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The large N limit of a one-dimensional infinite chain of random matrices is investigated. It is found that in addition to the expected Kosterlitz--Thouless phase transition this model exhibits an infinite series of phase transitions at…

High Energy Physics - Theory · Physics 2009-07-09 A. Matytsin , P. Zaugg

The deconfined quantum critical point (DQCP) was originally proposed as a continuous transition between two spontaneous symmetry breaking phases in 2D spin-1/2 systems. While great efforts have been spent on the DQCP for 2D systems, both…

Strongly Correlated Electrons · Physics 2019-09-23 Rui-Zhen Huang , Da-Chuan Lu , Yi-Zhuang You , Zi Yang Meng , Tao Xiang

The hardcore model is a model of lattice gas systems which has received much attention in statistical physics, probability theory and theoretical computer science. It is the probability distribution over independent sets $I$ of a graph…

Computational Complexity · Computer Science 2010-06-01 Allan Sly

We study $C^{2}$ weakly order preserving circle maps with a flat interval. The main result of the paper is about a sharp transition from degenerate geometry to bounded geometry depending on the degree of the singularities at the boundary of…

Dynamical Systems · Mathematics 2015-06-04 Liviana Palmisano

We consider a stochastic model describing the spiking activity of a countable set of neurons spatially organized into a homogeneous tree of degree $d$, $d \geq 2$; the degree of a neuron is just the number of connections it has. Roughly,…

Probability · Mathematics 2022-05-17 A. M. B. Nascimento

We consider a slight modification of the frog model. For a given graph, each vertex has $\mathrm{Poisson}(\lambda)$ particles (or frogs). At time zero, only the particles at the origin are active, and all the other particles are sleeping.…

Probability · Mathematics 2026-01-27 Omer Angel , Daniel de la Riva , Jonathan Hermon , Yuliang Shi

We study the frog model with death on the biregular tree $\mathbb{T}_{d_1,d_2}$. Initially, there is a random number of awake and sleeping particles located on the vertices of the tree. Each awake particle moves as a discrete-time…

Probability · Mathematics 2020-06-04 Elcio Lebensztayn , Jaime Utria

In high-dimensional learning, models remain stable until they collapse abruptly once the sample size falls below a critical level. This instability is not algorithm-specific but a geometric mechanism: when the weakest Fisher eigendirection…

Machine Learning · Statistics 2025-11-26 William Hao-Cheng Huang

Consider a sequence (indexed by n) of Markov chains Z^n in R^d characterized by transition kernels that approximately (in n) depend only on the rescaled state n^{-1} Z^n. Subject to a smoothness condition, such a family can be closely…

Probability · Mathematics 2009-08-17 Kamil Szczegot

We study various classes of random processes defined on the regular tree $T_d$ that are invariant under the automorphism group of $T_d$. Most important ones are factor of i.i.d. processes (randomized local algorithms), branching Markov…

Probability · Mathematics 2015-07-28 Ágnes Backhausz , Balázs Szegedy

We study the evolution of graphs densifying by adding edges: Two vertices are chosen randomly, and an edge is (i) established if each vertex belongs to a tree; (ii) established with probability $p$ if only one vertex belongs to a tree;…

Probability · Mathematics 2024-09-10 P. L. Krapivsky

For $d\ge 3$ we construct a new coupling of the trace left by a random walk on a large $d$-dimensional discrete torus with the random interlacements on $\mathbb Z^d$. This coupling has the advantage of working up to macroscopic subsets of…

Probability · Mathematics 2014-12-01 Jiří Černý , Augusto Teixeira

We study a system of simple random walks on graphs, known as frog model. This model can be described as follows: There are active and sleeping particles living on some graph G. Each active particle performs a simple random walk with…

Probability · Mathematics 2019-03-05 O. S. M. Alves , F. P. Machado , S. Yu. Popov

We deal with a random graph model evolving in discrete time steps by duplicating and deleting the edges of randomly chosen vertices. We prove the existence of an a.s. asymptotic degree distribution, with streched exponential decay; more…

Probability · Mathematics 2014-11-10 Ágnes Backhausz , Tamás F. Móri

We consider the level-sets of continuous Gaussian fields on $\mathbb{R}^d$ above a certain level $-\ell\in \mathbb{R}$, which defines a percolation model as $\ell$ varies. We assume that the covariance kernel satisfies certain regularity,…

Probability · Mathematics 2021-06-15 Franco Severo

We study phase transitions and the nature of order in a class of classical generalized $O(N)$ nonlinear $\sigma$-models (NLS) constructed by minimally coupling pure NLS with additional degrees of freedom in the form of (i) Ising…

Statistical Mechanics · Physics 2015-12-23 Tirthankar Banerjee , Niladri Sarkar , Abhik Basu

We show that the contact process on a random $d$-regular graph initiated by a single infected vertex obeys the "cutoff phenomenon" in its supercritical phase. In particular, we prove that when the infection rate is larger than the critical…

Probability · Mathematics 2015-02-27 Steven Lalley , Wei Su

Distinguishing between continuous and first-order phase transitions is a major challenge in random discrete systems. We study the topic for events with recursive structure on Galton-Watson trees. For example, let $\mathcal{T}_1$ be the…

Probability · Mathematics 2022-08-05 Tobias Johnson

We obtain a representation of the free energy of an XY model on a fully connected graph with spins subjected to a random crystal field of strength $D$ and with random orientation $\alpha$. Results are obtained for an arbitrary probability…

Statistical Mechanics · Physics 2022-02-14 Sumedha , M. Barma

We present an approach for the detection of sharp change points (short-lived and persistent) in nonlinear and nonstationary dynamic systems under high levels of noise by tracking the local phase and amplitude synchronization among the…

Data Analysis, Statistics and Probability · Physics 2020-08-04 Ashif Sikandar Iquebal , Satish Bukkapatnam , Arun Srinivasa
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