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Shirshendu Ganguly

Publications and source records attributed to Shirshendu Ganguly.

At least 19 recordsLinked to original sources

Sharp decay thresholds for eigenvalues of discrete Schrödinger operators on $\mathbb{Z}^2$

We study eigenvalues of discrete Schrödinger operators $H=Δ+V$ on $\mathbb{Z}^2$, where $Δ$ is the uncentered Laplacian, i.e., the un-normalized adjacency operator of $\mathbb{Z}^2$ and $V$ decays at infinity. By Weyl's theorem, the essential spectrum of $H$ is $[-4,4]$. We determine the sharp decay thresholds for existence of eigenvalues in three distinct spectral regimes. While it is natural to expect different behavior at the spectral edge $λ=\pm4$, and the bulk, there is a further distinction between the regular energies $0<|λ|<4$ and the interior critical energy $λ=0$ stemming from the reducibility of the corresponding Fermi surface in the latter case. For every $0<|λ|<4$, we construct potentials $V$ satisfying $|V(n)|\leq C|n|^{-1}$ for which $λ$ is an eigenvalue of $Δ+V$, and prove absence of eigenvalues when $|V(n)|\leq C|n|^{-1-\varepsilon}$ for some $\varepsilon>0$. At $λ=0$, the critical power changes and we construct potentials $V$ satisfying $|V(n)|\leq C|n| ^{-2}$ for which $0$ is an eigenvalue of $Δ+V$, as well as prove absence when $|V(n)|\leq C|n|^{-2-\varepsilon}$ for any $\varepsilon>0$. Finally, at each spectral edge, we show that, for every $K\geq3$, an eigenvalue can be created by potentials supported on exactly $K$ sites, whereas a potential supported on at most two sites cannot create an edge eigenvalue. The proofs combine Green-function expansions and moment cancellation, Hilbert-space-valued iterations, discrete Carleman estimates, and a uniform Green-kernel estimate.

math-ph

Logarithmic intermittency of the critical 2D SHF

While the solution to the $1+1$ dimensional stochastic heat equation with multiplicative noise is closely related to the exponential of a Brownian motion, the two-dimensional picture exhibits an additional weak-to-strong disorder transition. In [CSZ '23], the critical two-dimensional stochastic heat flow (SHF) was constructed as the scaling limit of the partition function of $2+1$ dimensional directed polymers under the logarithmic intermediate-disorder scaling at criticality. The SHF is a random measure and, like many naturally occurring random measures, it is expected to exhibit rich intermittency. [CSZ '25] established that it is almost surely singular with respect to the Lebesgue measure. More recently, [GT '26] showed that the logarithm of the SHF averaged over small balls is asymptotically Gaussian, with both its mean and variance diverging as the ball radius tends to zero. In this paper we prove a sharp result quantifying the singularity of the support of the SHF as well as its intermittency. In particular, we show that, almost surely, for all small $\varepsilon>0$, up to a vanishing error, all the mass of the point-to-plane SHF in any domain is concentrated on ${1}/{\big(\varepsilon^2\log^{1/2+o(1)}(1/\varepsilon)\big)}$ balls of radius $\varepsilon$, each containing $\varepsilon^2{\log^{1/2+o(1)}(1/\varepsilon)}$ mass, thus precisely establishing its logarithmic fractal behavior. A key ingredient in the proof is a refined large-deviations theory, which allows access to conditional distributions, by taking advantage of the Gaussian-like behavior of the SHF at quasi-critical scales. A further useful observation that features prominently is that conditioning a Brownian motion on its endpoint being unusually large essentially induces a shift in the mean of its increments, and consequently, at small enough scales, their distributions do not alter significantly.

math.PR

Correlation decay in area-tilted line ensembles

Random surfaces on a hard substrate often exhibit entropic repulsion, wherein the surface is propelled upwards to allow entropically preferable downward fluctuations. A particularly rich class of examples arises from the low-temperature 3D Ising model. A powerful approach to studying such surfaces is through their level curves, which form a family of non-intersecting random curves. In [CIW18, CIW19], an ensemble of Brownian lines with geometrically increasing area tilts was proposed as a putative limiting model in this case. This model falls outside the scope of techniques based on integrable or SDE structures, which have been key ingredients in the study of the Airy line ensemble. A particularly intriguing question about such line ensembles concerns their mixing properties when viewed as a Markov process, and in particular the rate of decay of correlations in time. For the Airy line ensemble, this decay is known to be inverse quadratic. The first quantitative bound on the decay of correlations in the area-tilted model, established in [CG25], was slower than polynomial in time. An earlier result [DLZ24] had established positivity of the spectral gap for the finite-line version of the ensemble, without quantitative bounds. This left open the important question of the true decay rate of correlations for the infinite ensemble. Settling this question for sufficiently large area-tilt strength, corresponding to sufficiently low temperature for the 3D Ising model, we prove exponential decay of correlations for the infinite ensemble and a uniform (in the number of lines) positive spectral gap for the finite ensemble. Our proof is based on establishing a precise form of separation of scales between curves of different indices, using a novel probabilistic approach involving embedding supercritical branching processes in the line ensemble.

math.PR

Last passage percolation in hierarchical environments

Last passage percolation (LPP) is a model of a directed metric and a zero-temperature polymer where the main observable is a directed path evolving in a random environment accruing as energy the sum of the random weights along itself. When the environment has light tails and a fast decay of correlation, the fluctuations of LPP are predicted to be explained by the Kardar-Parisi-Zhang (KPZ) universality theory. However, the KPZ theory is not expected to apply for many natural environments, particularly "critical" ones exhibiting a hierarchical structure often leading to logarithmic correlations. In this article, we initiate a novel study of LPP in such hierarchical environments by investigating two particularly interesting examples. The first is an i.i.d. environment but with a power-law distribution with an inverse quadratic tail decay which is conjectured to be the critical point for the validity of the KPZ scaling relation. The second is the Branching Random Walk which is a hierarchical approximation of the two-dimensional Gaussian Free Field. The second example may be viewed as a high-temperature (weak coupling) directed version of Liouville Quantum Gravity, which is a model of random geometry driven by the exponential of a logarithmically correlated field. Due to the underlying fractal structure, LPP in such environments is expected to exhibit logarithmic correction terms with novel critical exponents. While discussions about such critical models appear in the physics literature, precise predictions about exponents seem to be missing. Developing a framework based on multi-scale analysis, we obtain bounds on such exponents and prove almost optimal concentration results in all dimensions for both models. As a byproduct of our analysis we answer a long-standing question of Martin on necessary and sufficient conditions for the linear growth of the LPP energy in i.i.d. environments.

math.PR

Temperature chaos in directed polymers

Disordered systems such as spin glasses and polymers characteristically exhibit random energy landscapes with many macroscopically separated energetic valleys corresponding to near-ground states. This high complexity renders these systems extremely sensitive to perturbations of external parameters. For instance, the support of associated Gibbs measures may change macroscopically under such perturbations, a phenomenon known as chaos in the literature. In experiments, chaotic phenomena are typically studied via temperature perturbations. In this article, we initiate the rigorous study of temperature-chaotic properties of the continuum directed random polymer (CDRP), a canonical model in the KPZ universality class. The CDRP is driven by white noise and is parametrized by inverse temperature $β$, and is known [Wu '26, Das-Zhu '24] to converge in the zero-temperature limit $β\to \infty$ to the directed landscape constructed in [Dauvergne-Ortmann-Virág '22], the putative universal scaling limit of models in the KPZ universality class. The main result of this article considers the CDRP free energies coupled through the same white noise at a pair of inverse temperatures $(β_1, β_2)$, and shows that they decouple in the limit $β_2 \gg β_1 \gg 1$, converging to a pair of independent directed landscapes. This is the first such "energetic de-correlation across temperatures" result. Our key estimate measures the "pivotality" or "influence" of spatially thin strips in models of last passage percolation. As a byproduct, the proof strategy also allows to show that the directed landscape is a two-dimensional black noise (in the sense of [Tsirelson-Vershik '98]), previously conjectured by Virág. This provides the third known example of a two-dimensional black noise after critical planar percolation [Schramm-Smirnov '11] and the Brownian web [Ellis-Feldheim '16].

math.PR

Branch lengths for geodesics in the directed landscape and mutation patterns in growing spatially structured populations

Consider a population that is expanding in two-dimensional space. Suppose we collect data from a sample of individuals taken at random either from the entire population, or from near the outer boundary of the population. A quantity of interest in population genetics is the site frequency spectrum, which is the number of mutations that appear on $k$ of the $n$ sampled individuals, for $k = 1, \dots, n-1$. As long as the mutation rate is constant, this number will be roughly proportional to the total length of all branches in the genealogical tree that are on the ancestral line of $k$ sampled individuals. While the rigorous literature has primarily focused on models without any spatial structure, in many natural settings, such as tumors or bacteria colonies, growth is dictated by spatial constraints. Many such two dimensional growth models are expected to fall in the KPZ universality class. In this article we adopt the perspective that for population models in the KPZ universality class, the genealogical tree can be approximated by the tree formed by the infinite upward geodesics in the directed landscape, a universal scaling limit constructed in \cite{dov22}, starting from $n$ randomly chosen points. Relying on geodesic coalescence, we prove new asymptotic results for the lengths of the portions of these geodesics that are ancestral to $k$ of the $n$ sampled points and consequently obtain exponents driving the site frequency spectrum as predicted in \cite{fgkah16}. An important ingredient in the proof is a new tight estimate of the probability that three infinite upward geodesics stay disjoint up to time $t$, i.e., a sharp quantitative version of the well studied N3G problem, which is of independent interest.

math.PR

van den Berg-Kesten--type correlation inequalities for disjoint polymers in the KPZ universality class

In classical percolation theory, the van den Berg-Kesten (BK) inequality is a fundamental tool that shows that disjoint events induce negative conditionings on each other. The inequality also holds in the context of last passage percolation (LPP), which is the zero temperature limit of polymer models and an important subclass in the Kardar-Parisi-Zhang (KPZ) universality class. Recently, an analog of the BK inequality was discovered in the context of zero temperature line ensembles and the scaling limit of LPP, where it was used to study upper tail probabilities of the weight and the scaling limit of geodesics under such upper tail conditionings. However, while it has become apparent that such an inequality in the positive temperature setting would have a number of applications, it seems likely that a direct generalization of the zero temperature inequality would not hold. In this work we prove a version of the BK inequality for the KPZ line ensemble and the continuum directed random polymer. We do so by working with the log gamma polymer, making use of its integrability and the geometric RSK correspondence. Our inequality serves as a key input in analyzing the KPZ line ensemble and proving sharp upper tail estimates of the KPZ equation in arXiv:2208.08922, and proving convergence of the continuum directed random polymer to Brownian bridge under the upper tail event in arXiv:2311.12009. The crucial role of integrability in the validity of such an inequality is highlighted via a counter-example for a non-integrable model.

math.PR

Sharp upper tail behavior of line ensembles via the tangent method

We develop a new probabilistic and geometric method to obtain several sharp results pertaining to the upper tail behavior of continuum Gibbs measures on infinite ensembles of random continuous curves, also known as line ensembles, satisfying some natural assumptions. The arguments make crucial use of Brownian resampling invariance properties and correlation inequalities admitted by such Gibbs measures. We obtain sharp one-point upper tail estimates showing that the probability of the value at zero being larger than $θ$ is $\exp(-\frac{4}{3}θ^{3/2}(1+o(1)))$. A key intermediate step is developing a precise understanding of the profile when conditioned on the value at zero equaling $θ$. Our method further allows one to obtain multi-point asymptotics which were out of reach of previous approaches. As an example, we prove sharp explicit two-point upper tail estimates. This framework is then used to establish the corresponding results for the KPZ equation, which are all new. Even for the zero-temperature case of the Airy$_2$ process, our arguments yield new proofs for one-point estimates previously known due to its connections to random matrix theory, as well as new two-point asymptotics. To showcase the reach of the method, we obtain the same results in a purely non-integrable setting under only assumptions of stationarity and extremality in the class of Gibbs measures. Our method bears resemblance to the tangent method introduced by Colomo-Sportiello and mathematically realized by Aggarwal in the context of the six-vertex model.

math.PR

Brownian bridge limit of path measures in the upper tail of KPZ models

For models in the KPZ universality class, such as the zero temperature model of planar last passage-percolation (LPP) and the positive temperature model of directed polymers, its upper tail behavior has been a topic of recent interest, with particular focus on the associated path measures (i.e., geodesics or polymers). For Exponential LPP, diffusive fluctuation had been established in Basu-Ganguly. In the directed landscape, the continuum limit of LPP, the limiting Gaussianity at one point, as well as of related finite-dimensional distributions of the KPZ fixed point, were established, using exact formulas in Liu and Wang-Liu. It was further conjectured in these works that the limit of the corresponding geodesic should be a Brownian bridge. We prove it in both zero and positive temperatures; for the latter, neither the one-point limit nor the scale of fluctuations was previously known. Instead of relying on formulas (which are still missing in the positive temperature literature), our arguments are geometric and probabilistic, using the results on the shape of the weight and free energy profiles under the upper tail from Ganguly-Hegde as a starting point. Another key ingredient involves novel coalescence estimates, developed using the recently discovered shift-invariance Borodin-Gorin-Wheeler in these models. Finally, our proof also yields insight into the structure of the polymer measure under the upper tail conditioning, establishing a quenched localization exponent around a random backbone.

math.PR

Decoupling of clusters in independent sets in a percolated hypercube

Independent sets in graphs are sets of vertices containing no neighbors, and they represent a canonical spin system with hardcore constraints. Of particular interest is the setting of the boolean hypercube, where counting independent sets was the original motivator for Sapozhenko's famous graph container method. A modern perspective on such problems is to consider the effect of disorder, and the study of independent sets in random subgraphs of the hypercube obtained via bond percolation with parameter $p$ was initiated by Kronenberg and Spinka. They employed tools from statistical mechanics to obtain detailed information about the moments of the number of independent sets (now a random variable), and posed many interesting questions. Previous work by the authors addressed many of these questions in the regime $p \geq \frac{2}{3}$, where the behavior is relatively simple and can be modeled well by a related family of independent particles. As $p$ decreases, though, typical independent sets become larger and feature more intricate clustering behavior. In the present article we overcome many of the challenges presented by this phenomenon and analyze the model for all $p> 0.465$. We obtain a sharp in-probability approximation for the number of independent sets in the percolated hypercube in terms of explicit random variables, as well as provide a sampling algorithm. Note that this shows, curiously, that $p = \frac{1}{2}$ is not a natural barrier for this problem unlike in many other problems where it appears as a point of a phase transition. A key contribution of this work is the introduction of a new probabilistic framework to handle the clustering behavior for these low values of $p$. Although our analysis is restricted to $p > 0.465$, our arguments are expected to be helpful for studying this model at even lower values of $p$, and possibly for other related problems.

math.PR

On quantum to classical comparison for Davies generators

Despite extensive study, our understanding of quantum Markov chains remains far less complete than that of their classical counterparts. [Temme'13] observed that the Davies Lindbladian, a well-studied model of quantum Markov dynamics, contains an embedded classical Markov generator, raising the natural question of how the convergence properties of the quantum and classical dynamics are related. While [Temme'13] showed that the spectral gap of the Davies Lindbladian can be much smaller than that of the embedded classical generator for certain highly structured Hamiltonians, we show that if the spectrum of the Hamiltonian does not contain long arithmetic progressions, then the two spectral gaps must be comparable. As a consequence, we prove that for a large class of Hamiltonians, including those obtained by perturbing a fixed Hamiltonian with a generic external field, the quantum spectral gap remains within a constant factor of the classical spectral gap. Our result aligns with physical intuition and enables the application of classical Markov chain techniques to the quantum setting. The proof is based on showing that any ``off-diagonal'' eigenvector of the Davies generator can be used to construct an observable which commutes with the Hamiltonian and has a Lindbladian Rayleigh quotient which can be upper bounded in terms of that of the original eigenvector's Lindbladian Rayleigh quotient. Thus, a spectral gap for such observables implies a spectral gap for the full Davies generator.

quant-ph

Unique continuation on planar graphs

We show that a discrete harmonic function which is bounded on a large portion of a periodic planar graph is constant. A key ingredient is a new unique continuation result for the weighted graph Laplacian. The proof relies on the structure of level sets of discrete harmonic functions, using arguments as in Bou-Rabee--Cooperman--Dario (2023) which exploit the fact that, on a planar graph, the sub- and super-level sets cannot cross over each other. In the special case of the square lattice this yields a new, geometric proof of the Liouville theorem of Buhovsky--Logunov--Malinnikova--Sodin (2017).

math.AP

Sharp moment and upper tail asymptotics for the critical $2d$ Stochastic Heat Flow

While $1+1$ dimensional growth models in the Kardar-Parisi-Zhang universality class have witnessed an explosion of activity, higher dimensional models remain much less explored. The special case of $2+1$ dimensions is particularly interesting as it is, in physics parlance, neither ultraviolet nor infrared super-renormalizable. Canonical examples include the stochastic heat equation (SHE) with multiplicative noise and directed polymers. The models exhibit a weak to strong disorder transition as the inverse temperature, up to a logarithmic (in the system size) scaling, crosses a critical value. While the sub-critical picture has been established in detail, very recently [CSZ '23] constructed a scaling limit of the critical $2+1$ dimensional directed polymer partition function, termed as the critical $2d$ Stochastic Heat Flow (SHF), a random measure on $\mathbb{R}^2.$ The SHF is expected to exhibit a rich intermittent behavior and consequently a rapid growth of its moments. The $h^{th}$ moment was known to grow at least as $\exp(Ω(h^{2}))$ (a consequence of the Gaussian correlation inequality) and at most as $\exp(\exp (O(h^2)))$. The true growth rate, however, was predicted to be $\exp(\exp (Θ(h)))$ in the late nineties [R '99]. In this paper we prove a lower bound of the $h^{th}$ moment which matches the predicted value, thereby exponentially improving the previous lower bound. We also obtain rather sharp bounds on its upper tail. The key ingredient in the proof involves establishing a new connection of the SHF and moments thereof to the Gaussian Free Field (GFF) on related Feynman diagrams. This connection opens the door to the rich algebraic structure of the GFF to study the SHF. Along the way we also prove a new monotonicity property of the correlation kernel for the SHF as a consequence of the domain Markov property of the GFF.

math.PR

Spectral properties of the zero temperature Edwards-Anderson model

An Ising model with random couplings on a graph is a model of a spin glass. While the mean field case of the Sherrington-Kirkpatrick model is very well studied, the more realistic lattice setting, known as the Edwards-Anderson (EA) model, has witnessed rather limited progress. In (Chatterjee,'23) chaotic properties of the ground state in the EA model were established via the study of the Fourier spectrum of the two-point spin correlation. A natural direction of research concerns fractal properties of the Fourier spectrum in analogy with critical percolation. In particular, numerical findings (Bray, Moore,'87) seem to support the belief that the fractal dimension of the associated spectral sample drawn according to the Fourier spectrum is strictly bigger than one. Towards this, in this note we introduce a percolation-type argument, relying on the construction of ``barriers'', to obtain new probabilistic lower bounds on the size of the spectral sample.

math.PR

Invariance principle for the Gaussian Multiplicative Chaos via a high dimensional CLT with low rank increments

Gaussian multiplicative chaos (GMC) is a canonical random fractal measure obtained by exponentiating log-correlated Gaussian processes, first constructed in the seminal work of Kahane (1985). Since then it has served as an important building block in constructions of quantum field theories and Liouville quantum gravity. However, in many natural settings, non-Gaussian log-correlated processes arise. In this paper, we investigate the universality of GMC through an invariance principle. We consider the model of a random Fourier series, a process known to be log-correlated. While the Gaussian Fourier series has been a classical object of study, recently, the non-Gaussian counterpart was investigated and the associated multiplicative chaos constructed by Junnila in 2016. We show that the Gaussian and non-Gaussian variables can be coupled so that the associated chaos measures are almost surely mutually absolutely continuous throughout the entire sub-critical regime. This solves the main open problem from Kim and Kriechbaum (2024) who had earlier established such a result for a part of the regime. The main ingredient is a new high dimensional CLT for a sum of independent (but not i.i.d.) random vectors belonging to rank one subspaces with error bounds involving the isotropic properties of the covariance matrix of the sum, which we expect will find other applications. The proof relies on a path-wise analysis of Skorokhod embeddings as well as a perturbative result about square roots of positive semi-definite matrices which, surprisingly, appears to be new.

math.PR

Critical level set percolation for the GFF in $d>6$: comparison principles and some consequences

The intrinsic geometry of the critical percolation cluster induced by the level set of the metric Gaussian free field on $\mathbb{Z}^{d}$ has been the subject of much recent activity. (Lupu, 2016) established that the critical percolation cluster has the same law as that in a Poisson loop soup where the intensity is dictated by the Green's function of the usual random walk. A sharp Euclidean one arm exponent was proven recently in (Cai and Ding, 2023), and subsequently in (Ganguly and Nam, 2024) other results about the chemical one arm exponent, volume growth and the Alexander-Orbach conjecture were established for all $d>20.$ In this article, we introduce new methods to obtain several sharp estimates about the intrinsic geometry which hold for all $d>6$. We develop two primary comparison methods. The first involves a comparison of the extrinsic (Euclidean) and intrinsic metrics allowing estimates about the former to be transferrable to the latter. The second compares intrinsic geodesics to a class of modified paths which are non-backtracking in a certain loop sense. The latter is amenable to analysis using methods of bond percolation. We finally prove that such non-backtracking paths are not much longer than geodesics allowing us to establish comparable estimates for the geodesic. As applications of such methods, we establish, for all $d>6,$ the chemical one-arm exponent, as well as an averaged version of a conjecture from (Werner, 2021) which asserts that deletion of loops with diameter larger than $r^{6/d}$ do not affect the connection probabilities between points at Euclidean distance $r.$ An important ingredient of independent interest is a local connectivity estimate which asserts that the connection probability between two points at distance $r$ remains, up to constants, unchanged even if the connecting path is confined to a ball of diameter comparable to $r.$

math.PR

Gaussian to log-normal transition for independent sets in a percolated hypercube

Independent sets in graphs, i.e., subsets of vertices where no two are adjacent, have long been studied, for instance as a model of hard-core gas. The $d$-dimensional hypercube, $\{0,1\}^d$, with the nearest neighbor structure, has been a particularly appealing choice for the base graph, owing in part to its many symmetries. Results go back to the work of Korshunov and Sapozhenko who proved sharp results on the count of such sets as well as structure theorems for random samples drawn uniformly. Of much interest is the behavior of such Gibbs measures in the presence of disorder. In this direction, Kronenberg and Spinka [KS] initiated the study of independent sets in a random subgraph of the hypercube obtained by considering an instance of bond percolation with probability $p$. Relying on tools from statistical mechanics they obtained a detailed understanding of the moments of the partition function, say $\mathcal{Z}$, of the hard-core model on such random graphs and consequently deduced certain fluctuation information, as well as posed a series of interesting questions. In particular, they showed in the uniform case that there is a natural phase transition at $p=2/3$ where $\mathcal{Z}$ transitions from being concentrated for $p>2/3$ to not concentrated at $p=2/3$. In this article, developing a probabilistic framework, as well as relying on certain cluster expansion inputs from [KS], we present a detailed picture of both the fluctuations of $\mathcal{Z}$ as well as the geometry of a randomly sampled independent set. In particular, we establish that $\mathcal{Z}$, properly centered and scaled, converges to a standard Gaussian for $p>2/3$, and to a sum of two i.i.d. log-normals at $p=2/3$. A particular step in the proof which could be of independent interest involves a non-uniform birthday problem for which collisions emerge at $p=2/3$.

math.PR

Stability and chaos in dynamical last passage percolation

Many complex statistical mechanical models have intricate energy landscapes. The ground state, or lowest energy state, lies at the base of the deepest valley. In examples such as spin glasses and Gaussian polymers, there are many valleys; the abundance of near-ground states (at the base of valleys) indicates the phenomenon of chaos, under which the ground state alters profoundly when the model's disorder is slightly perturbed. In this article, we compute the critical exponent that governs the onset of chaos in a dynamic manifestation of a canonical model in the Kardar-Parisi-Zhang [KPZ] universality class, Brownian last passage percolation [LPP]. In this model in its static form, semi-discrete polymers advance through Brownian noise, their energy given by the integral of the white noise encountered along their journey. A ground state is a geodesic, of extremal energy given its endpoints. We perturb Brownian LPP by evolving the disorder under an Ornstein-Uhlenbeck flow. We prove that, for polymers of length $n$, a sharp phase transition marking the onset of chaos is witnessed at the critical time $n^{-1/3}$. Indeed, the overlap between the geodesics at times zero and $t > 0$ that travel a given distance of order $n$ will be shown to be of order $n$ when $t\ll n^{-1/3}$; and to be of smaller order when $t\gg n^{-1/3}$. We expect this exponent to be shared among many interface models. The present work thus sheds light on the dynamical aspect of the KPZ class; it builds on several recent advances. These include Chatterjee's harmonic analytic theory [Cha14] of equivalence of superconcentration and chaos in Gaussian spaces; a refined understanding of the static landscape geometry of Brownian LPP developed in the companion paper [GH20]; and, underlying the latter, strong comparison estimates of the geodesic energy profile to Brownian motion in [CHH19].

math.PR