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Given their ability to effectively learn non-linear mappings and perform fast inference, deep neural networks (NNs) have been proposed as a viable alternative to traditional simulation-driven approaches for solving high-dimensional…

Machine Learning · Computer Science 2022-02-16 Sangeeta Srivastava , Samuel Olin , Viktor Podolskiy , Anuj Karpatne , Wei-Cheng Lee , Anish Arora

One-dependent first passage percolation is a spreading process on a graph where the transmission time through each edge depends on the direct surroundings of the edge. In particular, the classical iid transmission time $L_{xy}$ is…

Probability · Mathematics 2024-03-26 Júlia Komjáthy , John Lapinskas , Johannes Lengler , Ulysse Schaller

We consider strongly coupled competitive elliptic systems of Gross-Pitaevskii type that arise in the study of two-component Bose-Einstein condensates, in general smooth bounded domains of $\mathbb{R}^N$, $N\geq 1$. As the coupling parameter…

Analysis of PDEs · Mathematics 2024-05-28 Christos Sourdis

Dendritic growth, and the formation of material microstructure in general, necessarily involves a wide range of length scales from the atomic up to sample dimensions. The phase field approach of Langer, enhanced by optimal asymptotic…

Materials Science · Physics 2015-06-25 Nigel Goldenfeld , Badrinarayan P. Athreya , Jonathan A. Dantzig

Structural analysis of self-catalyzed GaAs nanowires (NWs) grown on lithography-free oxide patterns is described with insight on their growth kinetics. Statistical analysis of templates and NWs in different phases of the growth reveals…

Mesoscale and Nanoscale Physics · Physics 2017-03-29 Eero Koivusalo , Teemu Hakkarainen , Mircea Guina

A perfect matching in an undirected graph $G=(V,E)$ is a set of vertex disjoint edges from $E$ that include all vertices in $V$. The perfect matching problem is to decide if $G$ has such a matching. Recently Rothvo{\ss} proved the striking…

Discrete Mathematics · Computer Science 2018-04-26 David Avis , David Bremner , Hans Raj Tiwary , Osamu Watanabe

The polymer model framework is a classical tool from statistical mechanics that has recently been used to obtain approximation algorithms for spin systems on classes of bounded-degree graphs; examples include the ferromagnetic Potts model…

Data Structures and Algorithms · Computer Science 2022-03-29 Andreas Galanis , Leslie Ann Goldberg , James Stewart

We consider an infinite-dimensional stochastic clustering model on $\mathbb{R}$. In discrete time, each point of a unit-intensity simple point process moves halfway toward either of its left or right neighbors, chosen uniformly at random.…

Probability · Mathematics 2026-03-10 Partha S. Dey , S. Rasoul Etesami , Aditya S. Gopalan

Three models from statistical physics can be analyzed by employing space-time determinantal processes: (1) crystal facets, in particular the statistical properties of the facet edge, and equivalently tilings of the plane, (2)…

Statistical Mechanics · Physics 2009-11-11 Herbert Spohn

The ability of different materials to display self-limiting growth has recently attracted enormous attention due to the importance of nanoscale materials in applications for catalysis, energy conversion, (opto)electronics, etc. Here, we…

We extend our 2+1 dimensional discrete growth model (PRE 79, 021125 (2009)) with conserved, local exchange dynamics of octahedra, describing surface diffusion. A roughening process was realized by uphill diffusion and curvature dependence.…

Statistical Mechanics · Physics 2010-05-14 Geza Odor , Bartosz Liedke , Karl-Heinz Heinig

Let P be a random $d$-dimensional 0/1-polytope with $n(d)$ vertices, and denote by $\phi_k(P)$ the \emph{$k$-face density} of $P$, i.e., the quotient of the number of $k$-dimensional faces of $P$ and $\binom{n(d)}{k+1}$. For each $k\ge 2$,…

Combinatorics · Mathematics 2007-05-23 Volker Kaibel

Given $\alpha \in (0, \infty)$ and $r \in (0, \infty)$, let ${\cal D}_{r, \alpha}$ be the disc of radius $r$ in the hyperbolic plane having curvature $-\alpha^2$. Consider the Poisson point process having uniform intensity density on ${\cal…

Probability · Mathematics 2021-01-01 Nikolaos Fountoulakis , Joseph Yukich

The epitaxial growth process of a high symmetry surface occurs because adatoms meet and nucleate new islands, that eventually coalesce and complete atomic layers. During multilayer growth, nucleation usually takes place on top of terraces…

Statistical Mechanics · Physics 2007-05-23 Paolo Politi , Claudio Castellano

State-of-the-art models for aerosol particle nucleation and growth from a cooling vapor primarily use a nodal method to numerically solve particle growth kinetics. In this method, particles that are smaller than the critical size are…

Computational Physics · Physics 2024-08-30 A. Khrabry , I. D. Kaganovich , S. Raman , E. Turkoz , D. Graves

Let $X$ be a normal projective variety of dimension $d$ over an algebraically closed field and $f$ an automorphism of $X$. Suppose that the pullback $f^*|_{\mathsf{N}^1(X)_\mathbf{R}}$ of $f$ on the real N\'eron--Severi space…

Algebraic Geometry · Mathematics 2026-05-14 Fei Hu , Chen Jiang

We introduce a broad class of spatial models to describe how spatially heterogeneous populations live, die, and reproduce. Individuals are represented by points of a point measure, whose birth and death rates can depend both on spatial…

Probability · Mathematics 2024-01-02 Alison M. Etheridge , Thomas G. Kurtz , Ian Letter , Peter L. Ralph , Terence Tsui Ho Lung

One-dimensional interacting particle systems, 1+1 random growth models, and two-dimensional directed polymers define 2d height fields. The KPZ universality conjecture posits that an appropriately scaled height function converges to a…

Probability · Mathematics 2022-07-21 Jinho Baik

Message passing Graph Neural Networks (GNNs) are known to be limited in expressive power by the 1-WL color-refinement test for graph isomorphism. Other more expressive models either are computationally expensive or need preprocessing to…

Machine Learning · Computer Science 2024-02-01 Mohammed Haroon Dupty , Yanfei Dong , Wee Sun Lee

Stochastic motion of a point -- known as Brownian motion -- has many successful applications in science, thanks to its scale invariance and consequent universal features such as Gaussian fluctuations. In contrast, the stochastic motion of a…

Statistical Mechanics · Physics 2011-08-11 Kazumasa A. Takeuchi , Masaki Sano , Tomohiro Sasamoto , Herbert Spohn