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We study deviation probabilities for the number of high positioned particles in branching Brownian motion, and confirm a conjecture of Derrida and Shi (2016). We also solve the corresponding problem for the two-dimensional discrete Gaussian…

Probability · Mathematics 2019-08-22 Elie Aïdékon , Yueyun Hu , Zhan Shi

Let $W$ denote the Brownian motion. For any exponentially bounded Borel function $g$ the function $u$ defined by $u(t,x)= \mathbb{E}[g(x{+}\sigma W_{T-t})]$ is the stochastic solution of the backward heat equation with terminal condition…

Probability · Mathematics 2019-02-04 Antti Luoto

Diffusion with stochastic transport is investigated here when the random driving process is a very general Gaussian process, including Fractional Brownian motion. The purpose is the comparison with a deterministic PDE, which in certain…

Probability · Mathematics 2026-04-20 Franco Flandoli , Francesco Russo

Let $(\lambda_k)$ be a strictly increasing sequence of positive numbers such that $\sum_{k=1}^{\infty} \frac{1}{\lambda_k} < \infty.$ Let $f $ be a bounded smooth function and denote by $u= u^f$ the bounded classical solution to $u(x) -…

Probability · Mathematics 2022-10-13 Emanuele Dolera , Enrico Priola

The Pearson family of ergodic diffusions with a quadratic diffusion coefficient and a linear force are characterized by explicit dynamics of their integer moments and by explicit relaxation spectral properties towards their steady state.…

Statistical Mechanics · Physics 2023-08-14 Cecile Monthus

We consider extended slow-fast systems of N interacting diffusions. The typical behavior of the empirical density is described by a nonlinear McKean-Vlasov equation depending on , the scaling parameter separating the time scale of the slow…

Analysis of PDEs · Mathematics 2021-08-09 Julien Barré , Cedric Bernardin , Raphaël Chétrite , Yash Chopra , Mauro Mariani

In this paper, we study the rate distortion function of the i.i.d sequence of multiplications of a Bernoulli $p$ random variable and a gaussian random variable $\sim N(0,1)$. We use a new technique in the derivation of the lower bound in…

Information Theory · Computer Science 2016-11-15 Cheng Chang

We construct stochastic gradient flows on the $2$-Wasserstein space $\mathcal P_2$ over $\mathbb R^d$ for energy functionals of the type $W_F(\rho d x)=\int_{\mathbb R^d}F(x,\rho(x))d x$. The functions $F$ and $\partial_2 F$ are assumed to…

Probability · Mathematics 2026-04-29 Panpan Ren , Michael Röckner , Feng-Yu Wang , Simon Wittmann

We consider a class of continuous time Markov chains on a compact metric space that admit an invariant measure strictly positive on open sets together with absorbing states. We prove the joint large deviation principle for the empirical…

Probability · Mathematics 2015-12-04 Giada Basile , Lorenzo Bertini

Let $(X,d)$ be a geodesic Gromov-hyperbolic space, $o \in X$ a basepoint and $\mu$ a countably supported non-elementary probability measure on $\operatorname{Isom}(X)$. Denote by $z_n$ the random walk on $X$ driven by the probability…

Probability · Mathematics 2022-03-15 Richard Aoun , Pierre Mathieu , Cagri Sert

The large deviations principle for the empirical measure for both continuous and discrete time Markov processes is well known. Various expressions are available for the rate function, but these expressions are usually as the solution to a…

Probability · Mathematics 2015-06-22 Paul Dupuis , Yufei Liu

Using analysis for 2-admissible functions in weighted Sobolev spaces and stochastic calculus for possibly degenerate symmetric elliptic forms, we construct weak solutions to a wide class of stochastic differential equations starting from an…

Probability · Mathematics 2016-11-16 Jiyong Shin , Gerald Trutnau

The area enclosed by the two-dimensional Brownian motion in the plane was studied by L\'evy, who found the characteristic function and probability density of this random variable. For other planar processes, in particular ergodic diffusions…

Statistical Mechanics · Physics 2023-10-24 Johan du Buisson , Thamu D. P. Mnyulwa , Hugo Touchette

In this paper we give a central limit theorem for the weighted quadratic variations process of a two-parameter Brownian motion. As an application, we show that the discretized quadratic variations $\sum_{i=1}^{[n s]} \sum_{j=1}^{[n t]} |…

Probability · Mathematics 2008-01-22 Anthony Réveillac

We perform rescaled range analysis upon the signals measured by Dual Particle Dynamical Analyzer in gas-liquid two-phase turbulent jets. A novel rescaled range analysis is proposed to investigate these unevenly sampled signals. The Hurst…

Fluid Dynamics · Physics 2012-10-08 Li-Jun Ji , Wei-Xing Zhou , Hai-feng Liu , Xin Gong , Fu-Chen Wang , Zun-Hong Yu

Consider a multidimensional diffusion process $X=\{X\left(t\right) :t\in\lbrack0,1]\}$. Let $\varepsilon>0$ be a \textit{deterministic}, user defined, tolerance error parameter. Under standard regularity conditions on the drift and…

Probability · Mathematics 2016-07-22 Jose Blanchet , Xinyun Chen , Jing Dong

Using the large deviation principle (LDP) for a re-scaled fractional Brownian motion $B^H_t$ where the rate function is defined via the reproducing kernel Hilbert space, we compute small-time asymptotics for a correlated fractional…

Pricing of Securities · Quantitative Finance 2021-03-17 Martin Forde , Hongzhong Zhang

We consider the paths of a Gaussian random process $x(t)$, $x(0)=0$ not exceeding a fixed positive level over a large time interval $(0,T)$, $T\gg 1$. The probability $p(T)$ of such event is frequently a regularly varying function at…

Probability · Mathematics 2009-09-29 G. Molchan , A. Khokhlov

We develop an efficient method to calculate the third-order corrections to the self-energy of the hole-doped two-dimensional Hubbard model in space-time representation. Using the Dyson equation we evaluate the renormalized spectral function…

Strongly Correlated Electrons · Physics 2009-10-31 V. Zlatic , B. Horvatic , B. Dolicki , S. Grabowski , P. Entel , K. -D. Schotte

Inferring a diffusion equation from discretely-observed measurements is a statistical challenge of significant importance in a variety of fields, from single-molecule tracking in biophysical systems to modeling financial instruments.…

Machine Learning · Statistics 2023-12-12 Yinuo Ren , Yiping Lu , Lexing Ying , Grant M. Rotskoff