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Erik I. Broman

Publications and source records attributed to Erik I. Broman.

At least 19 recordsLinked to original sources
arXiv2025

The Poisson stick model in hyperbolic space

In this paper we study the Poisson stick model in two dimensional hyperbolic space $\mathbb{H}^2,$ where the sticks all have length $L.$ Typically, percolation models in hyperbolic space undergo two phase transitions as the intensity $λ$ varies, namely the percolation phase transition and the uniqueness phase transition. For the Poisson stick model, the critical intensities at which these transitions occur will depend on $L$, and in this paper we study the asymptotic behavior of these critical points as $L\to \infty.$ Our main results show that the critical point for the percolation phase transition scales like $L^{-2},$ while the critical point for the uniqueness phase transition scales like $L^{-1}.$ Comparing these results to the analogous results in Euclidean space show that the behavior of the percolation phase transition is the same in these two settings, while the uniqueness phase transition scales differently.

math.PR↗
arXiv2024

Cover times of the massive random walk loop soup

We study cover times of subsets of ${\mathbb Z}^2$ by a two-dimensional massive random walk loop soup. We consider a sequence of subsets $A_n \subset {\mathbb Z}^2$ such that $|A_n| \to \infty$ and determine the distributional limit of their cover times ${\mathcal T}(A_n).$ We allow the killing rate $κ_n$ (or equivalently the ``mass'') of the loop soup to depend on the size of the set $A_n$ to be covered. In particular, we determine the limiting behavior of the cover times for inverse killing rates all the way up to $κ_n^{-1}=|A_n|^{1-8/(\log \log |A_n|)},$ showing that it can be described by a Gumbel distribution. Since a typical loop in this model will have length at most of order $κ_n^{-1/2}=|A_n|^{1/2},$ if $κ_n^{-1}$ exceeded $|A_n|,$ the cover times of all points in a tightly packed set $A_n$ (i.e. a square or close to a ball) would presumably be heavily correlated, complicating the analysis. Our result comes close to this extreme case.

math.PR↗
arXiv2021

Higher-dimensional stick percolation

We consider two cases of the so-called stick percolation model with sticks of length $L.$ In the first case, the orientation is chosen independently and uniformly, while in the second all sticks are oriented along the same direction. We study their respective critical values $λ_c(L)$ of the percolation phase transition, and in particular we investigate the asymptotic behavior of $λ_c(L)$ as $L\to \infty$ for both of these cases. In the first case we prove that $λ_c(L)\sim L^{-2}$ for any $d\geq 2,$ while in the second we prove that $λ_c(L)\sim L^{-1}$ for any $d\geq 2.$

math.PR↗
arXiv2019

The existence phase transition for scale invariant Poisson random fractal models

In this paper we study the existence phase transition of scale invariant random fractal models. We determine the exact value of the critical point of this phase transition for all models satisfying some weak assumptions. In addition, we show that for a large subclass, the fractal model is in the empty phase at the critical point. This subclass of models includes the scale invariant Poisson Boolean model and the Brownian loop soup. In contrast to earlier results in the literature, we do not need to restrict our attention to random fractal models generated by open sets.

math.PR↗
arXiv2018

Random cover times using the Poisson cylinder process

In this paper we deal with the classical problem of random cover times. We investigate the distribution of the time it takes for a Poisson process of cylinders to cover a set $A \subset \mathbb{R}^d.$ This Poisson process of cylinders is invariant under rotations, reflections and translations, and in addition we add a time component so that cylinders are "raining from the sky" at unit rate. Our main results concerns the asymptotic of this cover time as the set $A$ grows. If the set $A$ is discrete and well separated, we show convergence of the cover time to a Gumbel distribution. If instead $A$ has positive box dimension (and satisfies a weak additional assumption), we find the correct rate of convergence.

math.PR↗
arXiv2018

Poisson cylinders in hyperbolic space

We consider the Poisson cylinder model in $d$-dimensional hyperbolic space. We show that in contrast to the Euclidean case, there is a phase transition in the connectivity of the collection of cylinders as the intensity parameter varies. We also show that for any non-trivial intensity, the diameter of the collection of cylinders is infinite.

math.PR↗
arXiv2016

Phase transition and uniqueness of levelset percolation

The main purpose of this paper is to introduce and establish basic results of a natural extension of the classical Boolean percolation model (also known as the Gilbert disc model). We replace the balls of that model by a positive non-increasing attenuation function $l:(0,\infty) \to (0,\infty)$ to create the random field $Ψ(y)=\sum_{x\in η}l(|x-y|),$ where $η$ is a homogeneous Poisson process in ${\mathbb R}^d.$ The field $Ψ$ is then a random potential field with infinite range dependencies whenever the support of the function $l$ is unbounded. In particular, we study the level sets $Ψ_{\geq h}(y)$ containing the points $y\in {\mathbb R}^d$ such that $Ψ(y)\geq h.$ In the case where $l$ has unbounded support, we give, for any $d\geq 2,$ exact conditions on $l$ for $Ψ_{\geq h}(y)$ to have a percolative phase transition as a function of $h.$ We also prove that when $l$ is continuous then so is $Ψ$ almost surely. Moreover, in this case and for $d=2,$ we prove uniqueness of the infinite component of $Ψ_{\geq h}$ when such exists, and we also show that the so-called percolation function is continuous below the critical value $h_c$.

math.PR↗
arXiv2015

Stochastic Ordering of Infinite Geometric Galton-Watson Trees

We consider Galton-Watson trees with Geom$(p)$ offspring distribution. We let $T_{\infty}(p)$ denote such a tree conditioned on being infinite. We prove that for any $1/2\leq p_1 <p_2 \leq 1$, there exists a coupling between $T_{\infty}(p_1)$ and $T_{\infty}(p_2)$ such that ${\mathbb P}(T_{\infty}(p_1) \subseteq T_{\infty}(p_2))=1.$

math.PR↗
arXiv2014

Stochastic Ordering of Infinite Binomial Galton-Watson Trees

We consider Galton-Watson trees with ${\rm Bin}(d,p)$ offspring distribution. We let $T_{\infty}(p)$ denote such a tree conditioned on being infinite. For $d=2,3$ and any $1/d\leq p_1 <p_2 \leq 1$, we show that there exists a coupling between $T_{\infty}(p_1)$ and $T_{\infty}(p_2)$ such that ${\mathbb P}(T_{\infty}(p_1) \subseteq T_{\infty}(p_2))=1.$

math.PR↗
arXiv2013

Connectedness of Poisson cylinders in Euclidean space

We consider the Poisson cylinder model in ${\mathbb R}^d$, $d\ge 3$. We show that given any two cylinders ${\mathfrak c}_1$ and ${\mathfrak c}_2$ in the process, there is a sequence of at most $d-2$ other cylinders creating a connection between ${\mathfrak c}_1$ and ${\mathfrak c}_2$. In particular, this shows that the union of the cylinders is a connected set, answering a question appearing in a previous paper. We also show that there are cylinders in the process that are not connected by a sequence of at most $d-3$ other cylinders. Thus, the diameter of the cluster of cylinders equals $d-2$.

math.PR↗
arXiv2012

A stochastic model for virus growth in a cell population

A stochastic model for the growth of a virus in a cell population is introduced. The virus has two ways of spreading: either by allowing its host cell to live on and duplicate, or else by multiplying in large numbers within the host cell such that the host cell finally bursts and the viruses then have the chance to enter new uninfected host cells. The model, and in particular the probability of the virus population surviving, is analyzed using the theory of Markov processes together with a coupling argument. Our analysis shows that the optimal strategy of the virus (in terms of survival) is obtained when the virus has no effect on the host cell's life-cycle, in agreement with experimental data about real viruses.

q-bio.CB↗
arXiv2012

Coexistence and non-coexistence of Markovian viruses and their hosts

The possibility of coexistence of two competing populations is a classical question which dates back to the earliest `predator-prey' models. In this paper we study this question in the context of a model for the spread of a virus infection in a population of healthy cells. The infected cells may be seen as a population of `predators' and the healthy cells as a population of `prey'. We show that, depending on the parameters defining the model, there may or may not be coexistence of the two populations, and we give precise criteria for this.

math.PR↗
arXiv2012

Fat fractal percolation and k-fractal percolation

We consider two variations on the Mandelbrot fractal percolation model. In the k-fractal percolation model, the d-dimensional unit cube is divided in N^d equal subcubes, k of which are retained while the others are discarded. The procedure is then iterated inside the retained cubes at all smaller scales. We show that the (properly rescaled) percolation critical value of this model converges to the critical value of ordinary site percolation on a particular d-dimensional lattice as N tends to infinity. This is analogous to the result of Falconer and Grimmett that the critical value for Mandelbrot fractal percolation converges to the critical value of site percolation on the same d-dimensional lattice. In the fat fractal percolation model, subcubes are retained with probability p_n at step n of the construction, where (p_n) is a non-decreasing sequence with \prod p_n > 0. The Lebesgue measure of the limit set is positive a.s. given non-extinction. We prove that either the set of connected components larger than one point has Lebesgue measure zero a.s. or its complement in the limit set has Lebesgue measure zero a.s.

math.PR↗
arXiv2011

Exclusion Sensitivity of Boolean Functions

Recently the study of noise sensitivity and noise stability of Boolean functions has received considerable attention. The purpose of this paper is to extend these notions in a natural way to a different class of perturbations, namely those arising from running the symmetric exclusion process for a short amount of time. In this study, the case of monotone Boolean functions will turn out to be of particular interest. We show that for this class of functions, ordinary noise sensitivity and noise sensitivity with respect to the complete graph exclusion process are equivalent. We also show this equivalence with respect to stability. After obtaining these fairly general results, we study "exclusion sensitivity" of critical percolation in more detail with respect to medium-range dynamics. The exclusion dynamics, due to its conservative nature, is in some sense more physical than the classical i.i.d dynamics. Interestingly, we will see that in order to obtain a precise understanding of the exclusion sensitivity of percolation, we will need to describe how typical spectral sets of percolation diffuse under the underlying exclusion process.

math.PR↗
arXiv2010

Universal Behavior of Connectivity Properties in Fractal Percolation Models

Partially motivated by the desire to better understand the connectivity phase transition in fractal percolation, we introduce and study a class of continuum fractal percolation models in dimension d greater than or equal to 2. These include a scale invariant version of the classical (Poisson) Boolean model of stochastic geometry and (for d=2) the Brownian loop soup introduced by Lawler and Werner. The models lead to random fractal sets whose connectivity properties depend on a parameter lambda. In this paper we mainly study the transition between a phase where the random fractal sets are totally disconnected and a phase where they contain connected components larger than one point. In particular, we show that there are connected components larger than one point at the unique value of lambda that separates the two phases (called the critical point). We prove that such a behavior occurs also in Mandelbrot's fractal percolation in all dimensions d greater than or equal to 2. Our results show that it is a generic feature, independent of the dimension or the precise definition of the model, and is essentially a consequence of scale invariance alone. Furthermore, for d=2 we prove that the presence of connected components larger than one point implies the presence of a unique, unbounded, connected component.

math.PR↗
arXiv2008

Large-N Limit of Crossing Probabilities, Discontinuity, and Asymptotic Behavior of Threshold Values in Mandelbrot's Fractal Percolation Process

We study Mandelbrot's percolation process in dimension $d \geq 2$. The process generates random fractal sets by an iterative procedure which starts by dividing the unit cube $[0,1]^d$ in $N^d$ subcubes, and independently retaining or discarding each subcube with probability $p$ or $1-p$ respectively. This step is then repeated within the retained subcubes at all scales. As $p$ is varied, there is a percolation phase transition in terms of paths for all $d \geq 2$, and in terms of $(d-1)$-dimensional "sheets" for all $d \geq 3$. For any $d \geq 2$, we consider the random fractal set produced at the path-percolation critical value $p_c(N,d)$, and show that the probability that it contains a path connecting two opposite faces of the cube $[0,1]^d$ tends to one as $N \to \infty$. As an immediate consequence, we obtain that the above probability has a discontinuity, as a function of $p$, at $p_c(N,d)$ for all $N$ sufficiently large. This had previously been proved only for $d=2$ (for any $N \geq 2$). For $d \geq 3$, we prove analogous results for sheet-percolation. In dimension two, Chayes and Chayes proved that $p_c(N,2)$ converges, as $N \to \infty$, to the critical density $p_c$ of site percolation on the square lattice. Assuming the existence of the correlation length exponent $ν$ for site percolation on the square lattice, we establish the speed of convergence up to a logarithmic factor. In particular, our results imply that $p_c(N,2)-p_c=(\frac{1}{N})^{1/ν+o(1)}$ as $N \to \infty$, showing an interesting relation with near-critical percolation.

math.PR↗
arXiv2007

Stochastic domination for a hidden Markov chain with applications to the contact process in a randomly evolving environment

The ordinary contact process is used to model the spread of a disease in a population. In this model, each infected individual waits an exponentially distributed time with parameter 1 before becoming healthy. In this paper, we introduce and study the contact process in a randomly evolving environment. Here we associate to every individual an independent two-state, $\{0,1\},$ background process. Given $δ_0<δ_1,$ if the background process is in state $0,$ the individual (if infected) becomes healthy at rate $δ_0,$ while if the background process is in state $1,$ it becomes healthy at rate $δ_1.$ By stochastically comparing the contact process in a randomly evolving environment to the ordinary contact process, we will investigate matters of extinction and that of weak and strong survival. A key step in our analysis is to obtain stochastic domination results between certain point processes. We do this by starting out in a discrete setting and then taking continuous time limits.

math.PR↗