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Using the matrix product formalism we formulate a natural p-species generalization of the asymmetric simple exclusion process. In this model particles hop with their own specific rate and fast particles can overtake slow ones with a rate…

Statistical Mechanics · Physics 2016-08-31 V. Karimipour

We prove several results concerning a polynomial that arises from the sandpile model on directed graphs; these results are previously only known for undirected graphs. Implicit in the sandpile model is the choice of a sink vertex, and it is…

Combinatorics · Mathematics 2018-02-13 Swee Hong Chan

On a smooth bounded Euclidean domain, Sobolev-subcritical fast diffusion with vanishing boundary trace is known to lead to finite-time extinction, with a vanishing profile selected by the initial datum. In rescaled variables, we quantify…

Analysis of PDEs · Mathematics 2023-03-22 Beomjun Choi , Robert J. McCann , Christian Seis

We investigate the bulldozing motion of a granular sandpile driven forwards by a vertical plate. The problem is set up in the laboratory by emplacing the pile on a table rotating underneath a stationary plate; the continual circulation of…

Fluid Dynamics · Physics 2014-05-02 A. Sauret , N. J. Balmforth , C. P. Caulfield , J. N. McElwaine

We present classes of models in which particles are dropped on an arbitrary fixed finite connected graph, obeying adhesion rules with screening. We prove that there is an invariant distribution for the resulting height profile, and Gaussian…

Probability · Mathematics 2010-12-23 S. R. Fleurke , M. Formentin , C. Kuelske

Random graphs have played an instrumental role in modelling real-world networks arising from the internet topology, social networks, or even protein-interaction networks within cells. Percolation, on the other hand, has been the fundamental…

Probability · Mathematics 2018-09-12 Souvik Dhara

Graph generative models have broad applications in biology, chemistry and social science. However, modelling and understanding the generative process of graphs is challenging due to the discrete and high-dimensional nature of graphs, as…

Machine Learning · Computer Science 2022-12-06 Han Huang , Leilei Sun , Bowen Du , Yanjie Fu , Weifeng Lv

The existing estimation of the upper critical dimension of the Abelian Sandpile Model is based on a qualitative consideration of avalanches as self-avoiding branching processes. We find an exact representation of an avalanche as a sequence…

Statistical Mechanics · Physics 2007-05-23 V. B. Priezzhev

We prove a necessary and sufficient condition for an Abelian Sandpile Model (ASM) to be avalanche-finite, namely: all unstable states of the system can be brought back to stability in finite number of topplings. The method is also…

adap-org · Physics 2015-06-24 S. W. Chan , H. F. Chau

The characteristics of topologically protected wave propagation is typically predicted via the band structure of the primitive unit cell, using Berry curvature to predict localized interface or boundary states (as well as their degree of…

Applied Physics · Physics 2023-01-25 Joshua R Tempelman , Alexander F Vakakis , Kathryn H Matlack

We prove that a distance-regular graph with a dominant distance is a spectral expander. The key ingredient of the proof is a new inequality on the intersection numbers. We use the spectral gap bound to study the structure of the…

Combinatorics · Mathematics 2021-07-28 Bohdan Kivva

We consider the systems of diffusion-orthogonal polynomials, defined in the work [1] of D. Bakry, S. Orevkov and M. Zani and (particularly) explain why these systems with boundary of maximal possible degree should always come from the…

Algebraic Geometry · Mathematics 2014-09-19 Lev Soukhanov

Consider a graph where the sites are distributed in space according to a Poisson point process on $\mathbb R^n$. We study a population evolving on this network, with individuals jumping between sites with a rate which decreases…

Probability · Mathematics 2023-04-05 Vincent Bansaye , Michele Salvi

Diffusion probabilistic models (DPMs), widely recognized for their potential to generate high-quality samples, tend to go unnoticed in representation learning. While recent progress has highlighted their potential for capturing visual…

Machine Learning · Computer Science 2025-05-09 Dingshuo Chen , Shuchen Xue , Liuji Chen , Yingheng Wang , Qiang Liu , Shu Wu , Zhi-Ming Ma , Liang Wang

In order to complete (and generalize) results of Gardiner and Praeger on 4-valent symmetric graphs (European J. Combin, 15 (1994)) we apply the method of lifting automorphisms in the context of elementary-abelian covering projections. In…

Combinatorics · Mathematics 2017-08-01 Boštjan Kuzman , Aleksander Malnič , Primož Potočnik

Given a weighted graph, we introduce a partition of its vertex set such that the distance between any two clusters is bounded from below by a power of the minimum weight of both clusters. This partition is obtained by recursively merging…

Probability · Mathematics 2020-03-16 Laurent Ménard , Arvind Singh

We study sandpile models as closed systems, with conserved energy density $\zeta$ playing the role of an external parameter. The critical energy density, $\zeta_c$, marks a nonequilibrium phase transition between active and absorbing…

Statistical Mechanics · Physics 2016-08-31 Alessandro Vespignani , Ronald Dickman , Miguel A. Munoz , Stefano Zapperi

The paper addresses the single-file diffusion in the presence of an absorbing boundary. The emphasis is on an interplay between the hard-core interparticle interaction and the absorption process. The resulting dynamics exhibits several…

Statistical Mechanics · Physics 2014-02-26 Artem Ryabov , Petr Chvosta

Generation of graphs is a major challenge for real-world tasks that require understanding the complex nature of their non-Euclidean structures. Although diffusion models have achieved notable success in graph generation recently, they are…

Machine Learning · Computer Science 2024-06-04 Jaehyeong Jo , Dongki Kim , Sung Ju Hwang

This paper focuses on spectral graph convolutional neural networks (ConvNets), where filters are defined as elementwise multiplication in the frequency domain of a graph. In machine learning settings where the dataset consists of signals…

Machine Learning · Computer Science 2021-06-15 Ron Levie , Wei Huang , Lorenzo Bucci , Michael M. Bronstein , Gitta Kutyniok