Maximum of a log-correlated Gaussian field

We study the maximum of a Gaussian field on [0,1]^\d (\d \geq 1) whose correlations decay logarithmically with the distance. Kahane \cite{Kah85} introduced this model to construct mathematically the Gaussian multiplicative chaos in the subcritical case. Duplantier, Rhodes, Sheffield and Vargas \cite{DRSV12a} \cite{DRSV12b} extended Kahane's construction to the critical case and established the KPZ formula at criticality. Moreover, they made in \cite{DRSV12a} several conjectures on the supercritical case and on the maximum of this Gaussian field. In this paper we resolve Conjecture 12 in \cite{DRSV12a}: we establish the convergence in law of the maximum and show that the limit law is the Gumbel distribution convoluted by the limit of the derivative martingale

The glassy phase of complex branching Brownian motion

In this paper, we study complex valued branching Brownian motion in the so-called glassy phase, or also called phase II. In this context, we prove a limit theorem for the complex partition function hence confirming a conjecture formulated by Lacoin and the last two authors in a previous paper on complex Gaussian multiplicative chaos. We will show that the limiting partition function can be expressed as a product of a Gaussian random variable, mainly due to the windings of the phase, and a stable transform of the so called derivative martingale, mainly due to the clustering of the modulus. The proof relies on the fine description of the extremal process available in the branching Brownian motion context.Comment: 23 pages; added references and a few details in the proof

Glassy phase and freezing of log-correlated Gaussian potentials

International audienceIn this paper, we consider the Gibbs measure associated to a logarithmically correlated random potential (including two dimensional free fields) at low temperature. We prove that the energy landscape freezes and enters in the so-called glassy phase. The limiting Gibbs weights are integrated atomic random measures with random intensity expressed in terms of the critical Gaussian multiplicative chaos constructed in \cite{Rnew7,Rnew12}. This could be seen as a first rigorous step in the renormalization theory of super-critical Gaussian multiplicative chaos

Branching random walks and log-correlated Gaussian fields

Nous étudions le modèle de la marche aléatoire branchante. Nous obtenons d'abord des résultats concernant le processus ponctuel formé par les particules extrémales, résolvant ainsi une conjecture de Brunet et Derrida 2010 [36]. Ensuite, nous établissons la dérivée au point critique de la limite des martingales additives complétant ainsi l'étude initiée par Biggins [23]. Ces deux travaux reposent sur les techniques modernes de décompositions épinales de la marche aléatoire branchante, originairement développées par Chauvin, Rouault et Wakolbinger [41], Lyons, Pemantle et Peres [74], Lyons [73] et Biggins et Kyprianou [24]. Le dernier chapitre de la thèse porte sur un champ Gaussien log-correle introduit par Kahane 1985 [61]. Via de récents travaux comme ceux de Allez, Rhodes et Vargas [11], Duplantier, Rhodes, Sheeld et Vargas [46] [47], ce modèle a connu un important regain d'intérêt. La construction du chaos multiplicatif Gaussien dans le cas critique a notamment été prouvée dans [46]. S'inspirant des techniques utilisées pour la marche aléatoire branchante nous résolvons une conjecture de [46] concernant le maximum de ce champ Gaussien.We study the model of the branching random walk. First we obtain some results concerning thepoint process formed by the extremal particles, proving a Brunet and Derrida's conjecture [36] as well. Thenwe establish the derivative of the additive martingale limit at the critical point, completing the study initiatedby Biggins [23]. These two works rely on the spinal decomposition of the branching random walk, originallyintroduced by Chauvin, Rouault and Wakolbinger [41], Lyons, Pemantle and Peres [74], Lyons [73] and Bigginsand Kyprianou [24].The last chapter of the thesis deals with a log-correlated Gaussian field introduced by Kahane [61]. Thismodel was recently revived in particular by Allez, Rhodes and Vargas [11], and Duplantier, Rhodes, Shefield andVargas [46] [47]. Inspired by the techniques used for branching random walk we solved a conjecture of Duplantier,Rhodes, Shefield and Vargas [46], on the maximum of this Gaussian field

Continuity estimates for the complex cascade model on the phase boundary

We consider the complex branching random walk on a dyadic tree with Gaussian weights on the boundary between the diffuse phase and the glassy phase. We study the branching random walk in the space of continuous functions and establish convergence in this space. The main difficulty here is that the expected modulus of continuity of the limit is too weak in order to show tightness in the space of continuous functions by means of standard tools from the theory of stochastic processes