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We study a large class of Bernoulli percolation models on random lattices of the half- plane, obtained as local limits of uniform planar triangulations or quadrangulations. We first compute the exact value of the site percolation threshold…

Probability · Mathematics 2015-12-21 Loïc Richier

We define the model of two-dimensional random interlacements using simple random walk trajectories conditioned on never hitting the origin, and then obtain some properties of this model. Also, for random walk on a large torus conditioned on…

Probability · Mathematics 2019-05-28 Francis Comets , Serguei Popov , Marina Vachkovskaia

We study the high-dimensional properties of an invading front in a disordered medium with random pinning forces. We concentrate on interfaces described by bounded slope models belonging to the quenched KPZ universality class. We find a…

Statistical Mechanics · Physics 2009-10-30 Omri Gat , Zeev Olami

Deep neural networks (DNNs) have gained prominence in various applications, such as classification, recognition, and prediction, prompting increased scrutiny of their properties. A fundamental attribute of traditional DNNs is their…

Machine Learning · Computer Science 2023-08-15 Roman Garaev , Bader Rasheed , Adil Khan

The study of interdependent networks, and in particular the robustness on networks, has attracted considerable attention. Recent studies mainly assume that the dependence is fully interdependent. However, targeted attack for partially…

Data Analysis, Statistics and Probability · Physics 2015-05-30 Gao-Gao Dong , Jian-Xi Gao , Li-Xin Tian , Rui-Jin Du , Ying-Huan He

In this work, we present a new algorithm to approximate the percolation centrality of every node in a graph. Such a centrality measure quantifies the importance of the vertices in a network during a contagious process. In this paper, we…

Social and Information Networks · Computer Science 2024-09-04 Antonio Cruciani

We model the isotropic depinning transition of a domain-wall using a two dimensional Ginzburg-Landau scalar field instead of a directed elastic string in a random media. An exact algorithm accurately targets both the critical depinning…

Disordered Systems and Neural Networks · Physics 2023-11-10 Alejandro B. Kolton , Ezequiel E. Ferrero , Alberto Rosso

Explosive percolation (EP) has received significant research attention due to its rich and anomalous phenomena near criticality. In our recent study [Phys. Rev. Lett. 130, 147101 (2023)], we demonstrated that the correct critical behaviors…

Statistical Mechanics · Physics 2024-09-20 Ming Li , Junfeng Wang , Youjin Deng

Recent research on finding important intermediate nodes in a network suspected to contain criminal activity is highly dependent on network centrality values. Betweenness centrality, for example, is widely used to rank the nodes that act as…

Social and Information Networks · Computer Science 2016-01-06 Pritheega Magalingam , Stephen Davis , Asha Rao

Random planar graphs appear in a variety of context and it is important for many different applications to be able to characterize their structure. Local quantities fail to give interesting information and it seems that path-related…

Physics and Society · Physics 2017-09-28 Benjamin Lion , Marc Barthelemy

A number of recent experimental measurements suggest the possibility of a breakdown of lepton ($\ell$) universality in exclusive $b \to c \ell \nu_\ell$ semileptonic meson decays. We analyze the full differential decay rates for several…

High Energy Physics - Phenomenology · Physics 2018-08-29 Thomas D. Cohen , Henry Lamm , Richard F. Lebed

We study analytically the dynamics of two-dimensional rectangular lattices with periodic boundary conditions. We consider anisotropic initial data supported on one low-frequency Fourier mode. We show that, in the continuous approximation,…

Dynamical Systems · Mathematics 2021-04-23 Matteo Gallone , Stefano Pasquali

We develop a mean-field theory of dropout as a perturbation of critical signal propagation at the edge of chaos. Dropout shifts the perfect-alignment fixed point, making the depth scale for information propagation finite even at critical…

Machine Learning · Computer Science 2026-05-22 Lucas Fernandez Sarmiento

We consider the transport of non-interacting electrons on two- and three-dimensional random Voronoi-Delaunay lattices. It was recently shown that these topologically disordered lattices feature strong disorder anticorrelations between the…

Disordered Systems and Neural Networks · Physics 2015-12-01 Martin Puschmann , Philipp Cain , Michael Schreiber , Thomas Vojta

Betweenness centrality is essential in complex network analysis; it characterizes the importance of nodes and edges in networks. It is a crucial problem that exactly computes the betweenness centrality in large networks faster, which…

Computational Engineering, Finance, and Science · Computer Science 2023-06-22 Yelai Feng , Huaixi Wang

We study the transfer of adversarial robustness of deep neural networks between different perturbation types. While most work on adversarial examples has focused on $L_\infty$ and $L_2$-bounded perturbations, these do not capture all types…

Machine Learning · Computer Science 2019-05-06 Daniel Kang , Yi Sun , Tom Brown , Dan Hendrycks , Jacob Steinhardt

Recent work in percolation has led to exact solutions for the site and bond critical thresholds of many new lattices. Here we show how these results can be extended to other classes of graphs, significantly increasing the number and variety…

Disordered Systems and Neural Networks · Physics 2009-11-11 Robert M. Ziff , Christian R. Scullard

The site and bond percolation problems are conventionally studied on (hyper)cubic lattices, which afford straightforward numerical treatments. The recent implementation of efficient simulation algorithms for high-dimensional systems now…

Statistical Mechanics · Physics 2021-06-14 Yi Hu , Patrick Charbonneau

Robustness and counterfactual bias are usually evaluated on a test dataset. However, are these evaluations robust? If the test dataset is perturbed slightly, will the evaluation results keep the same? In this paper, we propose a "double…

Computation and Language · Computer Science 2021-04-13 Chong Zhang , Jieyu Zhao , Huan Zhang , Kai-Wei Chang , Cho-Jui Hsieh

We study the tolerance of random networks to intentional attack, whereby a fraction p of the most connected sites is removed. We focus on scale-free networks, having connectivity distribution of P(k)~k^(-a) (where k is the site…

Disordered Systems and Neural Networks · Physics 2009-10-31 Reuven Cohen , Keren Erez , Daniel ben-Avraham , Shlomo Havlin