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This paper presents a kriging method for spatial prediction of temporal intensity functions, for situations where a temporal point process is observed at different spatial locations. Assuming that several replications of the processes are…

Methodology · Statistics 2021-07-02 Daniel Gervini

This work introduces a new approach to velocity averaging lemmas in kinetic theory. This approach -- based upon the classical energy method -- provides a powerful duality principle in kinetic transport equations which allows for a natural…

Analysis of PDEs · Mathematics 2021-09-15 Diogo Arsénio , Nicolas Lerner

Neuronal ensemble activity, including coordinated and oscillatory patterns, exhibits hallmarks of nonequilibrium systems with time-asymmetric trajectories to maintain their organization. However, assessing time asymmetry from neuronal…

Neurons and Cognition · Quantitative Biology 2025-12-12 Ken Ishihara , Hideaki Shimazaki

The focus of our study in this paper is on the active dynamics and a fractional generalized Langevin equation with a memory kernel K(t). The Fokker-Planck equation is obtained by deriving it from a second-order differential equation. The…

Statistical Mechanics · Physics 2024-12-17 Yun Jeong Kang , Kyungsik Kim

Perhaps the most basic question we can ask about cosmological correlations is how their strength changes as we smoothly vary kinematic parameters. The answer is encoded in differential equations that govern this evolution in kinematic…

High Energy Physics - Theory · Physics 2023-12-12 Nima Arkani-Hamed , Daniel Baumann , Aaron Hillman , Austin Joyce , Hayden Lee , Guilherme L. Pimentel

This paper develops a conceptual extension of the Kinetic Theory of Active Particles, building upon the framework introduced in [2]. Living systems cannot be adequately described within classical single-scale paradigms, even when refined.…

Dynamical Systems · Mathematics 2026-04-22 Diletta Burini , Damian A. Knopoff

We describe a new technique to estimate the mean square velocity of a Brownian particle from time series of the position of the particle sampled at frequencies several orders of magnitude smaller than the momentum relaxation frequency. We…

Statistical Mechanics · Physics 2014-06-18 Édgar Roldán , Ignacio A. Martínez , Luis Dinis , Raúl A. Rica

The local balance equations for the density, momentum, and energy of a dilute gas of elastic or inelastic hard spheres, strongly confined between two parallel hard plates are obtained. The starting point is a Boltzmann-like kinetic…

Statistical Mechanics · Physics 2020-04-22 J. Javier Brey , P. Maynar , M. I. García de Soria

We study the analytical solution of the Monte Carlo dynamics in the spherical Sherrington-Kirkpatrick model using the technique of the generating function. Explicit solutions for one-time observables (like the energy) and two-time…

Condensed Matter · Physics 2009-10-28 L. L. Bonilla , F. G. Padilla , G. Parisi , F. Ritort

We present a new way of quantum kinetic equation derivation. This method appears as a natural generalization of the many-particle quantum hydrodynamic method. Kinetic equations are derived for different system of particles. First of all we…

Plasma Physics · Physics 2012-12-04 Pavel A. Andreev

We generalize the Green-Kubo approach, previously applied to bulk systems of spherically symmetric active particles [J. Chem. Phys. 145, 161101 (2016)], to include spatially inhomogeneous activity. The method is applied to predict the…

Soft Condensed Matter · Physics 2017-09-20 Abhinav Sharma , Joseph Brader

We provide a detailed multiscale analysis of a system of particles interacting through a dynamical network of links. Starting from a microscopic model, via the mean field limit, we formally derive coupled kinetic equations for the particle…

Analysis of PDEs · Mathematics 2016-07-14 Julien Barré , Pierre Degond , Ewelina Zatorska

In the present paper we give a brief summary of some recent theoretical advances in the treatment of inhomogeneous fluids and methods which have applications in the study of dynamical properties of liquids in situations of extreme…

Statistical Mechanics · Physics 2015-07-15 Umberto Marini Bettolo Marconi , Simone Melchionna

We explore Langevin dynamics in the spherical Sherrington-Kirkpatrick model, delving into the asymptotic energy limit. Our approach involves integro-differential equations, incorporating the Crisanti-Horner-Sommers-Cugliandolo-Kurchan…

Probability · Mathematics 2024-01-09 Tingzhou Yu

In this paper, we consider the kinetic model of continuous type describing a polyatomic gas in two different settings corresponding to a different choice of the functional space used to define macroscopic quantities. Such a model introduces…

Mathematical Physics · Physics 2021-02-16 Vladimir Djordjić , Milana Pavić-Čolić , Nikola Spasojević

We study a Hamiltonian system of type describing a charged particle resonant interaction with an electromagnetic wave. We consider an ensemble of particles that repeatedly pass through the resonance with the wave, and study evolution of the…

Plasma Physics · Physics 2017-10-13 A. V. Artemyev , A. I. Neishtadt , A. A. Vasiliev , D. Mourenas

In a mean-field approximation within Kinetic Field Theory, it is possible to derive an accurate analytic expression for the power spectrum of present-day non-linear cosmic density fluctuations. It depends on the theory of gravity and the…

Cosmology and Nongalactic Astrophysics · Physics 2025-03-13 Alexander Oestreicher , Harshda Saxena , Niklas Reinhardt , Elena Kozlikin , Johannes Dombrowski , Matthias Bartelmann

Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique…

Disordered Systems and Neural Networks · Physics 2021-05-13 Miguel Aguilera , S. Amin Moosavi , Hideaki Shimazaki

Influenced mixed moving average fields are a versatile modeling class for spatio-temporal data. However, their predictive distribution is not generally known. Under this modeling assumption, we define a novel spatio-temporal embedding and a…

Machine Learning · Statistics 2024-08-05 Imma Valentina Curato , Orkun Furat , Lorenzo Proietti , Bennet Stroeh

Inverse kinematic (IK) methods recover the parameters of the joints, given the desired position of selected elements in the kinematic chain. While the problem is well-defined and low-dimensional, it has to be solved rapidly, accounting for…

Machine Learning · Computer Science 2022-05-24 Raphael Bensadoun , Shir Gur , Nitsan Blau , Tom Shenkar , Lior Wolf