133 research outputs found
Joint distribution of the process and its sojourn time for pseudo-processes governed by high-order heat equation
Consider the high-order heat-type equation for an integer and introduce the related
Markov pseudo-process . In this paper, we study the sojourn
time in the interval up to a fixed time for this
pseudo-process. We provide explicit expressions for the joint distribution of
the couple
On the most visited sites of planar Brownian motion
Let (B_t : t > 0) be a planar Brownian motion and define gauge functions
for . If we show that
almost surely there exists a point x in the plane such that , but if almost surely simultaneously for all . This resolves a longstanding open
problem posed by S.,J. Taylor in 1986
Fluctuations of the Total Number of Critical Points of Random Spherical Harmonics
We determine the asymptotic law for the fluctuations of the total number of
critical points of random Gaussian spherical harmonics in the high degree
limit. Our results have implications on the sophistication degree of an
appropriate percolation process for modelling nodal domains of eigenfunctions
on generic compact surfaces or billiards
Joint distribution of the process and its sojourn time on the positive half-line for pseudo-processes governed by high-order heat equation.
Consider the high-order heat-type equation ∂u/∂t = ±∂Nu/∂xN for an integer N > 2 and introduce the related Markov pseudo-process (X(t))t≥0. In this paper, we study the sojourn time T(t) in the interval [0, +∞) up to a fixed time t for this pseudo-process. We provide explicit expressions for the joint distribution of the couple (T(t),X(t))
On the Correlation of Critical Points and Angular Trispectrum for Random Spherical Harmonics
We prove a Central Limit Theorem for the Critical Points of Random Spherical
Harmonics, in the High-Energy Limit. The result is a consequence of a deeper
characterizations of the total number of critical points, which are shown to be
asymptotically fully correlated with the sample trispectrum, i.e., the integral
of the fourth Hermite polynomial evaluated on the eigenfunctions themselves. As
a consequence, the total number of critical points and the nodal length are
fully correlated for random spherical harmonics, in the high-energy limit
Entrance and sojourn times for Markov chains. Application to -random walks
In this paper, we provide a methodology for computing the probability
distribution of sojourn times for a wide class of Markov chains. Our
methodology consists in writing out linear systems and matrix equations for
generating functions involving relations with entrance times. We apply the
developed methodology to some classes of random walks with bounded
integer-valued jumps.Comment: 30 page
A quantitative central limit theorem for the Euler–Poincaré characteristic of random spherical eigenfunctions.
We establish here a quantitative central limit theorem (in Wasserstein distance) for the Euler–Poincaré characteristic of excursion sets of random spherical eigenfunctions in dimension 2. Our proof is based upon a decomposition of the Euler–Poincaré characteristic into different Wiener-chaos components: we prove that its asymptotic behaviour is dominated by a single term, corresponding to the chaotic component of order two. As a consequence, we show how the asymptotic dependence on the threshold level u is fully degenerate, that is, the Euler–Poincaré characteristic converges to a single random variable times a deterministic function of the threshold. This deterministic function has a zero at the origin, where the variance is thus asymptotically of smaller order. We discuss also a possible unifying framework for the Lipschitz–Killing curvatures of the excursion sets for Gaussian spherical harmonics
Joint distribution of the process and its sojourn time in a half-line for pseudo-processes driven by a high-order heat-type equation.
Let (X(t))t≥0 be the pseudo-process driven by the high-order heat-type equation ∂u = ± ∂Nu , ∂t ∂xN
where N is an integer greater than 2. We consider the sojourn time spent by (X(t))t≥0 in [a,+∞) (a ∈ R), up to a fixed time t > 0: Ta(t) = 0t 1l[a,+∞)(X(s)) ds. The purpose of this paper is to explicit the joint pseudo-distribution of the vector (Ta(t),X(t)) when the pseudo-process starts at a point x ∈ R at time 0. The method consists in solving a boundary value problem satisfied by the Laplace transform of the aforementioned distribution
- …