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We consider a one-dimensional stationary stochastic process $x(\tau)$ of duration $T$. We study the probability density function (PDF) $P(t_{\rm m}|T)$ of the time $t_{\rm m}$ at which $x(\tau)$ reaches its global maximum. By using a path…

Statistical Mechanics · Physics 2021-10-15 Francesco Mori , Satya N. Majumdar , Gregory Schehr

We study the random acceleration model, which is perhaps one of the simplest, yet nontrivial, non-Markov stochastic processes, and is key to many applications. For this non-Markov process, we present exact analytical results for the…

Statistical Mechanics · Physics 2019-09-04 Satya N. Majumdar , Alberto Rosso , Andrea Zoia

Of stochastic differential equations, diffusion processes have been adopted in numerous applications, as more relevant and flexible models. This paper studies diffusion processes in a different setting, where for a given stationary…

Probability · Mathematics 2024-12-31 Saber Jafarizadeh

We present an exact solution for the probability density function $P(\tau=t_{\min}-t_{\max}|T)$ of the time-difference between the minimum and the maximum of a one-dimensional Brownian motion of duration $T$. We then generalise our results…

Statistical Mechanics · Physics 2020-04-20 Francesco Mori , Satya N. Majumdar , Gregory Schehr

We present an approximate calculation for the distribution of the maximum of a smooth stationary temporal signal X(t). As an application, we compute the persistence exponent associated to the probability that the process remains below a…

Statistical Mechanics · Physics 2007-05-23 Clément Sire

We study a class of stochastic processes of the type $\frac{d^n x}{dt^n}= v_0\, \sigma(t)$ where $n>0$ is a positive integer and $\sigma(t)=\pm 1$ represents an `active' telegraphic noise that flips from one state to the other with a…

Statistical Mechanics · Physics 2021-01-27 David S. Dean , Satya N. Majumdar , Hendrik Schawe

The TCP window size process appears in the modeling of the famous Transmission Control Protocol used for data transmission over the Internet. This continuous time Markov process takes its values in [0, \infty), is ergodic and irreversible.…

It is, perhaps, surprising that the location of the unique supremum of a stationary process on an interval can fail to be uniformly distributed over that interval. We show that this distribution is absolutely continuous in the interior of…

Probability · Mathematics 2013-10-04 Gennady Samorodnitsky , Yi Shen

Let $X=(X_t)_{t\geq 0}$ be a known process and $T$ an unknown random time independent of $X$. Our goal is to derive the distribution of $T$ based on an iid sample of $X_T$. Belomestny and Schoenmakers (2015) propose a solution based the…

Probability · Mathematics 2019-05-27 Viktor Schulmann

In this paper we consider the distribution of the location of the path supremum in a fixed interval for self-similar processes with stationary increments. To this end, a point process is constructed and its relation to the distribution of…

Probability · Mathematics 2016-05-24 Yi Shen

We calculate analytically the probability density $P(t_m)$ of the time $t_m$ at which a continuous-time Brownian motion (with and without drift) attains its maximum before passing through the origin for the first time. We also compute the…

Statistical Mechanics · Physics 2008-02-25 Julien Randon-Furling , Satya N. Majumdar

Unbalanced probability circulation, which yields cyclic motions in phase space, is the defining characteristics of a stationary diffusion process without detailed balance. In over-damped soft matter systems, such behavior is a hallmark of…

Mathematical Physics · Physics 2015-09-22 Hong Qian

The non-equilibrium steady states emerging from stochastic resetting to a distribution is studied. We show that for a range of processes, the steady-state moments can be expressed as a linear combination of the moments of the distribution…

Statistical Mechanics · Physics 2023-10-10 Kristian Stølevik Olsen

For each $n\geq 1$, let $ {X_{in}, \quad i \geq 1} $ be independent copies of a nonnegative continuous stochastic process $X_{n}=(X_n(t))_{t\in T}$ indexed by a compact metric space $T$. We are interested in the process of partial maxima…

Probability · Mathematics 2011-10-07 Clément Dombry , Frédéric Eyi-Minko

We develop a new continuous-time stochastic gradient descent method for optimizing over the stationary distribution of stochastic differential equation (SDE) models. The algorithm continuously updates the SDE model's parameters using an…

Machine Learning · Computer Science 2023-08-29 Ziheng Wang , Justin Sirignano

We study a Brownian particle diffusing under a time-modulated stochastic resetting mechanism to a fixed position. The rate of resetting r(t) is a function of the time t since the last reset event. We derive a sufficient condition on r(t)…

Statistical Mechanics · Physics 2016-05-18 Arnab Pal , Anupam Kundu , Martin R. Evans

We investigate the work fluctuations in an overdamped non-equilibrium process that is stopped at a stochastic time. The latter is characterized by a first passage event that marks the completion of the non-equilibrium process. In…

Statistical Mechanics · Physics 2024-03-20 Iago N Mamede , Prashant Singh , Arnab Pal , Carlos E. Fiore , Karel Proesmans

We derive P(M,t_m), the joint probability density of the maximum M and the time t_m at which this maximum is achieved for a class of constrained Brownian motions. In particular, we provide explicit results for excursions, meanders and…

Statistical Mechanics · Physics 2008-10-31 Satya. N. Majumdar , Julien Randon-Furling , Michael J. Kearney , Marc Yor

Using statistical thermodynamics, we derive a general expression of the stationary probability distribution for thermodynamic systems driven out of equilibrium by several thermodynamic forces. The local equilibrium is defined by imposing…

Statistical Mechanics · Physics 2015-06-12 Giorgio Sonnino , György Steinbrecher , Alessandro Cardinali , Alberto Sonnino , Mustapha Tlidi

With $M(t):=\sup_{s\in[0,t]}A(s)-s$ denoting the running maximum of a fractional Brownian motion $A(\cdot)$ with negative drift, this paper studies the rate of convergence of $\mathbb {P}(M(t)>x)$ to $\mathbb{P}(M>x)$. We define two metrics…

Probability · Mathematics 2009-09-01 Michel Mandjes , Ilkka Norros , Peter Glynn
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