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This thesis is devoted to the study of extreme value statistics in stochastic processes and their applications. In the first part, we obtain exact analytical results on the extreme value statistics of both discrete-time and continuous-time…

Statistical Mechanics · Physics 2023-10-24 Benjamin De Bruyne

The real-space renormalization group (RSRG) method introduced previously for the Brownian landscape is generalized to obtain the joint probability distribution of the subset of the important extrema at large scales of other one-dimensional…

Disordered Systems and Neural Networks · Physics 2009-11-07 P. Le Doussal , C. Monthus

We study the extreme value statistics of a one-dimensional resetting Brownian motion (RBM) till its first passage through the origin starting from the position $x_0$ ($>0$). By deriving the exit probability of RBM in an interval $\left[0, M…

Statistical Mechanics · Physics 2024-01-26 Wusong Guo , Hao Yan , Hanshuang Chen

Reinforced random walks (RRWs), including vertex-reinforced random walks (VRRWs) and edge-reinforced random walks (ERRWs), model random walks where the transition probabilities evolve based on prior visitation history~\cite{mgr, fmk,…

Machine Learning · Statistics 2026-05-22 Qinghua , Ding , Venkat Anantharam

We study the statistics of near-extreme events of Brownian motion (BM) on the time interval [0,t]. We focus on the density of states (DOS) near the maximum \rho(r,t) which is the amount of time spent by the process at a distance r from the…

Statistical Mechanics · Physics 2013-12-16 Anthony Perret , Alain Comtet , Satya N. Majumdar , Gregory Schehr

We present real--space renormalization group (RG) calculations of the critical properties of the random--field Ising model on a cubic lattice in three dimensions. We calculate the RG flows in a two--parameter truncation of the Hamiltonian…

Condensed Matter · Physics 2009-10-22 M. E. J. Newman , B. W. Roberts , G. T. Barkema , J. P. Sethna

The one-dimensional Brownian motion starting from the origin at time $t=0$, conditioned to return to the origin at time $t=1$ and to stay positive during time interval $0 < t < 1$, is called the Bessel bridge with duration 1. We consider…

Statistical Mechanics · Physics 2008-11-06 Naoki Kobayashi , Minami Izumi , Makoto Katori

We present a numerical implementation of the renormalization group (RG) for partial differential equations, constructing similarity solutions and travelling waves. We show that for a large class of well-localized initial conditions,…

chao-dyn · Physics 2009-10-22 Lin-Yuan Chen , Nigel Goldenfeld

We study continuous time random walks (CTRW) with power law distribution of waiting times under resetting which brings the walker back to the origin, with a power-law distribution of times between the resetting events. Two situations are…

Statistical Mechanics · Physics 2020-07-01 Anna S. Bodrova , Igor M. Sokolov

We study the extreme value statistics of first-passage trajectories generating from a one-dimensional drifted Brownian motion subject to stochastic resetting to the starting point with a constant rate $r$. Each stochastic trajectory starts…

Statistical Mechanics · Physics 2025-06-18 Wusong Guo , Hao Yan , Hanshuang Chen

For three constrained Brownian motions, the excursion, the meander, and the reflected bridge, the densities of the maximum and of the time to reach it were expressed as double series by Majumdar, Randon-Furling, Kearney, and Yor (2008).…

Probability · Mathematics 2018-07-25 Robin Khanfir

We present a renormalization group (RG) procedure which works naturally on a wide class of interacting one-dimension models based on perturbed (possibly strongly) continuum conformal and integrable models. This procedure integrates Kenneth…

Strongly Correlated Electrons · Physics 2016-07-05 Robert M. Konik , Yury Adamov

We develop a continuous time random walk (CTRW) approach for the evolution of Lagrangian velocities in steady heterogeneous flows based on a stochastic relaxation process for the streamwise particle velocities. This approach describes…

Fluid Dynamics · Physics 2016-11-30 Marco Dentz , Peter K. Kang , Alessandro Comolli , Tanguy Le Borgne , Daniel R. Lester

A continuous time random walk (CTRW) is a random walk in which both spatial changes represented by jumps and waiting times between the jumps are random. The CTRW is coupled if a jump and its preceding or following waiting time are dependent…

Probability · Mathematics 2016-03-14 Adam Barczyk , Peter Kern

We show how to extract the scaling behavior of quantum walks using the renormalization group (RG). We introduce the method by efficiently reproducing well-known results on the one-dimensional lattice. As a nontrivial model, we apply this…

Statistical Mechanics · Physics 2014-09-30 S. Boettcher , S. Falkner , R. Portugal

We consider a one-dimensional Brownian motion of fixed duration $T$. Using a path-integral technique, we compute exactly the probability distribution of the difference $\tau=t_{\min}-t_{\max}$ between the time $t_{\min}$ of the global…

Statistical Mechanics · Physics 2020-05-13 Francesco Mori , Satya N. Majumdar , Gregory Schehr

Sood and Grassberger studied in [Phys. Rev. Lett. 99, 098701 (2007)] random walks on random graphs that are biased towards a fixed target point. They put forward a critical bias strength b_c such that a random walker on an infinite graph…

Statistical Mechanics · Physics 2009-11-13 O. Benichou , R. Voituriez

We study a general continuous-time random walk (CTRW), by including non-Markovian cases and L\'evy flights, under complete stochastic resetting to the initial position with an arbitrary law, which can be power-lawed as well as Poissonian.…

Statistical Mechanics · Physics 2025-07-11 Fausto Colantoni , Gianni Pagnini

Brownian motion is a well-known model for normal diffusion, but not all physical phenomena behave according to a Brownian motion. Many phenomena exhibit irregular diffusive behavior, called anomalous diffusion. Examples of anomalous…

Probability · Mathematics 2011-10-04 Meredith N. Burr

Extreme value functionals of stochastic processes are inverse functionals of the first passage time -- a connection that renders their probability distribution functions equivalent. Here, we deepen this link and establish a framework for…

Statistical Mechanics · Physics 2019-05-30 David Hartich , Aljaz Godec
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