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We study an inhomogeneous sparse random graph on [N] = {1, . . . , N } as introduced in a seminal paper by Bollobas, Janson and Riordan (2007): vertices have a type (here in a compact metric space S), and edges between different vertices…

Probability · Mathematics 2023-08-21 Luisa Andreis , Wolfgang König , Heide Langhammer , Robert I. A. Patterson

We introduce a cellular automaton model coupled with a transport equation for flows on graphs. The direction of the flow is described by a switching process where the switching probability dynamically changes according to the value of the…

Cellular Automata and Lattice Gases · Physics 2013-07-02 Pierre Degond , Michael Herty , Jian-Guo Liu

An intense activity is nowadays devoted to the definition of models capturing the properties of complex networks. Among the most promising approaches, it has been proposed to model these graphs via their clique incidence bipartite graphs.…

Discrete Mathematics · Computer Science 2021-03-09 Matthieu Latapy , Thi Ha Duong Phan , Christophe Crespelle , Thanh Qui Nguyen

We establish the existence of the phase transition in site percolation on pseudo-random $d$-regular graphs. Let $G=(V,E)$ be an $(n,d,\lambda)$-graph, that is, a $d$-regular graph on $n$ vertices in which all eigenvalues of the adjacency…

Combinatorics · Mathematics 2015-07-07 Michael Krivelevich

Hypergraphs are a generalization of graphs in which edges can connect any number of vertices. They allow the modeling of complex networks with higher-order interactions, and their spectral theory studies the qualitative properties that can…

Combinatorics · Mathematics 2021-12-01 Raffaella Mulas

The presented material continues the previous article (arxiv:1007.1059) and also is devoted to the equivalent conversion between the graphs. The examining of the transformation of the vertex graphs into the edge graphs (together with the…

General Mathematics · Mathematics 2012-10-24 Leonid Malinin , Natalia Malinina

Cross phenomena, representing responses of a system to external stimuli, are ubiquitous from quantum to macro scale. The Onsager theorem is often used to describe them, stating that the coefficient matrix of cross phenomena connecting the…

Materials Science · Physics 2023-03-28 Zi-Kui Liu

Reciprocal processes are acausal generalizations of Markov processes introduced by Bernstein in 1932. In the literature, a significant amount of attention has been focused on developing dynamical models for reciprocal processes. In this…

Machine Learning · Statistics 2016-05-16 Francesca Paola Carli

The empirical scaling law, wherein the total photoabsorption cross section depends on the single variable eta=(Q^2+m_0^2)/Lambda^2(W^2), provides empirical evidence for saturation in the sense of sigma_{gamma* p}(W^2,Q^2)/sigma_{gamma…

High Energy Physics - Phenomenology · Physics 2007-05-23 D. Schildknecht , M. Tentyukov , M. Kuroda , B. Surrow

We prove that any over-twist pattern is conjugate to an interval exchange transformation with bounded number of segments of isometry, restricted on one of its cycles. The bound is independent of the period and over-rotation number of the…

Dynamical Systems · Mathematics 2024-08-20 Sourav Bhattacharya

Simple models of irreversible dynamical processes such as Bootstrap Percolation have been successfully applied to describe cascade processes in a large variety of different contexts. However, the problem of analyzing non-typical…

Statistical Mechanics · Physics 2013-09-03 F. Altarelli , A. Braunstein , L. Dall'Asta , R. Zecchina

We offer a solution to a long-standing problem in the physics of networks, the creation of a plausible, solvable model of a network that displays clustering or transitivity -- the propensity for two neighbors of a network node also to be…

Statistical Mechanics · Physics 2009-08-13 M. E. J. Newman

The maxima and the minima of a randomly stopped sample of a random variable, $X$, together with two newly defined random variables that make $X$ into the maxima or minima of a randomly stopped sample of them, can be used to define…

Statistics Theory · Mathematics 2024-12-23 Jordi Valero , Josep Ginebra

A method for data-driven interpolatory model reduction is presented in this extended abstract. This framework enables the computation of the transfer function values at given interpolation points based on time-domain input-output data only,…

Systems and Control · Electrical Eng. & Systems 2020-05-12 Azka Muji Burohman , Bart Besselink , Jacquelien M. A. Scherpen , M. Kanat Camlibel

We study a class of quantum spin systems in the mean-field setting of the complete graph. For spin $S=\tfrac12$ the model is the Heisenberg ferromagnet, for general spin $S\in\tfrac12\mathbb{N}$ it has a probabilistic representation as a…

Mathematical Physics · Physics 2019-12-16 J. E. Björnberg

The mechanism of synchronization in the random Zaslavsky map is investigated. From the error dynamics of two particles, the structure of phase space was analyzed, and a transcritical bifurcation between a saddle and a stable fixed point was…

Chaotic Dynamics · Physics 2016-09-07 Dong-Uk Hwang , Inbo Kim , Sunghwan Rim , Chil-Min Kim , Young-Jai Park

The random antiferromagnetic spin-1/2 XX and XXZ chain is studied numerically for varying strength of the disorder, using exact diagonalization and stochastic series expansion methods. The spin-spin correlation function as well as the…

Strongly Correlated Electrons · Physics 2009-11-10 Nicolas laflorencie , Heiko Rieger , Anders W. Sandvik , Patrik Henelius

In this paper we study the cycle descent statistic on permutations. Several involutions on permutations and derangements are constructed. Moreover, we construct a bijection between negative cycle descent permutations and Callan perfect…

Combinatorics · Mathematics 2015-12-08 Jun Ma , Shimei Ma , Yeong-Nan Yeh , Zhu Xu

A general random graph evolution mechanism is defined. The evolution is a combination of the preferential attachment model and the interaction of N vertices (N>=3). A vertex in the graph is characterized by its degree and its weight. The…

Probability · Mathematics 2013-09-18 István Fazekas , Bettina Porvázsnyik

Probabilistic inferences distill knowledge from graphs to aid human make important decisions. Due to the inherent uncertainty in the model and the complexity of the knowledge, it is desirable to help the end-users understand the inference…

Social and Information Networks · Computer Science 2019-08-21 Chao Chen , Yifei Liu , Xi Zhang , Sihong Xie