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Porous membranes are thin solid structures that allow the flow to pass through their tiny openings, called pores. Flow inertia may play a significant role in several filtration flows of natural and engineering interest. Here, we develop a…

The permeability of complex porous materials can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particular, the simulation convergence time scales poorly as…

An investigation of the effect of surface diffusion in random deposition model is made by analytical methods and reasoning. For any given site, the extent to which a particle can diffuse is decided by the morphology in the immediate…

Soft Condensed Matter · Physics 2011-12-14 Baisakhi Mal , Subhankar Ray , J. Shamanna

We consider the distribution of free path lengths, or the distance between consecutive bounces of random particles, in an n-dimensional rectangular box. If each particle travels a distance R, then, as R tends to infinity the free path…

Dynamical Systems · Mathematics 2018-11-14 Samuel Holmin , Pär Kurlberg , Daniel Månsson

When we represent a network of sensors in Euclidean space by a graph, there are two distances between any two nodes that we may consider. One of them is the Euclidean distance. The other is the distance between the two nodes in the graph,…

Networking and Internet Architecture · Computer Science 2009-06-10 Rodrigo S. C. Leao , Valmir C. Barbosa

We examine the geometry of the spaces between particles in diffusion-limited cluster aggregation, a numerical model of aggregating suspensions. Computing the distribution of distances from each point to the nearest particle, we show that it…

Statistical Mechanics · Physics 2009-11-07 R. M. L. Evans , M. D. Haw

Let $0<a<b<\infty$, and for each edge $e$ of $Z^d$ let $\omega_e=a$ or $\omega_e=b$, each with probability 1/2, independently. This induces a random metric $\dist_\omega$ on the vertices of $Z^d$, called first passage percolation. We prove…

Probability · Mathematics 2008-11-26 Itai Benjamini , Gil Kalai , Oded Schramm

The empirical measure of an interacting particle system is a purely atomic random probability measure. In the limit as the number of particles grows to infinity, we show for McKean-Vlasov systems with common noise that this measure becomes…

Probability · Mathematics 2025-09-01 Robert Alexander Crowell

Using a population of large-scale filaments extracted from an AREPO simulation of a Milky Way-like galaxy, we seek to understand the extent to which observed large-scale filament properties (with lengths $\gtrsim 100$ pc) can be explained…

Astrophysics of Galaxies · Physics 2020-01-01 Catherine Zucker , Rowan Smith , Alyssa Goodman

Consider the following random spatial network: in a large disk, construct a network using a stationary and isotropic Poisson line process of unit intensity. Connect pairs of points using the network, with initial / final segments of the…

Probability · Mathematics 2014-11-03 Wilfrid S. Kendall

We characterize the different morphologies adopted by a drop of liquid placed on two randomly oriented fibers, which is a first step toward understanding the wetting of fibrous networks. The present work reviews previous modeling for…

Fluid Dynamics · Physics 2015-08-31 Alban Sauret , François Boulogne , Beatrice Soh , Emilie Dressaire , Howard A. Stone

Networks that are fragmented into small disconnected components are prevalent in a large variety of systems. These include the secure communication networks of commercial enterprises, government agencies and illicit organizations, as well…

Disordered Systems and Neural Networks · Physics 2018-07-04 Eytan Katzav , Ofer Biham , Alexander K. Hartmann

In complex systems, responses to small perturbations are too diverse to predict how much they would be definitely, and then such diverse responses can be predicted in a probabilistic way. Here we study such a problem in scale-free networks,…

Statistical Mechanics · Physics 2007-05-23 J. -H. Kim , K. -I. Goh , B. Kahng , D. Kim

We present an exact mathematical framework able to describe site-percolation transitions in real multiplex networks. Specifically, we consider the average percolation diagram valid over an infinite number of random configurations where…

Physics and Society · Physics 2016-12-21 Ginestra Bianconi , Filippo Radicchi

Consider an improper Poisson line process, marked by positive speeds so as to satisfy a scale-invariance property (actually, scale-equivariance). The line process can be characterized by its intensity measure, which belongs to a…

Probability · Mathematics 2014-04-17 Wilfrid S. Kendall

Distributions of the resilience of transport networks are studied numerically, in particular the large-deviation tails. Thus, not only typical quantities like average or variance but the distributions over the (almost) full support can be…

Physics and Society · Physics 2015-06-18 Alexander K. Hartmann

We consider the problem of estimating the parameters of a $d$-dimensional rectified Gaussian distribution from i.i.d. samples. A rectified Gaussian distribution is defined by passing a standard Gaussian distribution through a one-layer ReLU…

Machine Learning · Computer Science 2019-09-20 Shanshan Wu , Alexandros G. Dimakis , Sujay Sanghavi

We study pore nucleation in a model membrane system, a freestanding polymer film. Nucleated pores smaller than a critical size close, while pores larger than the critical size grow. Holes of varying size were purposefully prepared in liquid…

Soft Condensed Matter · Physics 2017-01-04 Mark Ilton , Christian DiMaria , Kari Dalnoki-Veress

Suspensions of hard core spherical particles of diameter $D$ with inter-core connectivity range $\delta$ can be described in terms of random geometric graphs, where nodes represent the sphere centers and edges are assigned to any two…

Disordered Systems and Neural Networks · Physics 2017-09-12 Claudio Grimaldi

We characterize probabilities in Bayesian networks in terms of algebraic expressions called quasi-probabilities. These are arrived at by casting Bayesian networks as noisy AND-OR-NOT networks, and viewing the subnetworks that lead to a node…

Artificial Intelligence · Computer Science 2012-07-19 Lenhart Schubert