arXiv subjects

Gregory Schehr

Publications and source records attributed to Gregory Schehr.

At least 37 records · Page 2Linked to original sources

arXiv2024

The number of minima in random landscapes generated by constrained random walk and Lévy flights: universal properties

We provide a uniform framework to compute the exact distribution of the number of minima/maxima in three different random walk landscape models in one dimension. The landscape is generated by the trajectory of a discrete-time continuous space random walk with arbitrary symmetric and continuous jump distribution at each step. In model I, we consider a ``free'' random walk of $N$ steps. In model II, we consider a ``meander landscape'' where the random walk, starting at the origin, stays non-negative up to $N$ steps. In model III, we study a ``first-passage landscape'' which is generated by the trajectory of a random walk that starts at the origin and stops when it crosses the origin for the first time. We demonstrate that while the exact distribution of the number of minima is different in the three models, for each model it is universal for all $N$, in the sense that it does not depend on the jump distribution as long as it is symmetric and continuous. In the last two cases we show that this universality follows from a non trivial mapping to the Sparre Andersen theorem known for the first-passage probability of discrete-time random walks with symmetric and continuous jump distribution. Our analytical results are in excellent agreement with our numerical simulations.

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arXiv2024

Cumulants and large deviations for the linear statistics of the one-dimensional trapped Riesz gas

We consider the classical trapped Riesz gas, i.e., $N$ particles at positions $x_i$ in one dimension with a repulsive power law interacting potential $\propto 1/|x_i-x_j|^{k}$, with $k>-2$, in an external confining potential of the form $V(x) \sim |x|^n$. We focus on the equilibrium Gibbs state of the gas, for which the density has a finite support $[-\ell_0/2,\ell_0/2]$. We study the fluctuations of the linear statistics ${\cal L}_N = \sum_{i=1}^N f(x_i)$ in the large $N$ limit for smooth functions $f(x)$. We obtain analytic formulae for the cumulants of ${\cal L}_N$ for general $k>-2$. For long range interactions, i.e. $k<1$, which include the log-gas ($k \to 0$) and the Coulomb gas ($k =-1$) these are obtained for monomials $f(x)= |x|^m$. For short range interactions, i.e. $k>1$, which include the Calogero-Moser model, i.e. $k=2$, we compute the third cumulant of ${\cal L}_N$ for general $f(x)$ and arbitrary cumulants for monomials $f(x)= |x|^m$. We also obtain the large deviation form of the probability distribution of ${\cal L}_N$, which exhibits an "evaporation transition" where the fluctuation of ${\cal L}_N$ is dominated by the one of the largest $x_i$. In addition, in the short range case, we extend our results to a (non-smooth) indicator function $f(x)$, obtaining thereby the higher order cumulants for the full counting statistics of the number of particles in an interval $[-L/2,L/2]$. We show in particular that they exhibit an interesting scaling form as $L/2$ approaches the edge of the gas $L/\ell_0 \to 1$, which we relate to the large deviations of the emptiness probability of the complementary interval on the real line.

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arXiv2024

Resetting by rescaling: exact results for a diffusing particle in one-dimension

In this paper, we study a simple model of a diffusive particle on a line, undergoing a stochastic resetting with rate $r$, via rescaling its current position by a factor $a$, which can be either positive or negative. For $|a|<1$, the position distribution becomes stationary at long times and we compute this limiting distribution exactly for all $|a|<1$. This symmetric distribution has a Gaussian shape near its peak at $x=0$, but decays exponentially for large $|x|$. We also studied the mean first-passage time (MFPT) $T(0)$ to a target located at a distance $L$ from the initial position (the origin) of the particle. As a function of the initial position $x$, the MFPT $T(x)$ satisfies a nonlocal second order differential equation and we have solved it explicitly for $0 \leq a < 1$. For $-1<a\leq 0$, we also solved it analytically but up to a constant factor $κ$ whose value can be determined independently from numerical simulations. Our results show that, for all $-1<a<1$, the MFPT $T(0)$ (starting from the origin) shows a minimum at $r=r^*(a)$. However, the optimised MFPT $T_{\rm opt}(a)$ turns out to be a monotonically increasing function of $a$ for $-1<a<1$. This demonstrates that, compared to the standard resetting to the origin ($a=0$), while the positive rescaling is not beneficial for the search of a target, the negative rescaling is. Thus resetting via rescaling followed by a reflection around the origin expedites the search of a target in one dimension.

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arXiv2024

Number of distinct and common sites visited by $N$ independent random walkers

In this Chapter, we consider a model of $N$ independent random walkers, each of duration $t$, and each starting from the origin, on a lattice in $d$ dimensions. We focus on two observables, namely $D_N(t)$ and $C_N(t)$ denoting respectively the number of distinct and common sites visited by the walkers. For large $t$, where the lattice random walkers converge to independent Brownian motions, we compute exactly the mean $\langle D_N(t) \rangle$ and $\langle C_N(t) \rangle$. Our main interest is on the $N$-dependence of these quantities. While for $\langle D_N(t) \rangle$ the $N$-dependence only appears in the prefactor of the power-law growth with time, a more interesting behavior emerges for $\langle C_N(t) \rangle$. For this latter case, we show that there is a ``phase transition'' in the $(N, d)$ plane where the two critical line $d=2$ and $d=d_c(N) = 2N/(N-1)$ separate three phases of the growth of $\langle C_N(t)\rangle$. The results are extended to the mean number of sites visited exactly by $K$ of the $N$ walkers. Furthermore in $d=1$, the full distribution of $D_N(t)$ and $C_N(t)$ are computed, exploiting a mapping to the extreme value statistics. Extensions to two other models, namely $N$ independent Brownian bridges and $N$ independent resetting Brownian motions/bridges are also discussed.

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arXiv2024

Decorrelation of a leader by the increasing number of followers

We compute the connected two-time correlator of the maximum $M_N(t)$ of $N$ independent Gaussian stochastic processes (GSP) characterised by a common correlation coefficient $ρ$ that depends on the two times $t_1$ and $t_2$. We show analytically that this correlator, for fixed times $t_1$ and $t_2$, decays for large $N$ as a power law $N^{-γ}$ (with logarithmic corrections) with a decorrelation exponent $γ= (1-ρ)/(1+ ρ)$ that depends only on $ρ$, but otherwise is universal for any GSP. We study several examples of physical processes including the fractional Brownian motion (fBm) with Hurst exponent $H$ and the Ornstein-Uhlenbeck (OU) process. For the fBm, $ρ$ is only a function of $τ= \sqrt{t_1/t_2}$ and we find an interesting ``freezing'' transition at a critical value $τ= τ_c=(3-\sqrt{5})/2$. For $τ< τ_c$, there is an optimal $H^*(τ) > 0$ that maximises the exponent $γ$ and this maximal value freezes to $γ= 1/3$ for $τ>τ_c$. For the OU process, we show that $γ= {\rm tanh}(μ\,|t_1-t_2|/2)$ where $μ$ is the stiffness of the harmonic trap. Numerical simulations confirm our analytical predictions.

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arXiv2024

Universal distribution of the number of minima for random walks and Lévy flights

We compute exactly the full distribution of the number $m$ of local minima in a one-dimensional landscape generated by a random walk or a Lévy flight. We consider two different ensembles of landscapes, one with a fixed number of steps $N$ and the other till the first-passage time of the random walk to the origin. We show that the distribution of $m$ is drastically different in the two ensembles (Gaussian in the former case, while having a power-law tail in the latter $m^{-3/2}$ in the latter case). However, the most striking aspect of our results is that, in each case, the distribution is completely universal for all $m$ (and not just for large $m$), i.e., independent of the jump distribution in the random walk. This means that the distributions are exactly identical for Lévy flights and random walks with finite jump variance. Our analytical results are in excellent agreement with our numerical simulations.

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arXiv2024

Optimal mean first-passage time of a run-and-tumble particle in a class of one-dimensional confining potentials

We consider a run-and-tumble particle (RTP) in one dimension, subjected to a telegraphic noise with a constant rate $γ$, and in the presence of an external confining potential $V(x) = α|x|^p$ with $p \geq 1$. We compute the mean first-passage time (MFPT) at the origin $τ_γ(x_0)$ for an RTP starting at $x_0$. We obtain a closed form expression for $τ_γ(x_0)$ for all $p \geq 1$, which becomes fully explicit in the case $p=1$, $p=2$ and in the limit $p \to \infty$. For generic $p>1$ we find that there exists an optimal rate $γ_{\rm opt}$ that minimizes the MFPT and we characterize in detail its dependence on $x_0$. We find that $γ_{\rm opt} \propto 1/x_0$ as $x_0 \to 0$, while $γ_{\rm opt}$ converges to a nontrivial constant as $x_0 \to \infty$. In contrast, for $p=1$, there is no finite optimum and $γ_{\rm opt} \to \infty$ in this case. These analytical results are confirmed by our numerical simulations.

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arXiv2024

Active particle in a harmonic trap driven by a resetting noise: an approach via Kesten variables

We consider the statics and dynamics of a single particle trapped in a one-dimensional harmonic potential, and subjected to a driving noise with memory, that is represented by a resetting stochastic process. The finite memory of this driving noise makes the dynamics of this particle ``active''. At some chosen times (deterministic or random), the noise is reset to an arbitrary position and restarts its motion. We focus on two resetting protocols: periodic resetting, where the period is deterministic, and Poissonian resetting, where times between resets are exponentially distributed with a rate $r$. Between the different resetting epochs, we can express recursively the position of the particle. The random relation obtained takes a simple Kesten form that can be used to derive an integral equation for the stationary distribution of the position. We provide a detailed analysis of the distribution when the noise is a resetting Brownian motion. In this particular instance, we also derive a renewal equation for the full time dependent distribution of the position that we extensively study. These methods are quite general and can be used to study any process harmonically trapped when the noise is reset at random times.

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arXiv2023

Fluctuations in the active Dyson Brownian motion and the overdamped Calogero-Moser model

Recently, we introduced the active Dyson Brownian motion model (DBM), in which $N$ run-and-tumble particles interact via a logarithmic repulsive potential in the presence of a harmonic well. We found that in a broad range of parameters the density of particles converges at large $N$ to the Wigner semi-circle law, as in the passive case. In this paper, we provide an analytical support for this numerical observation, by studying the fluctuations of the positions of the particles in the nonequilibrium stationary state of the active DBM, in the regime of weak noise and large persistence time. In this limit, we obtain an analytical expression for the covariance between the particle positions for any $N$ from the exact inversion of the Hessian matrix of the system. We show that, when the number of particles is large $N \gg 1$, the covariance matrix takes scaling forms that we compute explicitly both in the bulk and at the edge of the support of the semi-circle. In the bulk, the covariance scales as $N^{-1}$, while at the edge, it scales as $N^{-2/3}$. Remarkably, we find that these results can be transposed directly to an equilibrium model, the overdamped Calogero-Moser model in the low temperature limit, providing an analytical confirmation of the numerical results by Agarwal, Kulkarni and Dhar. For this model, our method also allows us to obtain the equilibrium two-time correlations and their dynamical scaling forms both in the bulk and at the edge. Our predictions at the edge are reminiscent of a recent result in the mathematics literature by Gorin and Kleptsyn on the (passive) DBM. That result can be recovered by the present methods, and also, as we show, using the stochastic Airy operator. Finally, our analytical predictions are confirmed by precise numerical simulations, in a wide range of parameters.

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arXiv2023

Dynamically emergent correlations between particles in a switching harmonic trap

We study a one dimensional gas of $N$ noninteracting diffusing particles in a harmonic trap, whose stiffness switches between two values $μ_1$ and $μ_2$ with constant rates $r_1$ and $r_2$ respectively. Despite the absence of direct interaction between the particles, we show that strong correlations between them emerge in the stationary state at long times, induced purely by the dynamics itself. We compute exactly the joint distribution of the positions of the particles in the stationary state, which allows us to compute several physical observables analytically. In particular, we show that the extreme value statistics (EVS), i.e., the distribution of the position of the rightmost particle has a nontrivial shape in the large $N$ limit. The scaling function characterizing this EVS has a finite support with a tunable shape (by varying the parameters). Remarkably, this scaling function turns out to be universal. First, it also describes the distribution of the position of the $k$-th rightmost particle in a $1d$ trap. Moreover, the distribution of the position of the particle farthest from the center of the harmonic trap in $d$ dimensions is also described by the same scaling function for all $d \geq 1$. Numerical simulations are in excellent agreement with our analytical predictions.

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arXiv2023

Interacting, running and tumbling: the active Dyson Brownian motion

We introduce and study a model in one dimension of $N$ run-and-tumble particles (RTP) which repel each other logarithmically in the presence of an external quadratic potential. This is an "active'' version of the well-known Dyson Brownian motion (DBM) where the particles are subjected to a telegraphic noise, with two possible states $\pm$ with velocity $\pm v_0$. We study analytically and numerically two different versions of this model. In model I a particle only interacts with particles in the same state, while in model II all the particles interact with each other. In the large time limit, both models converge to a steady state where the stationary density has a finite support. For finite $N$, the stationary density exhibits singularities, which disappear when $N \to +\infty$. In that limit, for model I, using a Dean-Kawasaki approach, we show that the stationary density of $+$ (respectively $-$) particles deviates from the DBM Wigner semi-circular shape, and vanishes with an exponent $3/2$ at one of the edges. In model II, the Dean-Kawasaki approach fails but we obtain strong evidence that the density in the large $N$ limit retains a Wigner semi-circular shape.

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arXiv2023

Universality in the number variance and counting statistics of the real and symplectic Ginibre ensemble

In this article, we compute and compare the statistics of the number of eigenvalues in a centred disc of radius $R$ in all three Ginibre ensembles. We determine the mean and variance as functions of $R$ in the vicinity of the origin, where the real and symplectic ensembles exhibit respectively an additional attraction to or repulsion from the real axis, leading to different results. In the large radius limit, all three ensembles coincide and display a universal bulk behaviour of $O(R^2)$ for the mean, and $O(R)$ for the variance. We present detailed conjectures for the bulk and edge scaling behaviours of the real Ginibre ensemble, having real and complex eigenvalues. For the symplectic ensemble we can go beyond the Gaussian case (corresponding to the Ginibre ensemble) and prove the universality of the full counting statistics both in the bulk and at the edge of the spectrum for rotationally invariant potentials, extending a recent work which considered the mean and the variance. This statistical behaviour coincides with the universality class of the complex Ginibre ensemble, which has been shown to be associated with the ground state of non-interacting fermions in a two-dimensional rotating harmonic trap. All our analytical results and conjectures are corroborated by numerical simulations.

math-ph↗

arXiv2023

Linear statistics for Coulomb gases: higher order cumulants

We consider $N$ classical particles interacting via the Coulomb potential in spatial dimension $d$ and in the presence of an external trap, at equilibrium at inverse temperature $β$. In the large $N$ limit, the particles are confined within a droplet of finite size. We study smooth linear statistics, i.e. the fluctuations of sums of the form ${\cal L}_N = \sum_{i=1}^N f({\bf x}_i)$, where ${\bf x}_i$'s are the positions of the particles and where $f({\bf x}_i)$ is a sufficiently regular function. There exists at present standard results for the first and second moments of ${\cal L}_N$ in the large $N$ limit, as well as associated Central Limit Theorems in general dimension and for a wide class of confining potentials. Here we obtain explicit expressions for the higher order cumulants of ${\cal L}_N$ at large $N$, when the function $f({\bf x})=f(|{\bf x}|)$ and the confining potential are both rotationnally invariant. A remarkable feature of our results is that these higher cumulants depend only on the value of $f'(|{\bf x}|)$ and its higher order derivatives evaluated exactly at the boundary of the droplet, which in this case is a $d$-dimensional sphere. In the particular two-dimensional case $d=2$ at the special value $β=2$, a connection to the Ginibre ensemble allows us to derive these results in an alternative way using the tools of determinantal point processes. Finally we also obtain the large deviation form of the full probability distribution function of ${\cal L}_N$.

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arXiv2023

Striking universalities in stochastic resetting processes

Given a random process $x(τ)$ which undergoes stochastic resetting at a constant rate $r$ to a position drawn from a distribution ${\cal P}(x)$, we consider a sequence of dynamical observables $A_1, \dots, A_n$ associated to the intervals between resetting events. We calculate exactly the probabilities of various events related to this sequence: that the last element is larger than all previous ones, that the sequence is monotonically increasing, etc. Remarkably, we find that these probabilities are ``super-universal'', i.e., that they are independent of the particular process $x(τ)$, the observables $A_k$'s in question and also the resetting distribution ${\cal P}(x)$. For some of the events in question, the universality is valid provided certain mild assumptions on the process and observables hold (e.g., mirror symmetry).

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arXiv2023

Critical number of walkers for diffusive search processes with resetting

We consider $N$ Brownian motions diffusing independently on a line, starting at $x_0>0$, in the presence of an absorbing target at the origin. The walkers undergo stochastic resetting under two protocols: (A) each walker resets independently to $x_0$ with rate $r$ and (B) all walkers reset simultaneously to $x_0$ with rate $r$. We compute analytically the mean first-passage time to the origin and show that, as a function of $r$ and for fixed $x_0$, it has a minimum at an optimal value $r^*>0$ as long as $N N_c$, the optimal value occurs at $r^*=0$ indicating that resetting hinders search processes. Continuing our results analytically to real $N$, we show that $N_c=7.3264773\ldots$ for protocol A and $N_c=6.3555864\ldots$ for protocol B, independently of $x_0$. Our theoretical predictions are verified in numerical Langevin simulations.

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arXiv2023

Effusion of stochastic processes on a line

We consider the problem of leakage or effusion of an ensemble of independent stochastic processes from a region where they are initially randomly distributed. The case of Brownian motion, initially confined to the left half line with uniform density and leaking into the positive half line is an example which has been extensively studied in the literature. Here we derive new results for the average number and variance of the number of leaked particles for arbitrary Gaussian processes initially confined to the negative half line and also derive its joint two-time probability distribution, both for the annealed and the quenched initial conditions. For the annealed case, we show that the two-time joint distribution is a bivariate Poisson distribution. We also discuss the role of correlations in the initial particle positions on the statistics of the number of particles on the positive half line. We show that the strong memory effects in the variance of the particle number on the positive real axis for Brownian particles, seen in recent studies, persist for arbitrary Gaussian processes and also at the level of two-time correlation functions.

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arXiv2023

Current fluctuations in stochastically resetting particle systems

We consider a system of non-interacting particles on a line with initial positions distributed uniformly with density $ρ$ on the negative half-line. We consider two different models: (i) each particle performs independent Brownian motion with stochastic resetting to its initial position with rate $r$ and (ii) each particle performs run and tumble motion, and with rate $r$ its position gets reset to its initial value and simultaneously its velocity gets randomised. We study the effects of resetting on the distribution $P(Q,t)$ of the integrated particle current $Q$ up to time $t$ through the origin (from left to right). We study both the annealed and the quenched current distributions and in both cases, we find that resetting induces a stationary limiting distribution of the current at long times. However, we show that the approach to the stationary state of the current distribution in the annealed and the quenched cases are drastically different for both models. In the annealed case, the whole distribution $P_{\rm an}(Q,t)$ approaches its stationary limit uniformly for all $Q$. In contrast, the quenched distribution $P_{\rm qu}(Q,t)$ attains its stationary form for $Q Q_{\rm crit}(t)$. We show that $Q_{\rm crit}(t)$ increases linearly with $t$ for large $t$. On the scale where $Q \sim Q_{\rm crit}(t)$, we show that $P_{\rm qu}(Q,t)$ has an unusual large deviation form with a rate function that has a third-order phase transition at the critical point. We have computed the associated rate functions analytically for both models. Using an importance sampling method that allows to probe probabilities as tiny as $10^{-14000}$, we were able to compute numerically this non-analytic rate function for the resetting Brownian dynamics and found excellent agreement with our analytical prediction.

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arXiv2023

Out of equilibrium dynamics of repulsive ranked diffusions: the expanding crystal

We study the non-equilibrium Langevin dynamics of $N$ particles in one dimension with Coulomb repulsive linear interactions. This is a dynamical version of the so-called jellium model (without confinement) also known as ranked diffusion. Using a mapping to the Lieb-Liniger model of quantum bosons, we obtain an exact formula for the joint distribution of the positions of the $N$ particles at time $t$, all starting from the origin. A saddle point analysis shows that the system converges at large time to a linearly expanding crystal. Properly rescaled, this dynamical state resembles the equilibrium crystal in a time dependent effective quadratic potential. This analogy allows to study the fluctuations around the perfect crystal, which, to leading order, are Gaussian. There are however deviations from this Gaussian behavior, which embody long-range correlations of purely dynamical origin, characterized by the higher order cumulants of, e.g., the gaps between the particles, that we calculate exactly. We complement these results using a recent approach by one of us in terms of a noisy Burgers equation. In the large $N$ limit, the mean density of the gas can be obtained at any time from the solution of a deterministic viscous Burgers equation. This approach provides a quantitative description of the dense regime at shorter times. Our predictions are in good agreement with numerical simulations for finite and large $N$.

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