arXiv subjects

Quentin Berger

Publications and source records attributed to Quentin Berger.

At least 19 recordsLinked to original sources

arXiv2026

Free energy and phase transition for 2D directed polymers with critical spatial correlations

We study the two-dimensional directed polymer model in a Gaussian environment which is independent in time and spatially correlated, with covariances $h(x)$ either summable or with a critical decay, satisfying $h(x) \sim (\log |x|)^a/|x|^2$ as $|x|\to\infty$ for some $a>-1$. We determine the precise high-temperature asymptotics of the free energy, confirming a conjecture of Lacoin (Ann. Probab. 2011), later refined by Cosco, Cottini and Donadini (2025). We also establish a phase transition for the diffusively rescaled partition functions: below some critical point they converge to the Lebesgue measure, while above it they converge to zero. A key feature of our approach is that both results are obtained using only second-moment estimates and are based on a simplified change-of-measure argument in the supercritical regime, that may prove useful for other disordered models.

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arXiv2026

Fractional moments of the Stochastic Heat Flow and 2D Directed Polymers

We estimate the fractional moments of the normalized mass assigned by the Critical 2D Stochastic Heat Flow to small balls. Our results also cover the discrete case corresponding to the 2D directed polymer model and provide estimates that are uniform in all parameters. One key takeaway of our results is that the vanishing of the fractional moments is completely governed by the divergence of the second moment. We use a quite robust method, by refining the change of measure argument and introducing a novel coarse-graining procedure, reducing the proof to essentially second moment estimates (in fact, we also provide sharp second moment estimates for directed polymers, of independent interest).

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arXiv2026

Sharp behavior of the free energy for the two-dimensional directed polymer model

We consider the directed polymer model on $\mathbb{Z}^d$, in an i.i.d.\ random environment $\omega=(\omega_{n,x})_{n\geq 0,x\in\mathbb Z^d}$, focusing on the critical dimension $d=2$. Our main contribution is to give a sharp lower bound on the free energy in the high-temperature regime. Our proof uses a percolation argument inspired by Lacoin (2010), for which we introduce a key property of bounded ``$\log$-energy'': this property quantifies the regularity of the polymer measures at diffusive scales and we show that it propagates along open paths. Writing $\mathfrak{f}(\beta)$ for the quenched free energy, and setting $\lambda(\beta):=\log \mathbb E[e^{\beta\omega_{1,0}}]$ and $\sigma(\beta)^2:=e^{\lambda(2\beta)-2\lambda(\beta)}-1$, our lower bound combined with Theorem 2.8 of Berger, Caravenna, and Turchi (2025) gives $$ -\mathfrak{f}(\beta) \asymp \exp{\Big(- \frac{\pi}{\sigma^2(\beta)}\Big)},\quad \text{ as $\beta\downarrow 0$.} $$

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arXiv2025

The Random Walk Pinning Model II: Upper bounds on the free energy and disorder relevance

This article investigates the question of disorder relevance for the continuous-time Random Walk Pinning Model (RWPM) and completes the results of our companion paper. The RWPM considers a continuous time random walk $X=(X_t)_{t\geq 0}$, whose law is modified by a Gibbs weight given by $\exp(\beta \int_0^T \mathbf{1}_{\{X_t=Y_t\}} dt)$, where $Y=(Y_t)_{t\geq 0}$ is a quenched trajectory of a second (independent) random walk and $\beta \geq 0$ is the inverse temperature. The random walk $Y$ has the same distribution as $X$ but a jump rate $\rho \geq 0$, interpreted as the disorder intensity. For fixed $\rho\ge 0$, the RWPM undergoes a localization phase transition as $\beta$ crosses a critical threshold $\beta_c(\rho)$. The question of disorder relevance then consists in determining whether a disorder of arbitrarily small intensity $\rho$ changes the properties of the phase transition. We focus our analysis on the case of transient $\gamma$-stable walks on $\mathbb{Z}$, i.e. random walks in the domain of attraction of a $\gamma$-stable law, with $\gamma\in (0,1)$. In the present paper, we show that disorder is relevant when $\gamma \in (0,\frac23]$, namely that $\beta_c(\rho)>\beta_c(0)$ for every $\rho>0$. We also provide lower bounds on the critical point shift, which are matching the upper bounds obtained in our companion paper. Interestingly, in the marginal case $\gamma = \frac23$, disorder is always relevant, independently of the fine properties of the random walk distribution. When $\gamma \in (\frac23,1)$, our companion paper proves that disorder is irrelevant (in particular $\beta_c(\rho)=\beta_c(0)$ for $\rho$ small enough). We provide here an upper bound on the free energy in the regime $\gamma\in (\frac 2 3,1)$ that highlights the fact that although disorder is irrelevant, it still has a non-trivial effect on the phase transition, at any $\rho>0$.

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arXiv2025

The Random Walk Pinning Model I: Lower bounds on the free energy and disorder irrelevance

The Random Walk Pinning Model (RWPM) is a statistical mechanics model in which the trajectory of a continuous time random walk $X=(X_t)_{t\geq 0}$ is rewarded according to the time it spends together with a moving catalyst. More specifically for a system of size $T$, the law of $X$ is tilted by the Gibbs factor $\exp(\beta \int_0^T \mathbf{1}_{\{X_t=Y_t\}} dt)$, where $\beta \geq 0$ is the inverse temperature. The moving catalyst $Y=(Y_t)_{t\ge 0}$ is given by the quenched trajectory of a second continuous-time random walk, with the same distribution as $X$ but a different jump rate $\rho\geq 0$, interpreted as the disorder intensity. For fixed $\rho\ge 0$, the RWPM undergoes a localization phase transition when $\beta$ passes a critical value $\beta_c(\rho)$. We thoroughly investigate the question of disorder relevance to determine whether a disorder of arbitrarily small intensity affects the features of the phase transition. We focus our analysis on the case of transient $\gamma$-stable walks on $\mathbb{Z}$, i.e. random walks in the domain of attraction of a $\gamma$-stable law, with $\gamma\in (0,1)$. In the present paper, we derive lower bounds for the free energy, which results in either a proof of disorder irrelevance or upper bounds on the critical point shift. More precisely, when $\gamma \in(\frac23,1)$, our estimates imply that that $\beta_c(\rho)=\beta_c(0)$ and $\rho$ is small, showing disorder irrelevance. When $\gamma\in (0,\frac23]$ our companion paper shows that $\beta_c(\rho)>\beta_c(0)$ for every $\rho>0$, showing disorder relevance: we derive here upper bounds on the critical point shift, which are matching the lower bounds obtained in our companion paper. For good measure, our analysis also includes the case of the simple random walk of $\mathbb{Z}^d$ (for $d\ge 3$) for which no upper bound on the critical point shift was previously known.

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arXiv2025

Strong Disorder for Stochastic Heat Flow and 2D Directed Polymers

The critical 2D Stochastic Heat Flow (SHF) is a universal measure-valued process that provides a notion of solution to the ill-defined 2D stochastic heat equation. We investigate the SHF in the large-time and strong-disorder regimes, proving a sharp form of local extinction: we identify the rate at which the distribution collapses to zero. We also identify the spatial scale governing the transition from vanishing mass to diverging mass, and from extinction to an averaged behavior. Corresponding results are established for the partition functions of 2D directed polymers, yielding precise free-energy estimates. Our proof provides a unified framework of change of measure and coarse-graining arguments. These results offer new insights into the 2D stochastic heat equation regularized via space-time discretization: for any regime of supercritical disorder strength $\beta$, including the case where $\beta > 0$ is kept fixed, the solution exhibits fluctuations on a superdiffusive scale.

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arXiv2025

A random polymer approach to the weak disorder phase of the vertex reinforced jump process

In this paper, we study the transient phase of the Vertex Reinforced Jump Process (VRJP) in dimension $d\geq 3$. In Sabot, Zeng (2019), the authors introduce a positive martingale and show that the VRJP is recurrent if and only if that martingale converges to $0$. On $\mathbb{Z}^d$, $d\ge 3$, with constant conductances $W$, it can be shown that there is a critical value $0 W_c(\mathbb{Z}^d)$. On the other hand, the VRJP martingale can be interpreted as the partition function of a non-directed polymer with a very specific $1$-dependent random potential. In this paper, we focus on the question of the $L^p$ integrability of the VRJP martingale, which is related to the (diffusive) behavior of the VRJP. First, taking inspiration from the work of Junk (2022) for directed polymers in $\mathbb{Z}^{1+d}$, we prove that on the half-space $\mathbb{H}_d$ of $\mathbb{Z}^d$, for all $W>W_c(\mathbb{H}_d)$ there is some $\delta>0$ such that the VRJP martingale is in $L^{1+\delta}$. Second, we prove that, in dimension $d\geq 4$, the VRJP martingale is in $L^{p}$ for all $p>1$ above the ``slab critical point'' $W_c^{\mathrm{slab}} (\mathbb{Z}^d) = \lim_{m\to\infty} W_c(\mathbb{Z}^{d-1} \times \{-m,\ldots,m\})$. We also propose some related conjectures.

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arXiv2024

Some properties of the principal Dirichlet eigenfunction in Lipschitz domains, via probabilistic couplings

We study a discrete and continuous version of the spectral Dirichlet problem in an open bounded connected set $\Omega\subset \mathbb{R}^d$, in dimension $d\geq 2$. More precisely, consider the simple random walk on $\mathbb{Z}^d$ killed upon exiting the (large) bounded domain $\Omega_N = (N\Omega)\cap \mathbb{Z}^d$. We let $P_N$ its transition matrix and we study the properties of its ($L^2$-normalized) principal eigenvector $\phi_N$, also known as ground state. Under mild assumptions on $\Omega$, we give regularity estimates on $\phi_N$, namely on its $k$-th order differences (or $k$-th order derivatives), with a uniform control inside $\Omega_N$. We provide a completely probabilistic proof of these estimates: our starting point is a Feynman-Kac representation of $\phi_N$, combined with gambler's ruin estimates and a new ``multi-mirror'' coupling, which may be of independent interest. We also obtain the same type of estimates for the first eigenfunction $\varphi_1$ of the corresponding continuous spectral Dirichlet problem, in relation with a Brownian motion killed upon exiting $\Omega$. Finally, we take the opportunity to review (and slightly extend) some of the literature on the $L^2$ and uniform convergence of $\phi_N$ to $\varphi_1$ in Lipschitz bounded domains of $\mathbb{R}^d$, which can be derived thanks to our estimates.

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arXiv2024

On joint returns to zero of Bessel processes

In this article, we consider joint returns to zero of $n$ Bessel processes ($n\geq 2$): our main goal is to estimate the probability that they avoid having joint returns to zero for a long time. More precisely, considering $n$ independent Bessel processes $(X_t^{(i)})_{1\leq i \leq n}$ of dimension $\delta \in (0,1)$, we are interested in the first joint return to zero of any two of them: \[ H_n := \inf\big\{ t>0, \exists 1\leq i t) = t^{-\theta_n+o(1)}$ as $t\to\infty$, and we provide some non-trivial bounds on $\theta_n$. In particular, when $n=3$, we show that $2(1-\delta)\leq \theta_3 \leq 2 (1-\delta) + f(\delta)$ for some (explicit) function $f(\delta)$ with $\sup_{[0,1]} f(\delta) \approx 0.079$.

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arXiv2024

Non-linear conductances of Galton-Watson trees and application to the (near) critical random cluster model

In this article, we study concave recursions on trees, which appear widely in information theory through algorithms such as belief propagation, and in statistical mechanics through models on tree-like graphs, including the Ising model, percolation, and more generally, the random cluster model. These tree recursions can, in fact, be compared with non-linear conductances, or $p$-conductances, between the root and the leaves of the tree. In this article, we estimate the $p$-conductances of $T_n$, a supercritical Galton--Watson tree of depth $n$, for any $p>1$, for a quenched realization of $T_n$. In particular, we find the sharp asymptotic behavior when $n$ goes to infinity, which depends on whether the offspring distribution admits a finite moment of order $q$, where $q=\frac{p}{p-1}$ is the conjugate exponent of $p$. We then apply our results to the random cluster model on $T_n$ (with cluster weight parameter in $(0,2]$ and wired boundary condition) providing sharp estimates on the probability that the root is connected to the leaves. As an example, for the Ising model on $T_n$ with plus boundary conditions on the leaves, we find that, at criticality, the quenched magnetization of the root decays like: (i) $n^{-1/2}$ times an explicit tree-dependent constant if the offspring distribution admits a finite third moment; (ii) $n^{-1/(\alpha-1)}$ if the offspring distribution has a heavy tail with exponent $\alpha \in (1,3)$.

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arXiv2023

Ising model on a Galton-Watson tree with a sparse random external field

We consider the Ising model on a supercritical Galton-Watson tree $\mathbf{T}_n$ of depth $n$ with a sparse random external field, given by a collection of i.i.d. Bernouilli random variables with vanishing parameter $p_n$. This may me viewed as a toy model for the Ising model on a configuration model with a few interfering external vertices carrying a plus spin: the question is to know how many (or how few) interfering vertices are enough to influence the whole graph. Our main result consists in providing a necessary and sufficient condition on the parameters $(p_n)_{n\geq 0}$ for the root of $\mathbf{T}_n$ to remain magnetized in the large $n$ limit. Our model is closely related to the Ising model on a (random) pruned sub-tree $\mathbf{T}_n^*$ with plus boundary condition; one key result is that this pruned tree turns out to be an inhomogeneous, $n$-dependent, Branching Process. We then use standard tools such as tree recursions and non-linear capacities to study the Ising model on this sequence of Galton-Watson trees; one difficulty is that the offspring distributions of $\mathbf{T}_n^*$, in addition to vary along the generations $0\leq k \leq n-1$, also depend on~$n$.

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arXiv2023

Wetting on a wall and wetting in a well: Overview of equilibrium properties

We study the wetting model, which considers a random walk constrained to remain above a hard wall, but with additional pinning potential for each contact with the wall. This model is known to exhibit a wetting phase transition, from a localized phase (with trajectories pinned to the wall) to a delocalized phase (with unpinned trajectories). As a preamble, we take the opportunity to present an overview of the model, collecting and complementing well-known and other folklore results. Then, we investigate a version with elevated boundary conditions, which has been studied in various contexts both in the physics and the mathematics literature; it can alternatively be seen as a wetting model in a square well. We complement here existing results, focusing on the equilibrium properties of the model, for a general underlying random walk (in the domain of attraction of a stable law). First, we compute the free energy and give some properties of the phase diagram; interestingly, we find that, in addition to the wetting transition, a so-called saturation phase transition may occur. Then, in the so-called Cram\'er's region, we find an exact asymptotic equivalent of the partition function, together with a (local) central limit theorem for the fluctuations of the left-most and right-most pinned points, jointly with the number of contacts at the bottom of the well.

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arXiv2023

An application of Sparre Andersen's fluctuation theorem for exchangeable and sign-invariant random variables

We revisit here a famous result by Sparre Andersen on persistence probabilities $\mathbf{P}(S_k>0 \;\forall\, 0\leq k\leq n)$ for symmetric random walks $(S_n)_{n\geq 0}$. We give a short proof of this result when considering sums of random variables that are only assumed exchangeable and sign-invariant. We then apply this result to the study of persistence probabilities of (symmetric) additive functionals of Markov chains, which can be seen as a natural generalization of integrated random walks.

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arXiv2023

Persistence problems for additive functionals of one-dimensional Markov processes

In this article, we consider additive functionals $\zeta_t = \int_0^t f(X_s)\mathrm{d} s$ of a c\`adl\`ag Markov process $(X_t)_{t\geq 0}$ on $\mathbb{R}$. Under some general conditions on the process $(X_t)_{t\geq 0}$ and on the function $f$, we show that the persistence probabilities verify $\mathbb{P}(\zeta_s < z \text{ for all } s\leq t ) \sim \mathcal{V}(z) \varsigma(t) t^{-\theta}$ as $t\to\infty$, for some (explicit) $\mathcal{V}(\cdot)$, some slowly varying function $\varsigma(\cdot)$ and some $\theta\in (0,1)$. This extends results in the literature, which mostly focused on the case of a self-similar process $(X_t)_{t\geq 0}$ (such as Brownian motion or skew-Bessel process) with a homogeneous functional $f$ (namely a pure power, possibly asymmetric). In a nutshell, we are able to deal with processes which are only asymptotically self-similar and functionals which are only asymptotically homogeneous. Our results rely on an excursion decomposition of $(X_t)_{t\geq 0}$, together with a Wiener--Hopf decomposition of an auxiliary (bivariate) L\'evy process, with a probabilistic point of view. This provides an interpretation for the asymptotic behavior of the persistence probabilities, and in particular for the exponent $\theta$, which we write as $\theta = \rho \beta$, with $\beta$ the scaling exponent of the local time of $(X_{t})_{t\geq 0}$ at level $0$ and $\rho$ the (asymptotic) positivity parameter of the auxiliary L\'evy process.

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arXiv2023

Collective vs. individual behaviour for sums of i.i.d. random variables: appearance of the one-big-jump phenomenon

This article studies large and local large deviations for sums of i.i.d. real-valued random variables in the domain of attraction of an $\alpha$-stable law, $\alpha\in (0,2]$, with emphasis on the case $\alpha=2$. There are two different scenarios: either the deviation is realised via a collective behaviour with all summands contributing to the deviation (a Gaussian scenario), or a single summand is atypically large and contributes to the deviation (a one-big-jump scenario). Such results are known when $\alpha \in (0,2)$ (large deviations always follow a one big-jump scenario) or when the random variables admit a moment of order $2+\delta$ for some $\delta>0$. We extend these results, including in particular the case where the right tail is regularly varying with index $-2$ (treating cases with infinite variance in the domain of attraction of the normal law). We identify the threshold for the transition between the Gaussian and the one-big-jump regimes; it is slightly larger when considering local large deviations compared to integral large deviations. Additionally, we complement our results by describing the behaviour of the sum and of the largest summand conditionally on a (local) large deviation, for any $\alpha\in (0,2]$, both in the Gaussian and in the one-big-jump regimes. As an application, we show how our results can be used in the study of condensation phenomenon in the zero-range process at the critical density, extending the range of parameters previously considered in the literature.

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arXiv2022

Scaling limit of the disordered generalized Poland--Scheraga model for DNA denaturation

The Poland--Scheraga model, introduced in the 1970's, is a reference model to describe the denaturation transition of DNA. More recently, it has been generalized in order to allow for asymmetry in the strands lengths and in the formation of loops: the mathematical representation is based on a bivariate renewal process, that describes the pairs of bases that bond together. In this paper, we consider a disordered version of the model, in which the two strands interact via a potential $\beta V(\hat\omega_i,\bar\omega_j)+h$ when the $i$-th monomer of the first strand and the $j$-th monomer of the second strand meet. Here, $h\in\mathbb R$ is a homogeneous pinning parameter, $(\hat\omega_i)_{i\geq 1}$ and $(\bar\omega_j)_{j\geq 1}$ are two sequences of i.i.d.~random variables attached to each DNA strand, $V(\cdot,\cdot)$ is an interaction function and $\beta>0$ is the disorder intensity. Our main result finds some condition on the underlying bivariate renewal so that, if one takes $\beta,h\downarrow0$ at some appropriate (explicit) rate as the length of the strands go to infinity, the partition function of the model admits a non-trivial, i.e. disordered, scaling limit. This is known as an \textit{intermediate disorder} regime and is linked to the question of disorder relevance for the denaturation transition. Interestingly and surprisingly, the rate at which one has to take $\beta\downarrow0$ depends on the interaction function $V(\cdot,\cdot)$ and on the distribution of $(\hat\omega_i)_{i\geq 1}$, $(\bar\omega_j)_{j\geq 1}$. On the other hand, the intermediate disorder limit of the partition function, when it exists, is universal: it is expressed as a chaos expansion of iterated integrals against a Gaussian process~$\mathcal{M}$, which arises as the scaling limit of the field $(e^{\beta V(\hat\omega_i,\bar\omega_j)})_{i,j\geq 0}$ and exhibits strong correlations on lines and columns.

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arXiv2021

The stochastic heat equation with multiplicative L\'evy noise: Existence, moments, and intermittency

We study the stochastic heat equation (SHE) $\partial_t u = \frac12 \Delta u + \beta u \xi$ driven by a multiplicative L\'evy noise $\xi$ with positive jumps and amplitude $\beta>0$, in arbitrary dimension $d\geq 1$. We prove the existence of solutions under an optimal condition if $d=1,2$ and a close-to-optimal condition if $d\geq3$. Under an assumption that is general enough to include stable noises, we further prove that the solution is unique. By establishing tight moment bounds on the multiple L\'evy integrals arising in the chaos decomposition of $u$, we further show that the solution has finite $p$th moments for $p>0$ whenever the noise does. Finally, for any $p>0$, we derive upper and lower bounds on the moment Lyapunov exponents of order $p$ of the solution, which are asymptotically sharp in the limit as $\beta\to0$. One of our most striking findings is that the solution to the SHE exhibits a property called strong intermittency (which implies moment intermittency of all orders $p>1$ and pathwise mass concentration of the solution), for any non-trivial L\'evy measure, at any disorder intensity $\beta>0$, in any dimension $d\geq1$.

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arXiv2021

Non-directed polymers in heavy-tail random environment in dimension $d\geq 2$

In this article we study a \emph{non-directed} polymer model in dimension $d\ge 2$: we consider a simple symmetric random walk on $\mathbb{Z}^d$ which interacts with a random environment, represented by i.i.d. random variables $(\omega_x)_{x\in \mathbb{Z}^d}$. The model consists in modifying the law of the random walk up to time (or length) $N$ by the exponential of $\sum_{x\in \mathcal{R}_N}\beta (\omega_x-h)$ where $\mathcal{R}_N$ is the range of the walk, \textit{i.e.} the set of visited sites up to time $N$, and $\beta\geq 0,\, h\in \mathbb{R}$ are two parameters. We study the behavior of the model in a weak-coupling regime, that is taking $\beta:=\beta_N$ vanishing as the length $N$ goes to infinity, and in the case where the random variables $\omega$ have a heavy tail with exponent $\alpha\in (0,d)$. We are able to obtain precisely the behavior of polymer trajectories under all possible weak-coupling regimes $\beta_N = \hat \beta N^{-\gamma}$ with $\gamma \geq 0$: we find the correct transversal fluctuation exponent $\xi$ for the polymer (it depends on $\alpha$ and $\gamma$) and we give the limiting distribution of the rescaled log-partition function. This extends existing works to the non-directed case and to higher dimensions.

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