arXiv subjects

Raluca M. Balan

Publications and source records attributed to Raluca M. Balan.

At least 37 records · Page 2Linked to original sources

arXiv2022

Central limit theorems for heat equation with time-independent noise: the regular and rough cases

In this article, we investigate the asymptotic behaviour of the spatial integral of the solution to the parabolic Anderson model with time independent noise in dimension $d\geq 1$, as the domain of the integral becomes large. We consider 3 cases: (a) the case when the noise has an integrable covariance function; (b) the case when the covariance of the noise is given by the Riesz kernel; (c) the case of the rough noise, i.e. fractional noise with index $H \in (\frac{1}{4},\frac{1}{2})$ in dimension $d=1$. In each case, we identify the order of magnitude of the variance of the spatial integral, we prove a quantitative central limit theorem for the normalized spatial integral by estimating its total variation distance to a standard normal distribution, and we give the corresponding functional limit result.

math.PR↗

arXiv2022

The hyperbolic Anderson model: Moment estimates of the Malliavin derivatives and applications

In this article, we study the hyperbolic Anderson model driven by a space-time \emph{colored} Gaussian homogeneous noise with spatial dimension $d=1,2$. Under mild assumptions, we provide $L^p$-estimates of the iterated Malliavin derivative of the solution in terms of the fundamental solution of the wave solution. To achieve this goal, we rely heavily on the \emph{Wiener chaos expansion} of the solution. Our first application are \emph{quantitative central limit theorems} for spatial averages of the solution to the hyperbolic Anderson model, where the rates of convergence are described by the total variation distance. These quantitative results have been elusive so far due to the temporal correlation of the noise blocking us from using the Itô calculus. A \emph{novel} ingredient to overcome this difficulty is the \emph{second-order Gaussian Poincaré inequality} coupled with the application of the aforementioned $L^p$-estimates of the first two Malliavin derivatives. Besides, we provide the corresponding functional central limit theorems. As a second application, we establish the absolute continuity of the law for the hyperbolic Anderson model. The $L^p$-estimates of Malliavin derivatives are crucial ingredients to verify a local version of Bouleau-Hirsch criterion for absolute continuity. Our approach substantially simplifies the arguments for the one-dimensional case, which has been studied in the recent work by Balan, Quer-Sardanyons and Song (2019).

math.PR↗

arXiv2022

Spatial integral of the solution to hyperbolic Anderson model with time-independent noise

In this article, we study the asymptotic behavior of the spatial integral of the solution to the hyperbolic Anderson model in dimension $d\leq 2$, as the domain of the integral gets large (for fixed time $t$). This equation is driven by a spatially homogeneous Gaussian noise, whose covariance function is either integrable, or is given by the Riesz kernel. The novelty is that the noise does not depend on time, which means that Itô's martingale theory for stochastic integration cannot be used. Using a combination of Malliavin calculus with Stein's method, we show that with proper normalization and centering, the spatial integral of the solution converges to a standard normal distribution, by estimating the speed of this convergence in the total variation distance. We also prove the corresponding functional limit theorem for the spatial integral process.

math.PR↗

arXiv2021

Exact asymptotics of the stochastic wave equation with time-independent noise

In this article, we study the stochastic wave equation in all dimensions $d\leq 3$, driven by a Gaussian noise $\dot{W}$ which does not depend on time. We assume that either the noise is white, or the covariance function of the noise satisfies a scaling property similar to the Riesz kernel. The solution is interpreted in the Skorohod sense using Malliavin calculus. We obtain the exact asymptotic behaviour of the $p$-th moment of the solution either when the time is large or when $p$ is large. For the critical case, that is the case when $d=3$ and the noise is white, we obtain the exact transition time for the second moment to be finite.

math.PR↗

arXiv2021

Stratonovich solution for the wave equation

In this article, we construct a Stratonovich solution for the stochastic wave equation in spatial dimension $d \leq 2$, with time-independent noise and linear term $σ(u)=u$ multiplying the noise. The noise is spatially homogeneous and its spectral measure satisfies an integrability condition which is stronger than Dalang's condition. We give a probabilistic representation for this solution, similar to the Feynman-Kac-type formula given in Dalang, Mueller and Tribe (2008) for the solution of the stochastic wave equation with spatially homogeneous Gaussian noise, that is white in time. We also give the chaos expansion of the Stratonovich solution and we compare it with the chaos expansion of the Skorohod solution from Balan, Chen and Chen (2020).

math.PR↗

arXiv2019

Weak convergence and tightness of probability measures in an abstract Skorohod space

In this article, we introduce the space $D([0,1];D)$ of functions defined on $[0,1]$ with values in the Skorohod space $D$, which are right-continuous and have left limits with respect to the $J_1$ topology. This space is equipped with the Skorohod-type distance introduced in Whitt (1980). Following the classical approach of Billingsley (1968, 1999), we give several criteria for tightness of probability measures on this space, by characterizing the relatively compact subsets of this space. In particular, one of these criteria has been used in the recent article Balan and Saidani (2018) for proving the existence of a $D$-valued $α$-stable Lévy motion. Finally, we give a criterion for weak convergence of random elements in $D([0,1];D)$, and a criterion for the existence of a process with sample paths in $D([0,1];D)$ based on its finite-dimensional distributions.

math.PR↗

arXiv2019

Existence of density for the stochastic wave equation with space-time homogeneous Gaussian noise

In this article, we consider the stochastic wave equation on $\mathbb{R}_{+} \times \mathbb{R}$, driven by a linear multiplicative space-time homogeneous Gaussian noise whose temporal and spatial covariance structures are given by locally integrable functions $γ$ (in time) and $f$ (in space), which are the Fourier transforms of tempered measures $ν$ on $\mathbb{R}$, respectively $μ$ on $\mathbb{R}$. Our main result shows that the law of the solution $u(t,x)$ of this equation is absolutely continuous with respect to the Lebesgue measure.

math.PR↗

arXiv2018

A gentle introduction to SPDEs: the random field approach

These notes constitute the basis for the lectures given by the author at Centre de recherches mathématiques (CRM) at Université de Montreal, as part of the thematic semester on "Mathematical challenges in many-body physics and quantum information" (September-December 2018). They are intended for researchers in mathematics who have a background (and an interest) in probability theory, but may not be familiar with the area of stochastic analysis, and in particular with stochastic partial differential equations (SPDEs). Their goal is to give a brief and concise introduction to the study of SPDEs using the random field approach, an area which has been expanding rapidly in the last 30 years, after the publication of John Walsh's lecture notes in 1986. These notes do not survey all the developments in this area, but have the rather modest goal of introducing the readers to the basic ideas, and (hopefully) spark their interest to learn more about this subject.

math.PR↗

arXiv2018

Stable Lévy motion with values in the Skorokhod space: construction and approximation

In this article, we introduce an infinite-dimensional analogue of the $α$-stable Lévy motion, defined as a Lévy process $Z=\{Z(t)\}_{t \geq 0}$ with values in the space $\mathbb{D}$ of càdlàg functions on $[0,1]$, equipped with Skorokhod's $J_1$ topology. For each $t \geq 0$, $Z(t)$ is an $α$-stable process with sample paths in $\mathbb{D}$, denoted by $\{Z(t,s)\}_{s\in [0,1]}$. Intuitively, $Z(t,s)$ gives the value of the process $Z$ at time $t$ and location $s$ in space. This process is closely related to the concept of regular variation for random elements in $\mathbb{D}$ introduced in de Haan and Lin (2001) and Hult and Lindskog (2005). We give a construction of $Z$ based on a Poisson random measure, and we show that $Z$ has a modification whose sample paths are càdlàg functions on $[0,\infty)$ with values in $\mathbb{D}$. Finally, we prove a functional limit theorem which identifies the distribution of this modification as the limit of the partial sum sequence $\{S_n(t)=\sum_{i=1}^{[nt]}X_i\}_{t\geq 0}$, suitably normalized and centered, associated to a sequence $(X_i)_{i\geq 1}$ of i.i.d. regularly varying elements in $\mathbb{D}$.

math.PR↗

arXiv2018

Hölder continuity for the Parabolic Anderson Model with space-time homogeneous Gaussian noise

In this article, we consider the Parabolic Anderson Model with constant initial condition, driven by a space-time homogeneous Gaussian noise, with general covariance function in time and spatial spectral measure satisfying Dalang's condition. First, we prove that the solution (in the Skorohod sense) exists and is continuous in $L^p(Ω)$. Then, we show that the solution has a modification whose sample paths are Hölder continuous in space and time, with optimal exponents, and under the minimal condition on the spatial spectral measure of the noise (which is the same as the condition encountered in the case of the white noise in time). This improves similar results which were obtained in Hu, Huang, Nualart and Tindel (2015), and Song (2017) under more restrictive conditions, and with sub-optimal exponents for Hölder continuity.

math.PR↗

arXiv2018

Asymptotic theory for longitudinal data with missing responses adjusted by inverse probability weights

In this article, we propose a new method for analyzing longitudinal data which contain responses that are missing at random. This method consists in solving the generalized estimating equation (GEE) of Liang and Zeger (1986) in which the incomplete responses are replaced by values adjusted using the inverse probability weights proposed in Yi, Ma and Carroll (2012). We show that the root estimator is consistent and asymptotically normal, essentially under the some conditions on the marginal distribution and the surrogate correlation matrix as those presented in Xie and Yang (2003) in the case of complete data, and under minimal assumptions on the missingness probabilities. This method is applied to a real-life dataset taken from Sommer, Katz and Tarwotjo (1984), which examines the incidence of respiratory disease in a sample of 250 pre-school age Indonesian children which were examined every 3 months for 18 months, using as covariates the age, gender, and vitamin A deficiency.

math.ST↗

arXiv2017

Hyperbolic Anderson Model with space-time homogeneous Gaussian noise

In this article, we study the stochastic wave equation in arbitrary spatial dimension $d$, with a multiplicative term of the form $σ(u)=u$, also known in the literature as the Hyperbolic Anderson Model. This equation is perturbed by a general Gaussian noise, which is homogeneous in both space and time. We prove the existence and uniqueness of a solution of this equation (in the Skorohod sense) and the Hölder continuity of its sample paths, under the same respective conditions on the spatial spectral measure of the noise as in the case of the white noise in time, regardless of the temporal covariance function of the noise.

math.PR↗

arXiv2017

Second order Lyapunov exponents for parabolic and hyperbolic Anderson models

In this article, we consider the hyperbolic and parabolic Anderson models in arbitrary space dimension $d$, with constant initial condition, driven by a Gaussian noise which is white in time. We consider two spatial covariance structures: (i) the Fourier transform of the spectral measure of the noise is a non-negative locally-integrable function; (ii) $d=1$ and the noise is a fractional Brownian motion in space with index $1/4<H<1/2$. In both cases, we show that there is striking similarity between the Laplace transforms of the second moment of the solutions to these two models. Building on this connection and the recent powerful results of Huang, Le and Nualart (2015) for the parabolic model, we compute the second order (upper) Lyapunov exponent for the hyperbolic model. In case (i), when the spatial covariance of the noise is given by the Riesz kernel, we present a unified method for calculating the second order Lyapunov exponents for the two models.

math.PR↗

arXiv2016

Parabolic Anderson Model with space-time homogeneous Gaussian noise and rough initial condition

In this article, we study the Parabolic Anderson Model driven by a space-time homogeneous Gaussian noise on $\mathbb{R}_{+} \times \mathbb{R}^d$, whose covariance kernels in space and time are locally integrable non-negative functions, which are non-negative definite (in the sense of distributions). We assume that the initial condition is given by a signed Borel measure on $\mathbb{R}^d$, and the spectral measure of the noise satisfies Dalang's (1999) condition. Under these conditions, we prove that this equation has a unique solution, and we investigate the magnitude of the $p$-th moments of the solution, for any $p \geq 2$. In addition, we show that this solution has a Hölder continuous modification with the same regularity and under the same condition as in the case of the white noise in time, regardless of the temporal covariance function of the noise.

math.PR↗

arXiv2016

Malliavin differentiability of solutions of SPDEs with Lévy white noise

In this article, we consider a stochastic partial differential equation (SPDE) driven by a Lévy white noise, with Lipschitz multiplicative term $σ$. We prove that under some conditions, this equation has a unique random field solution. These conditions are verified by the stochastic heat and wave equations. We introduce the basic elements of Malliavin calculus with respect to the compensated Poisson random measure associated with the Lévy white noise. If $σ$ is affine, we prove that the solution is Malliavin differentiable and its Malliavin derivative satisfies a stochastic integral equation.

math.PR↗

arXiv2016

Intermittency for the Hyperbolic Anderson Model with rough noise in space

In this article, we consider the stochastic wave equation on the real line driven by a linear multiplicative Gaussian noise, which is white in time and whose spatial correlation corresponds to that of a fractional Brownian motion with Hurst index $H\in (\frac14,\frac12)$. Initial data are assumed to be constant. First, we prove that this equation has a unique solution (in the Skorohod sense) and obtain an exponential upper bound for the $p$-th moment of the solution, for any $p\geq 2$. Condition $H>\frac14$ turns out to be necessary for the existence of solution. Secondly, we show that this solution coincides with the one obtained by the authors in a recent publication, in which the solution is interpreted in the Itô sense. Finally, we prove that the solution of the equation in the Skorohod sense is weakly intermittent.

math.PR↗

arXiv2016

Intermittency for the wave and heat equations with fractional noise in time

In this article, we consider the stochastic wave and heat equations driven by a Gaussian noise which is spatially homogeneous and behaves in time like a fractional Brownian motion with Hurst index $H>1/2$. The solutions of these equations are interpreted in the Skorohod sense. Using Malliavin calculus techniques, we obtain an upper bound for the moments of order $p\geq2$ of the solution. In the case of the wave equation, we derive a Feynman-Kac-type formula for the second moment of the solution, based on the points of a planar Poisson process. This is an extension of the formula given by Dalang, Mueller and Tribe [Trans. Amer. Math. Soc. 360 (2008) 4681-4703], in the case $H=1/2$, and allows us to obtain a lower bound for the second moment of the solution. These results suggest that the moments of the solution grow much faster in the case of the fractional noise in time than in the case of the white noise in time.

math.PR↗

arXiv2016

SPDEs with rough noise in space: Hölder continuity of the solution

We consider the stochastic wave and heat equations with affine multiplicative Gaussian noise which is white in time and behaves in space like the fractional Brownian motion with index $H \in (\frac14,\frac12)$. The existence and uniqueness of the solution to these equations has been proved recently by the authors. In the present note we show that these solutions have modifications which are Hölder continuous in space of order smaller than $H$, and Hölder continuous in time of order smaller than $γ$, where $γ=H$ for the wave equation and $γ=H/2$ for the heat equation.

math.PR↗