problems for a wide range of nonlinear continuous and hybrid systems. To do so, we describe stability properties of dynamical systems using…

Systems and Control · Computer Science 2014-06-05 Sicun Gao , Soonho Kong , Edmund Clarke

The possibility that evolutionary forces -- together with a few fundamental factors such as thermodynamic constraints, specific computational features enabling information processing, and ecological processes -- might constrain the logic of…

Biological Physics · Physics 2025-12-30 Manlio De Domenico

Large scale parameter estimation problems are among some of the most computationally demanding problems in numerical analysis. An academic researcher's domain-specific knowledge often precludes that of software design, which results in…

Mathematical Software · Computer Science 2017-04-05 Curt Da Silva , Felix J. Herrmann

In this work, we present scalable balancing domain decomposition by constraints methods for linear systems arising from arbitrary order edge finite element discretizations of multi-material and heterogeneous 3D problems. In order to enforce…

Computational Engineering, Finance, and Science · Computer Science 2024-12-20 Santiago Badia , Alberto F. Martín , Marc Olm

The Energy-Dissipation Principle provides a variational tool for the analysis of parabolic evolution problems: solutions are characterized as so-called null-minimizers of a global functional on entire trajectories. This variational…

Analysis of PDEs · Mathematics 2021-09-14 Luca Scarpa , Ulisse Stefanelli

We provide a new approach to obtain solutions of certain evolution equations set in a Banach space and equipped with nonlocal boundary conditions. From this approach we derive a family of numerical schemes for the approximation of the…

Numerical Analysis · Mathematics 2024-02-13 Paola Boito , Yuli Eidelman , Luca Gemignani

Materials science inherently spans disciplines: experimentalists use advanced microscopy to uncover micro- and nanoscale structure, while theorists and computational scientists develop models that link processing, structure, and properties.…

Machine Learning · Computer Science 2026-03-25 Simon Daubner , Alexander E. Cohen , Benjamin Dörich , Samuel J. Cooper

This paper studies formulations of second-order elliptic partial differential equations in nondivergence form on convex domains as equivalent variational problems. The first formulation is that of Smears \& S\"uli [SIAM J.\ Numer.\ Anal.\…

Numerical Analysis · Mathematics 2017-01-17 Dietmar Gallistl

Nonlinearities and instabilities in mechanical structures have shown great promise for embedding advanced functionalities. However, simulating structures subject to nonlinearities can be challenging due to the complexity of their behavior,…

Soft Condensed Matter · Physics 2025-10-23 Paul Ducarme , Bart Weber , Martin van Hecke , Johannes T. B. Overvelde

We present a robust computational framework for advective-diffusive-reactive systems that satisfies maximum principles, the non-negative constraint, and element-wise species balance property. The proposed methodology is valid on general…

Numerical Analysis · Mathematics 2015-11-10 M. K. Mudunuru , K. B. Nakshatrala

We study diffusion-type equations supported on structures that are randomly varying in time. After settling the issue of well-posedness, we focus on the asymptotic behavior of solutions: our main result gives sufficient conditions for…

Dynamical Systems · Mathematics 2020-04-28 Stefano Bonaccorsi , Francesca Cottini , Delio Mugnolo

The continuous dependence of solutions to certain (non-autonomous, partial, integro-differential-algebraic, evolutionary) equations on the coefficients is addressed. We give criteria that guarantee that convergence of the coefficients in…

Functional Analysis · Mathematics 2016-01-21 Marcus Waurick

A technique is introduced which allows to generate -- starting from any solvable discrete-time dynamical system involving N time-dependent variables -- new, generally nonlinear, generations of discrete-time dynamical systems, also involving…

Mathematical Physics · Physics 2017-06-07 Oksana Bihun , Francesco Calogero

In this present paper, we introduce and study a dynamical systems involving fractional derivative operator and nonlocal condition, which is constituted of a fractional evolution equation and a time-dependent variational inequality, and is…

General Mathematics · Mathematics 2023-10-11 Jinxia Cen , J. Vanterler da C. Sousa , Wei Wu

We study numerical methods for the nonlinear partial differential equation that governs the motion of level sets by affine curvature. We show that standard finite difference schemes are nonlinearly unstable. We build convergent finite…

Numerical Analysis · Mathematics 2016-11-01 Adam M. Oberman , Tiago Salvador

Nonlinear equations systems (NESs) are widely used in real-world problems while they are also difficult to solve due to their characteristics of nonlinearity and multiple roots. Evolutionary algorithm (EA) is one of the methods for solving…

Neural and Evolutionary Computing · Computer Science 2020-08-11 Aijuan Song , Guohua Wu , Witold Pedrycz

We consider nonlinear viscoelastic materials of differential type and for some special models we derive exact solutions of initial boundary value problems. These exact solutions are used to investigate the reasons of non-existence of global…

Classical Physics · Physics 2011-09-28 Edvige Pucci , Giuseppe Saccomandi

Fractional order models have proven to be a very useful tool for the modeling of the mechanical behaviour of viscoelastic materials. Traditional numerical solution methods exhibit various undesired properties due to the non-locality of the…

Numerical Analysis · Mathematics 2023-01-30 Kai Diethelm

Diffusion models have emerged as powerful generative tools with applications in computer vision and scientific machine learning (SciML), where they have been used to solve large-scale probabilistic inverse problems. Traditionally, these…

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