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The Navier--Stokes order hydrodynamic equations for a low-density driven granular mixture obtained previously [Khalil and Garz\'o, Phys. Rev. E \textbf{88}, 052201 (2013)] from the Chapman--Enskog solution to the Boltzmann equation are…

Statistical Mechanics · Physics 2018-02-08 Nagi Khalil , Vicente Garzó

Inductive bias refers to restrictions on the hypothesis class that enable a learning method to generalize effectively from limited data. A canonical example in control is linearity, which underpins low sample-complexity guarantees for…

Optimization and Control · Mathematics 2026-04-21 Zhuo Ouyang , Jixian Liu , Enrique Mallada

By analyzing the real space nonequilibrium dynamics of polymers, we elucidate the physics of driven translocation and propose its dynamical scaling scenario analogous to that in the surface growth phenomena. We provide a detailed account of…

Soft Condensed Matter · Physics 2011-11-28 Takuya Saito , Takahiro Sakaue

Analyses of urban scaling laws assume that observations in different cities are independent of the existence of nearby cities. Here we introduce generative models and data-analysis methods that overcome this limitation by modelling…

Physics and Society · Physics 2021-01-21 Eduardo G. Altmann

The development of a subduction zone, whether spontaneous or induced, encompasses a stage of strain localization and is epitomized by the growth of lithospheric-scale shear bands. Our aim in this paper, using a solid-mechanical constitutive…

Geophysics · Physics 2022-12-27 Ekeabino Momoh , Harsha S. Bhat , Steve Tait

The objective of this three-part work is to formulate and rigorously analyse a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled surface…

Fluid Dynamics · Physics 2023-12-29 Piotr Morawiecki , Philippe H. Trinh

We present a detailed derivation of Fourier's law in a class of stochastic energy exchange systems that naturally characterize two-dimensional mechanical systems of locally confined particles in interaction. The stochastic systems consist…

Statistical Mechanics · Physics 2009-08-29 Pierre Gaspard , Thomas Gilbert

We study heat transport in the context of Hamiltonian and related stochastic models with nearest-neighbor coupling, and derive a universal law for the temperature profiles of a large class of such models. This law contains a parameter…

Statistical Mechanics · Physics 2009-11-10 Jean-Pierre Eckmann , Lai-Sang Young

The crucial problem for better understanding the nature of glass transition and related relaxation phenomena is to find proper interrelations between molecular dynamics and thermodynamics of viscous systems. To gain this aim the recently…

Soft Condensed Matter · Physics 2012-10-17 Andrzej Grzybowski , Kajetan Koperwas , Marian Paluch

We describe an asymptotic procedure for deriving continuum equations from the kinetic theory of a simple gas. As in the works of Hilbert, of Chapman and of Enskog, we expand in the mean flight time of the constituent particles of the gas,…

Astrophysics · Physics 2009-11-06 Xinzhong Chen , Hongling Rao , Edward A. Spiegel

The transient growth of disturbances made possible by the non-normality of the linearized Navier-Stokes equations plays an important role in bypass transition for many shear flows. Transient growth is typically quantified by the maximum…

Fluid Dynamics · Physics 2026-03-24 Zhicheng Kai , Peter Frame , Aaron Towne

With the rapid development of computational techniques and scientific tools, great progress of data-driven analysis has been made to extract governing laws of dynamical systems from data. Despite the wide occurrences of non-Gaussian…

Dynamical Systems · Mathematics 2022-10-12 Yubin Lu , Yang Li , Jinqiao Duan

In recent years, research and development in nanoscale science and technology have grown significantly, with electrical transport playing a key role. A natural challenge for its description is to shed light on anomalous behaviours observed…

Populations and Evolution · Quantitative Biology 2025-04-10 Sara Bernardi , Paolo Begnamino , Marco Pizzi , Lamberto Rondoni

The data-driven discovery of interpretable models approximating the underlying dynamics of a physical system has gained attraction in the past decade. Current approaches employ pre-specified functional forms or basis functions and often…

Machine Learning · Computer Science 2025-07-30 Rahul Golder , M. M. Faruque Hasan

Externally driven dense packings of particles can exhibit nonlinear wave phenomena that are not described by effective medium theory or linearized approximate models. Such nontrivial wave responses can be exploited to design…

Soft Condensed Matter · Physics 2024-11-26 Atoosa Parsa , James Bagrow , Corey S. O'Hern , Rebecca Kramer-Bottiglio , Josh Bongard

Learning arguably involves the discovery and memorization of abstract rules. The aim of this paper is to study associative memory mechanisms. Our model is based on high-dimensional matrices consisting of outer products of embeddings, which…

Machine Learning · Statistics 2024-02-22 Vivien Cabannes , Elvis Dohmatob , Alberto Bietti

Because the Navier-Stokes equations are dissipative, the long-time dynamics of a flow in state space are expected to collapse onto a manifold whose dimension may be much lower than the dimension required for a resolved simulation. On this…

Fluid Dynamics · Physics 2023-01-12 Alec J. Linot , Michael D. Graham

Plasticity modelling has long been based on phenomenological models based on ad-hoc assuption of constitutive relations, which are then fitted to limited data. Other work is based on the consideration of physical mechanisms which seek to…

Materials Science · Physics 2022-06-06 Stefan Hiemer , Haidong Fan , Michael Zaiser

This paper investigates the dynamic properties of a confined quasi-two-dimensional granular fluid at moderate densities, modeled within the framework of the Enskog kinetic equation. The system is described using the so-called…

Soft Condensed Matter · Physics 2026-05-06 David González Méndez , Rubén Gómez González , Vicente Garzó

Experimental particle spectra can be successfully described by power-law tailed energy distributions characteristic to canonical equilibrium distributions associated to R\'enyi's or Tsallis' entropy formula - over a wide range of energies,…

Nuclear Theory · Physics 2013-06-27 T. S. Biró , E. Molnár
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