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Related papers: Kang-Redner Anomaly in Cluster-Cluster Aggregation

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We consider the scaling solutions of Smoluchowski's equation of irreversible aggregation, for a non gelling collision kernel. The scaling mass distribution f(s) diverges as s^{-tau} when s->0. tau is non trivial and could, until now, only…

Statistical Mechanics · Physics 2016-08-31 Stephane Cueille , Clement Sire

We realized one dimensional disordered photonic structures by grouping high refractive index layers in clusters, randomly distributed in such structure. We have control on the maximum size of the cluster and on the ratio high-low refractive…

Materials Science · Physics 2016-09-21 Michele Bellingeri , Francesco Scotognella

We consider a system of classical particles confined in a box $\Lambda\subset\mathbb{R}^d$ with zero boundary conditions interacting via a stable and regular pair potential. Based on the validity of the cluster expansion for the canonical…

Probability · Mathematics 2021-03-30 Giuseppe Scola

We consider diffusion limited aggregation of particles of two different kinds. It is assumed that a particle of one kind may adhere only to another particle of the same kind. The particles aggregate on a linear substrate which consists of…

Other Condensed Matter · Physics 2015-05-20 E. B. Postnikov , A. B. Ryabov , A. Loskutov

We study the long-time asymptotic behavior of the position distribution of a run-and-tumble particle (RTP) in two dimensions and show that the distribution at a time $t$ can be expressed as a perturbative series in $(\gamma t)^{-1}$, where…

Statistical Mechanics · Physics 2023-03-24 Ion Santra , Urna Basu , Sanjib Sabhapandit

We study, in d-dimensions, the random walker with geometrically shrinking step sizes at each hop. We emphasize the integrated quantities such as expectation values, cumulants and moments rather than a direct study of the probability…

Statistical Mechanics · Physics 2009-11-11 Tonguc Rador

We carry out the asymptotic analysis of repulsive ensembles of N particles which are discrete analogues of continuous 1d log-gases or beta-ensembles of random matrix theory. The ensembles that we study have several groups of particles which…

Probability · Mathematics 2026-03-03 Gaëtan Borot , Vadim Gorin , Alice Guionnet

We study a new parametric family of distributions on the ordered simplex $\nabla^{d-1} = \{y \in \mathbb{R}^d: y_1 \geq \dots \geq y_d \geq 0, \sum_{k=1}^d y_k = 1\}$, which we call Generalized Rank Dirichlet (GRD) distributions. Their…

Probability · Mathematics 2023-10-25 David Itkin

We consider the mass-dependent aggregation process (k+1)X -> X, given a fixed number of unit mass particles in the initial state. One cluster is chosen proportional to its mass and is merged into one either with k-neighbors in one…

Data Analysis, Statistics and Probability · Physics 2011-11-02 Seung-Woo Son , Claire Christensen , Golnoosh Bizhani , Peter Grassberger , Maya Paczuski

Anomalous diffusion occurs in many physical and biological phenomena, when the growth of the mean squared displacement (MSD) with time has an exponent different from one. We show that recurrent neural networks (RNN) can efficiently…

Statistical Mechanics · Physics 2019-07-24 Stefano Bo , Falko Schmidt , Ralf Eichhorn , Giovanni Volpe

We study two types of probability measures on the set of integer partitions of $n$ with at most $m$ parts. The first one chooses the random partition with a chance related to its largest part only. We then obtain the limiting distributions…

Probability · Mathematics 2023-01-03 Tiefeng Jiang , Ke Wang

We consider the one-dimensional Katz-Lebowitz-Spohn (KLS) model, which is a two-parameter generalization of the Totally Asymmetric Simple Exclusion Process (TASEP) with nearest neighbour interaction. Using a powerful mapping, the KLS model…

Statistical Mechanics · Physics 2010-09-08 Attila Rákos

The definitions of breaks and clusters in a one-dimensional chain in equilibrium are discussed. Analytical expressions are obtained for the expected cluster length, $\langle K \rangle$, as a function of temperature and pressure in a…

Statistical Mechanics · Physics 2017-10-04 G. R. Lee-Dadswell , Nicholas Barrett , Michael Power

Relative entropy serves as a cornerstone concept in quantum information theory. In this work, we study relative entropy of random states from major generic state models of Hilbert-Schmidt and Bures-Hall ensembles. In particular, we derive…

Mathematical Physics · Physics 2026-05-28 Lu Wei

The probability distribution of the maximum $M_t$ of a single resetting Brownian motion (RBM) of duration $t$ and resetting rate $r$, properly centred and scaled, is known to converge to the standard Gumbel distribution of the classical…

Statistical Mechanics · Physics 2026-01-19 Alexander K. Hartmann , Satya N. Majumdar , Gregory Schehr

The aggregation properties of heavy inertial particles in the elastic turbulence regime of an Oldroyd-B fluid with periodic Kolmogorov mean flow are investigated by means of extensive numerical simulations in two dimensions. Both the small…

Fluid Dynamics · Physics 2018-10-03 Himani Garg , Enrico Calzavarini , Gilmar Mompean , Stefano Berti

We extend the generalized D-dimensional unitarity method for numerical evaluation of one-loop amplitudes by incorporating massive particles. The issues related to extending the spinor algebra to higher dimensions, treatment of external…

High Energy Physics - Phenomenology · Physics 2010-04-21 R. K. Ellis , W. T. Giele , Z. Kunszt , K. Melnikov

The dynamics of a coupled two-component nonequilibrium system is examined by means of continuum field theory representing the corresponding master equation. Particles of species A may perform hopping processes only when particles of…

Statistical Mechanics · Physics 2009-10-31 S. Trimper , U. C. Taeuber , G. M. Schuetz

We introduce kernel thinning, a new procedure for compressing a distribution $\mathbb{P}$ more effectively than i.i.d. sampling or standard thinning. Given a suitable reproducing kernel $\mathbf{k}_{\star}$ and $O(n^2)$ time, kernel…

Machine Learning · Statistics 2024-05-14 Raaz Dwivedi , Lester Mackey

Density aggregation is a central problem in machine learning, for instance when combining predictions from a Deep Ensemble. The choice of aggregation remains an open question with two commonly proposed approaches being linear pooling…