SearcharxivSearch

arXiv · 2310.07040

Degree-penalized contact processes

Abstract

We study degree-penalized contact processes on Galton-Watson trees (GW) and the configuration model. The model we consider is a modification of the usual contact process on a graph. In particular, each vertex can be either infected or healthy. When infected, each vertex heals at rate one. Also, when infected, a vertex $v$ with degree $d_v$ infects its neighboring vertex $u$ with degree $d_u$ with rate $\lambda/f(d_u, d_v)$ for some positive function $f$. In the case $f(d_u, d_v)=\max(d_u, d_v)^\mu$ for some $\mu>0$, the infection is slowed down to and from high degree vertices. This is in line with arguments used in social network science: people with many contacts do not have the time to infect their neighbors at the same rate as people with fewer contacts. We show that new phase transitions occur in terms of the parameter $\mu$ (at $1/2$) and the degree distribution $D$ of the GW tree. - When $\mu\ge 1$, the process goes extinct for all distributions $D$ for all sufficiently small $\lambda>0$; - When $\mu\in(1/2, 1)$, and the tail of $D$ weakly follows a power law with tail-exponent less than $1-\mu$, the process survives globally but not locally for all $\lambda$ small enough; - When $\mu\in(1/2, 1)$, and $\mathbb{E}[D^{1-\mu}]<\infty$, the process goes extinct almost surely, for all $\lambda$ small enough; - When $\mu<1/2$, and $D$ is heavier then stretched exponential with stretch-exponent $1-2\mu$, the process survives (locally) with positive probability for all $\lambda>0$. We also study the product case $f(x,y)=(xy)^\mu$. In that case, the situation for $\mu < 1/2$ is the same as the one described above, but $\mu\ge 1/2$ always leads to a subcritical contact process for small enough $\lambda>0$ on all graphs. Furthermore, for finite random graphs with prescribed degree sequences, we establish the corresponding phase transitions in terms of the length of survival.

Explore related subjects

Keep this discovery

BibTeXRIS

Zsolt Bartha, Júlia Komjáthy, Daniel Valesin. 2023-10-10. Degree-penalized contact processes. https://doi.org/10.1017/fms.2025.10144

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection

In this paper, we study averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection. First, we derive a general averaging principle applicable to such equations under minimal assumptions. Subsequently, since the coefficients of the obtained averaged equation still depend on the small scaling parameter $\e$, we impose either periodic or asymptotic conditions on the coefficients, thereby obtain two distinct averaged equations whose coefficients are independent of $\e$ and establish two averaging principles. Stopping times and Khasminskii's time discretization schemes play an important role. Finally, a concrete example is provided to illustrate the applicability and validity of the theoretical results.

math.PR

Spectral properties of Random Matrices

We give the theoretical foundations of random matrix theory through the definitions of a random matrix, a random probability measure and the corresponding empirical spectral distribution. The technical tool we use is the Stieltjes transform method through which we prove optimal convergence of the empirical spectral distribution of random sample covariance matrices to the deterministic Marchenko-Pastur distribution. We also give new results about the rigidity of the eigenvalues of this random sample covariance matrix and the rate of their convergence. We then define the Dyson equation method to prove new local laws about a random matrix model that interpolates between the Marchenko-Pastur distribution, the elliptical law and the circular law. Through our work these local laws can be considered universal.

math.PR

Moments approach for the elephant random walk

We discuss the method of moments for the one-dimensional elephant random walk (ERW). We first derive a differential recurrence relation for the characteristic function of the ERW, which yields a corresponding system of recurrence relations for its moments. We then obtain asymptotic approximations for the moments in each of the three parameter regimes of the ERW. Finally, by establishing the convergence of the moments and verifying the corresponding moment-determinacy conditions, we identify the limiting distributions of the ERW in each regime.

math.PR