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We provide the detailed asymptotic behavior for first-order aggregation models of heterogeneous oscillators. Due to the dissimilarity of natural frequencies, one could expect that all relative distances converge to definite positive value…

Dynamical Systems · Mathematics 2022-06-03 Dohyun Kim , Hansol Park

Consider a system of particles performing nearest neighbor random walks on the lattice $\ZZ$ under hard--core interaction. The rate for a jump over a given bond is direction--independent and the inverse of the jump rates are i.i.d. random…

Probability · Mathematics 2007-09-05 A. Faggionato , M. Jara , C. Landim

It is well-known that many diffusion equations can be recast as Wasserstein gradient flows. Moreover, in recent years, by modifying the Wasserstein distance appropriately, this technique has been transferred to further evolution equations…

Probability · Mathematics 2020-10-15 Kaveh Bashiri , Anton Bovier

We derive the system of differential equations for the gradient flow characterizing the training process of linear in-context learning in full generality. Next, we explore the geometric structure of the gradient flows in two instances,…

Dynamical Systems · Mathematics 2024-12-24 Songtao Lu , Yingdong Lu , Tomasz Nowicki

We consider an infinite lattice system of interacting spins living on a smooth compact manifold, with short- but not necessarily finite-range pairwise interactions. We construct the gradient flow of the infinite-volume free energy on the…

Probability · Mathematics 2025-02-19 Ronan Herry , Thomas Leblé

Far-from-equilibrium kinetic systems collapse onto a hydrodynamic attractor, traditionally approximated by a gradient expansion. While temporal gradient series are non-Borel summable and require transseries completions, the analytic…

Mathematical Physics · Physics 2026-04-07 Mahdi Kooshkbaghi

An appealing property of the natural gradient is that it is invariant to arbitrary differentiable reparameterizations of the model. However, this invariance property requires infinitesimal steps and is lost in practical implementations with…

Machine Learning · Computer Science 2018-06-11 Yang Song , Jiaming Song , Stefano Ermon

We study the hydrodynamic limit for three gradient spin models: generalized Kipnis-Marchioro-Presutti (KMP), its discrete version and a family of harmonic models, under symmetric and nearest-neighbor interactions. These three models share…

Probability · Mathematics 2025-05-19 Chiara Franceschini , Patrícia Gonçalves , Kohei Hayashi , Makiko Sasada

We perform a convergence analysis of a discrete-in-time minimization scheme approximating a finite dimensional singularly perturbed gradient flow. We allow for different scalings between the viscosity parameter $\varepsilon$ and the time…

Analysis of PDEs · Mathematics 2018-11-14 Giovanni Scilla , Francesco Solombrino

Magneto-hydrodynamics is one of the foremost models in plasma physics with applications in inertial confinement fusion, astrophysics and elsewhere. Advanced numerical methods are needed to get an insight into the complex physical phenomena.…

Computational Physics · Physics 2022-03-29 Jan Nikl , Milan Kuchařík , Stefan Weber

We derive a hydrodynamic description of metric-free active matter: starting from self-propelled particles aligning with neighbors defined by "topological" rules, not metric zones, -a situation advocated recently to be relevant for bird…

Soft Condensed Matter · Physics 2015-06-04 Anton Peshkov , Sandrine Ngo , Eric Bertin , Hugues Chaté , Francesco Ginelli

We report part of our recent work on viscous hydrodynamics with consistent phase space distribution $f(x,\p)$ for freeze out. We develop the gradient expansion formalism based on kinetic theory, and with the constraints from the comparison…

Nuclear Theory · Physics 2015-06-11 Li Yan

Several quantities important in condensed matter physics, quantum information, and quantum chemistry, as well as quantities required in meta-optimization of machine learning algorithms, can be expressed as gradients of implicitly defined…

Quantum Physics · Physics 2022-11-28 Shahnawaz Ahmed , Nathan Killoran , Juan Felipe Carrasquilla Álvarez

Collective motion is often modeled within the framework of active fluids, where the constituent active particles, when interactions with other particles are switched off, perform normal diffusion at long times. However, in biology,…

Statistical Mechanics · Physics 2020-04-02 Andrea Cairoli , Chiu Fan Lee

We study the gradient flow of the potential energy on the infinite-dimensional Riemannian manifold of spatial curves parametrized by the arc length, which models overdamped motion of a falling inextensible string. We prove existence of…

Analysis of PDEs · Mathematics 2019-02-28 Wenhui Shi , Dmitry Vorotnikov

Our conventional understanding of optical responses in metals has been based on the Drude theory. In recent years, however, it has become possible to prepare ultrapure metallic samples where the electron-electron scattering becomes the most…

Mesoscale and Nanoscale Physics · Physics 2019-10-04 Riki Toshio , Kazuaki Takasan , Norio Kawakami

We address several concerns related to the derivation of drift-ordered fluid equations. Starting from a fully Galilean invariant fluid system, we show how consistent sets of perturbative drift-fluid equations in the case of a isothermal…

Plasma Physics · Physics 2019-03-27 Jakob Gath , Matthias Wiesenberger

We develop a general kinetic theory framework to describe the hydrodynamics of strongly interacting, nonequilibrium quantum systems in which integrability is weakly broken, leaving a few residual conserved quantities. This framework is…

Statistical Mechanics · Physics 2021-03-03 Javier Lopez-Piqueres , Brayden Ware , Sarang Gopalakrishnan , Romain Vasseur

Dissipation anomaly-the persistence of finite energy dissipation in the inviscid limit-is a hallmark of turbulence, sometimes regarded as the "zeroth law" of turbulent flows. Here, we demonstrate that this phenomenon is not exclusive to…

Statistical Mechanics · Physics 2025-11-25 Hiroyoshi Nakano , Yuki Minami

We propose a variational form of the BDF2 method as an alternative to the commonly used minimizing movement scheme for the time-discrete approximation of gradient flows in abstract metric spaces. Assuming uniform semi-convexity --- but no…

Analysis of PDEs · Mathematics 2017-12-25 Daniel Matthes , Simon Plazotta