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Symplectic and optical joint probability representations of quantum mechanics are considered, in which the functions describing the states are the probability distributions with all random arguments (except the argument of time ). The…

Quantum Physics · Physics 2017-02-01 Ya. A. Korennoy , V. I. Man'ko

A hydrodynamic formulation of the evolution of large-scale structure in the Universe is presented. It relies on the spatially coarse-grained description of the dynamical evolution of a many-body gravitating system. Because of the assumed…

Astrophysics · Physics 2009-10-31 Alvaro Dominguez

We investigate dynamics of deformable self-propelled particles with a repulsive interaction whose magnitude depends on the relative direction of elongation of a pair of particles. A collective motion of the particles appears in two…

Soft Condensed Matter · Physics 2015-05-27 Yu Itino , Takahiro Ohkuma , Takao Ohta

We propose a new model for the description of complex granular particles and their interaction in molecular dynamics simulations of granular material in two dimensions. The grains are composed of triangles which are connected by deformable…

Materials Science · Physics 2007-05-23 Thorsten Poeschel , Volkhard Buchholtz

We give sufficient conditions for asymptotic stabilization of equilibrium points and periodic orbits of a dynamical system when we add a geometric dissipation of gradient type. We also describe the domain of attraction in the case of…

Mathematical Physics · Physics 2016-05-02 Petre Birtea , Dan Comănescu

A vast concourse of events and phenomena occur in nature that may be interrelated by a entropy-maximization technique that provides a comprehensible explanation of a range of physical problems, integrating in a new framework the universal…

Classical Physics · Physics 2021-10-18 Mario J Pinheiro

The evolution of occupied volume under progressive fragmentation of granular matter is studied using a purely geometric model. Rather than modelling disorder directly, properties are investigated by analysing highly ordered reference…

Soft Condensed Matter · Physics 2026-03-25 Malkhazi A. Meladze

We consider a system of two coupled particles evolving in a periodic and spatially symmetric potential under the influence of external driving and damping. The particles are driven individually in such a way that in the uncoupled regime,…

Chaotic Dynamics · Physics 2013-05-27 Colm Mulhern , Dirk Hennig , Andrew D. Burbanks

We put forward a conjecture of recurrence for a gas of hard spheres that collide elastically in a finite volume. The dynamics consists of a sequence of instantaneous binary collisions. We study how the numbers of collisions of different…

Chaotic Dynamics · Physics 2015-05-27 Alexander Jonathan Vidgop , Itzhak Fouxon

Non-equilibrium self-organized patterns formed by particles interacting through competing range interaction are driven over a substrate by an external force. We show that, with increasing driving force, the pre-existed static patterns…

Soft Condensed Matter · Physics 2013-08-20 H. J. Zhao , V. R. Misko , F. M. Peeters

A geometrical formulation for adjoint-symmetries as 1-forms is studied for general partial differential equations (PDEs), which provides a dual counterpart of the geometrical meaning of symmetries as tangent vector fields on the solution…

Mathematical Physics · Physics 2021-03-23 Stephen C. Anco , Bao Wang

An approach to analyse the properties of a particle system is to compare it with different processes to understand when one of them is larger than other ones. The main technique for that is coupling, which may not be easy to construct. We…

Probability · Mathematics 2011-02-22 Davide Borrello

We study a system of self-propelled particles which interact with their neighbors via alignment and repulsion. The particle velocities result from self-propulsion and repulsion by close neighbors. The direction of self-propulsion is…

Mathematical Physics · Physics 2014-04-22 Pierre Degond , Giacomo Dimarco , Thi Bich Ngoc Mac , Nan Wang

A typical system of k difference (or differential) equations can be compressed, or folded into a difference (or ordinary differential) equation of order k. Such foldings appear in control theory as the canonical forms of the controllability…

Dynamical Systems · Mathematics 2014-03-18 H. Sedaghat

The Standard Model of the elementary particles is controlled by more than 20 parameters, of which it is not known today how they can be linked to deeper principles. Any attempt to clean up this theory, in general results in producing more…

High Energy Physics - Theory · Physics 2022-02-14 Gerard t Hooft

A new model that describes adsorption and clustering of particles on a surface is introduced. A {\it clustering} transition is found which separates between a phase of weakly correlated particle distributions and a phase of strongly…

Statistical Mechanics · Physics 2009-10-31 Ofer Biham , Ofer Malcai , Daniel A. Lidar , David Avnir

We consider the dynamics of a collection of particles that interact pairwise and are restricted to move along the real line. Moreover, we focus on the situation in which particles undergo perfectly inelastic collisions when they collide.…

Analysis of PDEs · Mathematics 2020-02-17 Ryan Hynd

When a two-dimensional curved surface is conceived as a limiting case of a curved shell of equal thickness d, where the limit d\rightarrow0 is then taken, the well-known geometric potential is induced by the kinetic energy operator, in fact…

Quantum Physics · Physics 2011-09-27 Q. H. Liu

Given a finite order Lagrangian L on a fibre bundle, its global generalized symmetries depending on higher order derivatives of dynamic variables are considered. The first variational formula is obtained. It leads both to the corresponding…

Mathematical Physics · Physics 2007-05-23 G. Giachetta , L. Mangiarotti , G. Sardanashvily

We use differential equations based approaches to provide some {\it \textbf{physics}} insights into analyzing the dynamics of popular optimization algorithms in machine learning. In particular, we study gradient descent, proximal gradient…

Machine Learning · Computer Science 2018-10-26 Lin F. Yang , R. Arora , V. Braverman , Tuo Zhao
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