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Related papers: Reduced models of point vortex systems

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We propose a method for approximating solutions to optimization problems involving the global stability properties of parameter-dependent continuous-time autonomous dynamical systems. The method relies on an approximation of the…

Optimization and Control · Mathematics 2013-08-12 Péter Koltai , Alexander Volf

This paper focuses on the numerical simulation of geothermal systems in complex geological settings. The physical model is based on two-phase Darcy flows coupling the mass conservation of the water component with the energy conservation and…

This paper presents a novel non-linear model reduction method: Probabilistic Manifold Decomposition (PMD), which provides a powerful framework for constructing non-intrusive reduced-order models (ROMs) by embedding a high-dimensional system…

Numerical Analysis · Mathematics 2026-01-09 Jiaming Guo , Dunhui Xiao

Linearized models of power systems are often desirable to formulate tractable control and optimization problems that still reflect real-world physics adequately under various operating conditions. In this paper, we propose an approach that…

Optimization and Control · Mathematics 2018-05-28 Marc Hohmann , Joseph Warrington , John Lygeros

Many living and physical systems such as cell aggregates, tissues or bacterial colonies behave as unconventional systems of particles that are strongly constrained by volume exclusion and shape interactions. Understanding how these…

Quantitative Methods · Quantitative Biology 2026-05-20 Antoine Diez , Jean Feydy

Numerical simulation of compressible fluid flows is performed using the Euler equations. They include the scalar advection equation for the density, the vector advection equation for the velocity and a given pressure dependence on the…

Computational Engineering, Finance, and Science · Computer Science 2018-01-22 Petr N. Vabishchevich

High-dimensional dynamical systems projected onto a reduced-order model cease to be deterministic and are best described by probability distributions in state space. Their equations of motion map onto an evolution operator with a…

Fluid Dynamics · Physics 2024-11-20 Javier Jiménez

We formulate a data-driven, physics-constrained closure method for coarse-scale numerical simulations of turbulent fluid flows. Our approach involves a closure scheme that is non-local both in space and time, i.e. the closure terms are…

Fluid Dynamics · Physics 2021-02-16 Alexis-Tzianni G. Charalampopoulos , Themistoklis P. Sapsis

We develop a method for multidimensional optimisation using flow equations. This method is based on homotopy continuation in combination with a maximum entropy approach. Extrema of the optimising functional correspond to fixed points of the…

Other Condensed Matter · Physics 2015-06-19 Matthias Punk

The present work extends known finite-dimensional constrained optimal control realizations to the realm of well-posed regular linear infinite-dimensional systems modelled by partial differential equations. The structure-preserving…

Optimization and Control · Mathematics 2020-05-21 Stevan Dubljevic , Jukka-Pekka Humaloja

We introduce a family of stochastic models motivated by the study of nonequilibrium steady states of fluid equations. These models decompose the deterministic dynamics of interest into fundamental building blocks, i.e., minimal vector…

Probability · Mathematics 2025-05-07 Andrea Agazzi , Jonathan C. Mattingly , Omar Melikechi

A new framework is introduced for constructing interpretable and truly reliable reduced models for multiscale problems in situations without scale separation. Hydrodynamic approximation to the kinetic equation is used as an example to…

Computational Physics · Physics 2019-10-31 Jiequn Han , Chao Ma , Zheng Ma , Weinan E

This paper deals with the one perturbed vortex dynamics problem which describes the system of two point vortices in a Bose-Einstein condensate enclosed in a cylindrical trap. This system is a completely integrable Hamiltonian system with…

Exactly Solvable and Integrable Systems · Physics 2018-11-27 Pavel E. Ryabov

In a recent paper, the authors proposed a general methodology for probabilistic learning on manifolds. The method was used to generate numerical samples that are statistically consistent with an existing dataset construed as a realization…

Probability · Mathematics 2018-03-30 C. Soizea , R. Ghanem , C. Safta , X. Huan , Z. P. Vane , J. Oefelein , G. Lacaz , H. N. Najm , Q. Tang , X. Chen

We analyze the convergence of the irreversible event-chain Monte Carlo algorithm for continuous spin models in the presence of topological excitations. In the two-dimensional XY model, we show that the local nature of the Markov-chain…

Statistical Mechanics · Physics 2018-09-13 Ze Lei , Werner Krauth

State-specific thermochemical collisional models are crucial to accurately describe the physics of systems involving nonequilibrium plasmas, but they are also computationally expensive and impractical for large-scale, multi-dimensional…

Computational Physics · Physics 2025-04-14 Ivan Zanardi , Alberto Padovan , Daniel J. Bodony , Marco Panesi

Finite-dimensional dissipative dynamical systems with multiple time-scales are obtained when modeling chemical reaction kinetics with ordinary differential equations. Such stiff systems are computationally hard to solve and therefore,…

Optimization and Control · Mathematics 2019-07-03 Marcus Heitel , Robin Verschueren , Moritz Diehl , Dirk Lebiedz

We consider the problem of computing equilibria (steady-states) for droop-controlled, islanded, AC microgrids that are both economic-optimal and dynamically stable. This work is motivated by the observation that classical optimal power flow…

Optimization and Control · Mathematics 2020-02-25 Sungho Shin , Victor M. Zavala

Typical fully conservative discretizations of the Euler compressible single or multi-component fluid equations governed by a real-fluid equation of state exhibit spurious pressure oscillations due to the nonlinearity of the thermodynamic…

Computational Physics · Physics 2025-12-05 Christopher DeGrendele , Nguyen Ly , Francois Cadieux , Michael Barad , Dongwook Lee , Jared Duensing

Devising optimal interventions for constraining stochastic systems is a challenging endeavour that has to confront the interplay between randomness and nonlinearity. Existing methods for identifying the necessary dynamical adjustments…

Statistical Mechanics · Physics 2022-10-18 Dimitra Maoutsa , Manfred Opper
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