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Shirshendu Ganguly

Publications and source records attributed to Shirshendu Ganguly.

At least 55 records · Page 3Linked to original sources

arXiv2021

Environment seen from infinite geodesics in Liouville Quantum Gravity

First passage percolation (FPP) on $\mathbb{Z}^d$ or $\mathbb{R}^d$ is a canonical model of a random metric space where the standard Euclidean geometry is distorted by random noise. Of central interest is the length and the geometry of the geodesic, the shortest path between points. Since the latter, owing to its length minimization, traverses through atypically low values of the underlying noise variables, it is an important problem to quantify the disparity between the environment rooted at a point on the geodesic and the typical one. We investigate this in the context of $γ$-Liouville Quantum Gravity (LQG) (where $γ\in (0,2)$ is a parameter) -- a random Riemannian surface induced on the complex plane by the random metric tensor $e^{2γh/d_γ} ({dx^2+dy^2}),$ where $h$ is the whole plane, properly centered, Gaussian Free Field (GFF), and $d_γ$ is the associated dimension. We consider the unique infinite geodesic $Γ$ from the origin, parametrized by the logarithm of its chemical length, and show that, for an almost sure realization of $h$, the distributions of the appropriately scaled field and the induced metric on a ball, rooted at a point "uniformly" sampled on $Γ$, converge to deterministic measures on the space of generalized functions and continuous metrics on the unit disk respectively. Moreover, we show that the limiting objects living on the unit disk are singular with respect to their typical counterparts, but become absolutely continuous away from the origin. Our arguments rely on unearthing a regeneration structure with fast decay of correlation in the geodesic owing to coalescence and the domain Markov property of the GFF. While there have been significant recent advances around this question for stochastic planar growth models in the KPZ class, the present work initiates this research program in the context of LQG.

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arXiv2021

Chemical subdiffusivity of critical 2D percolation

We show that random walk on the incipient infinite cluster (IIC) of two-dimensional critical percolation is subdiffusive in the chemical distance (i.e., in the intrinsic graph metric). Kesten (1986) famously showed that this is true for the Euclidean distance, but it is known that the chemical distance is typically asymptotically larger. More generally, we show that subdiffusivity in the chemical distance holds for stationary random graphs of polynomial volume growth, as long as there is a multi-scale way of covering the graph so that "deep patches" have "thin backbones". Our estimates are quantitative and give explicit bounds in terms of the one and two-arm exponents $η_2 > η_1 > 0$: For $d$-dimensional models, the mean chemical displacement after $T$ steps of random walk scales asymptotically slower than $T^{1/β}$, whenever \[ β< 2 + \frac{η_2-η_1}{d-η_1}\,. \] Using the conjectured values of $η_2 = η_1 + 1/4$ and $η_1 = 5/48$ for 2D lattices, the latter quantity is $2+12/91$.

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arXiv2021

Large deviations for the largest eigenvalue of Gaussian networks with constant average degree

Large deviation behavior of the largest eigenvalue $λ_1$ of Gaussian networks (Erdős-Rényi random graphs $\mathcal{G}_{n,p}$ with i.i.d. Gaussian weights on the edges) has been the topic of considerable interest. Recently in [6,30], a powerful approach was introduced based on tilting measures by suitable spherical integrals, particularly establishing a non-universal large deviation behavior for fixed $p<1$ compared to the standard Gaussian ($p=1$) case. The case when $p\to 0$ was however completely left open with one expecting the dense behavior to hold only until the average degree is logarithmic in $n$. In this article we focus on the case of constant average degree i.e., $p=\frac{d}{n}$. We prove the following results towards a precise understanding of the large deviation behavior in this setting. 1. (Upper tail probabilities): For $δ>0,$ we pin down the exact exponent $ψ(δ)$ such that $$\mathbb{P}(λ_1\ge \sqrt{2(1+δ)\log n})=n^{-ψ(δ)+o(1)}.$$ Further, we show that conditioned on the upper tail event, with high probability, a unique maximal clique emerges with a very precise $δ$ dependent size (takes either one or two possible values) and the Gaussian weights are uniformly high in absolute value on the edges in the clique. Finally, we also prove an optimal localization result for the leading eigenvector, showing that it allocates most of its mass on the aforementioned clique which is spread uniformly across its vertices. 2. (Lower tail probabilities): The exact stretched exponential behavior of $\mathbb{P}(λ_1\le \sqrt{2(1-δ)\log n})$ is also established. As an immediate corollary, we get $λ_1 \approx \sqrt{2 \log n}$ typically, a result that surprisingly appears to be new. A key ingredient is an extremal spectral theory for weighted graphs obtained via the classical Motzkin-Straus theorem.

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arXiv2021

Local and global geometry of the 2D Ising interface in critical pre-wetting

Consider the Ising model at low-temperatures and positive external field $λ$ on an $N\times N$ box with Dobrushin boundary conditions that are plus on the north, east, and west boundaries and minus on the south boundary. If $λ= 0$, the interface separating the plus and minus phases is diffusive, having $O(\sqrt N)$ height fluctuations, and the model is fully wetted. Under an order one field, the interface fluctuations are $O(1)$ and the interface is only partially wetted, being pinned to its southern boundary. We study the critical pre-wetting regime of $λ_N \downarrow 0$, where the height fluctuations are expected to scale as $λ^{ -1/3}$ and the rescaled interface is predicted to converge to the Ferrari--Spohn diffusion. Velenik (2004) identified the order of the area under the interface up to logarithmic corrections. Since then, more refined features of such interfaces have only been identified in simpler models of random walks under area tilts. In this paper, we resolve several conjectures of Velenik regarding the refined features of the Ising interface in the critical pre-wetting regime. Our main result is a sharp bound on the one-point height fluctuation, proving $e^{ - Θ(x^{3/2})}$ upper tails reminiscent of the Tracy--Widom distribution, capturing a tradeoff between the locally Brownian oscillations and the global field effect. We further prove a concentration estimate for the number of points above which the interface attains a large height. These are used to deduce various geometric properties of the interface, including the order and tails of the area it confines, and the poly-logarithmic pre-factor governing its maximum height fluctuation. Our arguments combine classical inputs from the random-line representation of the Ising interface, with novel local resampling and coupling schemes.

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arXiv2021

Temporal Correlation in Last Passage Percolation with Flat Initial Condition via Brownian Comparison

We consider directed last passage percolation on $\mathbb{Z}^2$ with exponential passage times on the vertices. A topic of great interest is the coupling structure of the weights of geodesics as the endpoints are varied spatially and temporally. A particular specialization is when one considers geodesics to points varying in the time direction starting from a given initial data. This paper considers the flat initial condition which corresponds to line-to-point last passage times. Settling a conjecture by Ferrari and Spohn (SIGMA, 2016), we show that for the passage times from the line $x+y=0$ to the points $(r,r)$ and $(n,n)$, denoted $X_{r}$ and $X_{n}$ respectively, as $n\to \infty$ and $\frac{r}{n}$ is small but bounded away from zero, the covariance satisfies $$\mbox{Cov}(X_{r},X_{n})=Θ\left((\frac{r}{n})^{4/3+o(1)} n^{2/3}\right),$$ thereby establishing $\frac{4}{3}$ as the temporal covariance exponent. This differs from the corresponding exponent for the droplet initial condition recently rigorously established in Ferrari and Occelli (2018), Basu and Ganguly (2018), and requires novel arguments. Key ingredients include the understanding of geodesic geometry and recent advances in quantitative comparison of geodesic weight profiles to Brownian motion using the Brownian Gibbs property. The proof methods are expected to be applicable for a wider class of initial data.

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arXiv2020

Upper Tails for Edge Eigenvalues of Random Graphs

The upper tail problem for the largest eigenvalue of the Erdős--Rényi random graph $\mathcal{G}_{n,p}$ is to estimate the probability that the largest eigenvalue of the adjacency matrix of $\mathcal{G}_{n,p}$ exceeds its typical value by a factor of $1+δ$. In this note we show that for $δ>0$ fixed, and $p \rightarrow 0$ such that $n^{\frac{1}{2}} p \rightarrow \infty$, the upper tail probability for the largest eigenvalue of $\mathcal{G}_{n,p}$ is $$\exp\left[-(1+o(1)) \min\left\{\tfrac{(1+δ)^2}{2}, δ(1+δ) \right\} n^{2}p^{2}\log (1/p)\right].$$ In the same regime of $p$, we show that the second largest eigenvalue $λ_2( \mathcal G_{n,p})$ of the adjacency matrix of $\mathcal{G}_{n,p}$ satisfies $$\mathbb P(λ_2(\mathcal G_{n,p})\ge δnp) = \exp\left[-(1+o(1)) \tfrac{1}{2} δ^2n^2p^2 \log (1/p) \right],$$ where $δ=δ_n < 1$ can depend on $n$ such that $δn^{\frac{1}{2}} p \rightarrow \infty$, which covers deviations of $λ_2(\mathcal G_{n,p})$ between $n^{\frac{1}{2}}$ and $np$. Our arguments build on recent results on the large deviations of the largest eigenvalue and related non-linear functions of the adjacency matrix in terms of natural mean-field entropic variational problems.

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arXiv2020

The geometry of near ground states in Gaussian polymer models

The energy and geometry of maximizing paths in integrable last passage percolation models are governed by the characteristic KPZ scaling exponents of one-third and two-thirds. When represented in scaled coordinates that respect these exponents, this random field of paths may be viewed as a complex energy landscape. We investigate the structure of valleys and connecting pathways in this landscape. The routed weight profile $\mathbb{R} \to \mathbb{R}$ associates to $x \in \mathbb{R}$ the maximum scaled energy obtainable by a path whose scaled journey from $(0,0)$ to $(0,1)$ passes through the point $(x,1/2)$. Developing tools of Brownian Gibbs analysis from [Ham16] and [CHH19], we prove an assertion of strong similarity of this profile for Brownian last passage percolation to Brownian motion of rate two on the unit-order scale. A sharp estimate on the rarity that two macroscopically different routes in the energy landscape offer energies close to the global maximum results. We prove robust assertions concerning modulus of continuity for the energy and geometry of scaled maximizing paths, that develop the results and approach of [HS20], delivering estimates valid on all scales above the microscopic. The geometry of excursions of near ground states about the maximizing path is investigated: indeed, we estimate the energetic shortfall of scaled paths forced to closely mimic the geometry of the maximizing route while remaining disjoint from it. We also provide bounds on the approximate gradient of the maximizing path, viewed as a function, ruling out sharp steep movement down to the microscopic scale. Our results find application in a companion study [GH20a] of the stability, and fragility, of last passage percolation under a dynamical perturbation.

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arXiv2020

Information Percolation and Cutoff for the Random-Cluster Model

We consider the Random-Cluster model on $(\mathbb{Z}/n\mathbb{Z})^d$ with parameters $p \in (0,1)$ and $q\ge 1$. This is a generalization of the standard bond percolation (with open probability $p$) which is biased by a factor $q$ raised to the number of connected components. We study the well known FK-dynamics on this model where the update at an edge depends on the global geometry of the system unlike the Glauber Heat Bath dynamics for spin systems, and prove that for all small enough $p$ (depending on the dimension) and any $q>1$, the FK-dynamics exhibits the cutoff phenomenon at $λ_{\infty}^{-1}\log n$ with a window size $O(\log\log n)$, where $λ_{\infty}$ is the large $n$ limit of the spectral gap of the process. Our proof extends the Information Percolation framework of Lubetzky and Sly [21] to the Random-Cluster model and also relies on the arguments of Blanca and Sinclair [4] who proved a sharp $O(\log n)$ mixing time bound for the planar version. A key aspect of our proof is the analysis of the effect of a sequence of dependent (across time) Bernoulli percolations extracted from the graphical construction of the dynamics, on how information propagates.

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arXiv2020

Interlacing and scaling exponents for the geodesic watermelon in last passage percolation

In discrete planar last passage percolation (LPP), random values are assigned independently to each vertex in $\mathbb Z^2$, and each finite upright path in $\mathbb Z^2$ is ascribed the weight given by the sum of values of its vertices. The weight of a collection of disjoint paths is the sum of its members' weights. The notion of a geodesic, a maximum weight path between two vertices, has a natural generalization concerning several disjoint paths: a $k$-geodesic watermelon in $[1,n]^2\cap\mathbb Z^2$ is a collection of $k$ disjoint paths contained in this square that has maximum weight among all such collections. While the weights of such collections are known to be important objects, the maximizing paths have been largely unexplored beyond the $k=1$ case. For exactly solvable models, such as exponential and geometric LPP, it is well known that for $k=1$ the exponents that govern fluctuation in weight and transversal distance are $1/3$ and $2/3$; that is, typically, the weight of the geodesic on the route $(1,1) \to (n,n)$ fluctuates around a dominant linear growth of the form $μn$ by the order of $n^{1/3}$; and the maximum Euclidean distance of the geodesic from the diagonal has order $n^{2/3}$. Assuming a strong but local form of convexity and one-point moderate deviation bounds for the geodesic weight profile---which are available in all known exactly solvable models---we establish that, typically, the $k$-geodesic watermelon's weight falls below $μnk$ by order $k^{5/3}n^{1/3}$, and its transversal fluctuation is of order $k^{1/3}n^{2/3}$. Our arguments crucially rely on, and develop, a remarkable deterministic interlacing property that the watermelons admit. Our methods also yield sharp rigidity estimates for naturally associated point processes, which improve on estimates obtained via tools from the theory of determinantal point processes available in the integrable setting.

math.PR↗

arXiv2020

Recovery and Rigidity in a Regular Stochastic Block Model

The stochastic block model is a natural model for studying community detection in random networks. Its clustering properties have been extensively studied in the statistics, physics and computer science literature. Recently this area has experienced major mathematical breakthroughs, particularly for the binary (two-community) version, see Mossel, Neeman, Sly (2012, 2013) and Massoulie (2013). In this paper, we introduce a variant of the binary model which we call the regular stochastic block model (RSBM). We prove rigidity by showing that with high probability an exact recovery of the community structure is possible. Spectral methods exhibit a regime where this can be done efficiently. Moreover we also prove that, in this setting, any suitably good partial recovery can be bootstrapped to obtain a full recovery of the communities.

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arXiv2020

Spectral Edge in Sparse Random Graphs: Upper and Lower Tail Large Deviations

In this paper we consider the problem of estimating the joint upper and lower tail large deviations of the edge eigenvalues of an Erdős-Rényi random graph $\mathcal{G}_{n,p}$, in the regime of $p$ where the edge of the spectrum is no longer governed by global observables, such as the number of edges, but rather by localized statistics, such as high degree vertices. Going beyond the recent developments in mean-field approximations of related problems, this paper provides a comprehensive treatment of the large deviations of the spectral edge in this entire regime, which notably includes the well studied case of constant average degree. In particular, for $r \geq 1$ fixed, we pin down the asymptotic probability that the top $r$ eigenvalues are jointly greater/less than their typical values by multiplicative factors bigger/smaller than $1$, in the regime mentioned above. The proof for the upper tail relies on a novel structure theorem, obtained by building on estimates of Krivelevich and Sudakov (2003), followed by an iterative cycle removal process, which shows, conditional on the upper tail large deviation event, with high probability the graph admits a decomposition in to a disjoint union of stars and a spectrally negligible part. On the other hand, the key ingredient in the proof of the lower tail is a Ramsey-type result which shows that if the $K$-th largest degree of a graph is not atypically small (for some large $K$ depending on $r$), then either the top eigenvalue or the $r$-th largest eigenvalue is larger than that allowed by the lower tail event on the top $r$ eigenvalues, thus forcing a contradiction. The above arguments reduce the problems to developing a large deviation theory for the extremal degrees which could be of independent interest.

math.PR↗

arXiv2019

Lower Deviations in $β$-ensembles and Law of Iterated Logarithm in Last Passage Percolation

For the last passage percolation (LPP) on $\mathbb{Z}^2$ with exponential passage times, let $T_{n}$ denote the passage time from $(1,1)$ to $(n,n)$. We investigate the law of iterated logarithm of the sequence $\{T_{n}\}_{n\geq 1}$; we show that $\liminf_{n\to \infty} \frac{T_{n}-4n}{n^{1/3}(\log \log n)^{1/3}}$ almost surely converges to a deterministic negative constant and obtain some estimates on the same. This settles a conjecture of Ledoux (J. Theor. Probab., 2018) where a related lower bound and similar results for the corresponding upper tail were proved. Our proof relies on a slight shift in perspective from point-to-point passage times to considering point-to-line passage times instead, and exploiting the correspondence of the latter to the largest eigenvalue of the Laguerre Orthogonal Ensemble (LOE). A key technical ingredient, which is of independent interest, is a new lower bound of lower tail deviation probability of the largest eigenvalue of $β$-Laguerre ensembles, which extends the results proved in the context of the $β$-Hermite ensembles by Ledoux and Rider (Electron. J. Probab., 2010).

math.PR↗

arXiv2019

High-girth near-Ramanujan graphs with localized eigenvectors

We show that for every prime $d$ and $α\in (0,1/6)$, there is an infinite sequence of $(d+1)$-regular graphs $G=(V,E)$ with girth at least $2α\log_{d}(|V|)(1-o_d(1))$, second adjacency matrix eigenvalue bounded by $(3/\sqrt{2})\sqrt{d}$, and many eigenvectors fully localized on small sets of size $O(|V|^α)$. This strengthens the results of Ganguly-Srivastava, who constructed high girth (but not expanding) graphs with similar properties, and may be viewed as a discrete analogue of the "scarring" phenomenon observed in the study of quantum ergodicity on manifolds. Key ingredients in the proof are a technique of Kahale for bounding the growth rate of eigenfunctions of graphs, discovered in the context of vertex expansion and a method of Erdős and Sachs for constructing high girth regular graphs.

math.CO↗

arXiv2019

Bounding the number of self-avoiding walks: Hammersley-Welsh with polygon insertion

Let $c_n = c_n(d)$ denote the number of self-avoiding walks of length $n$ starting at the origin in the Euclidean nearest-neighbour lattice $\mathbb{Z}^d$. Let $μ= \lim_n c_n^{1/n}$ denote the connective constant of $\mathbb{Z}^d$. In 1962, Hammersley and Welsh [HW62] proved that, for each $d \geq 2$, there exists a constant $C > 0$ such that $c_n \leq \exp(C n^{1/2}) μ^n$ for all $n \in \mathbb{N}$. While it is anticipated that $c_n μ^{-n}$ has a power-law growth in $n$, the best known upper bound in dimension two has remained of the form $n^{1/2}$ inside the exponential. The natural first improvement to demand for a given planar lattice is a bound of the form $c_n \leq \exp (C n^{1/2 - ε})μ^n$, where $μ$ denotes the connective constant of the lattice in question. We derive a bound of this form for two such lattices, for an explicit choice of $ε> 0$ in each case. For the hexagonal lattice $\mathbb{H}$, the bound is proved for all $n \in \mathbb{N}$; while for the Euclidean lattice $\mathbb{Z}^2$, it is proved for a set of $n \in \mathbb{N}$ of limit supremum density equal to one. A power-law upper bound on $c_n μ^{-n}$ for $\mathbb{H}$ is also proved, contingent on a non-quantitative assertion concerning this lattice's connective constant.

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arXiv2019

Fractal geometry of Airy_2 processes coupled via the Airy sheet

In last passage percolation models lying in the Kardar-Parisi-Zhang universality class, maximizing paths that travel over distances of order $n$ accrue energy that fluctuates on scale $n^{1/3}$; and these paths deviate from the linear interpolation of their endpoints on scale $n^{2/3}$. These maximizing paths and their energies may be viewed via a coordinate system that respects these scalings. What emerges by doing so is a system indexed by $x,y \in \mathbb{R}$ and $s,t \in \mathbb{R}$ with $s < t$ of unit order quantities $W_n\big( x,s ; y,t \big)$ specifying the scaled energy of the maximizing path that moves in scaled coordinates between $(x,s)$ and $(y,t)$. The space-time Airy sheet is, after a parabolic adjustment, the putative distributional limit $W_\infty$ of this system as $n \to \infty$. The Airy sheet has recently been constructed in [15] as such a limit of Brownian last passage percolation. In this article, we initiate the study of fractal geometry in the Airy sheet. We prove that the scaled energy difference profile given by $\mathbb{R} \to \mathbb{R}: z \to W_\infty \big( 1,0 ; z,1 \big) - W_\infty \big( -1,0 ; z,1 \big)$ is a non-decreasing process that is constant in a random neighbourhood of almost every $z \in \mathbb{R}$; and that the exceptional set of $z \in \mathbb{R}$ that violate this condition almost surely has Hausdorff dimension one-half. Points of violation correspond to special behaviour for scaled maximizing paths, and we prove the result by investigating this behaviour, making use of two inputs from recent studies of scaled Brownian LPP; namely, Brownian regularity of profiles, and estimates on the rarity of pairs of disjoint scaled maximizing paths that begin and end close to each other.

math.PR↗

arXiv2019

Ground States And Hyperuniformity Of The Hierarchical Coulomb Gas In All Dimensions

Stochastic point processes with Coulomb interactions arise in various natural examples of statistical mechanics, random matrices and optimization problems. Often such systems due to their natural repulsion exhibit remarkable hyperuniformity properties, that is, the number of points landing in any given region fluctuates at a much smaller scale compared to that of a set of i.i.d. random points. A well known conjecture from physics appearing in the works of Jancovici, Lebowitz, Manificat, Martin, and Yalcin ('80,'83,'93), states that the variance of the number of points landing in a set should grow like the surface area instead of the volume unlike i.i.d. random points. In a recent beautiful work, Chatterjee (2017) gave the first proof of such a result in dimension three for a Coulomb type system, known as the hierarchical Coulomb gas, inspired by Dyson's hierarchical model of the Ising ferromagnet. However the case of dimensions greater than three had remained open. In this paper, we establish the correct fluctuation behavior up to logarithmic factors in all dimensions greater than three, for the hierarchical model. Using similar methods, we also prove sharp variance bounds for smooth linear statistics which were unknown in any dimension bigger than two. A key intermediate step is to obtain precise results about the ground states of such models whose behavior can be interpreted as hierarchical analogues of various crystalline conjectures predicted for energy minimizing systems, and could be of independent interest.

math.PR↗

arXiv2019

Connecting Eigenvalue Rigidity with Polymer Geometry: Diffusive Transversal Fluctuations under Large Deviation

We consider the exactly solvable model of exponential directed last passage percolation on $\mathbb{Z}^2$ in the large deviation regime. Conditional on the upper tail large deviation event $\mathcal{U}_δ:=\{T_{n}\geq (4+δ)n\}$ where $T_{n}$ denotes the last passage time from $(1,1)$ to $(n,n)$, we study the geometry of the polymer/geodesic $Γ_{n}$, i.e., the optimal path attaining $T_{n}$. We show that conditioning on $\mathcal{U}_δ$ changes the transversal fluctuation exponent from the characteristic $2/3$ of the KPZ universality class to $1/2$, i.e., conditionally, the smallest strip around the diagonal that contains $Γ_{n}$ has width $n^{1/2+o(1)}$ with high probability. This sharpens a result of Deuschel and Zeitouni (1999) who proved a $o(n)$ bound on the transversal fluctuation in the context of Poissonian last passage percolation, and complements (Basu, Ganguly, Sly, 2017), where the transversal fluctuation was shown to be $Θ(n)$ in the lower tail large deviation event. Our proof exploits the correspondence between last passage times in the exponential LPP model and the largest eigenvalue of the Laguerre Unitary Ensemble (LUE) together with the determinantal structure of the spectrum of the latter. A key ingredient in our proof is a sharp refinement of the large deviation result for the largest eigenvalue (Seppäläinen '98, Johansson '99), using rigidity properties of the spectrum, which could be of independent interest.

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arXiv2018

Competitive Erosion is Conformally Invariant

We study a graph-theoretic model of interface dynamics called $Competitive\, Erosion$. Each vertex of the graph is occupied by a particle, which can be either red or blue. New red and blue particles are emitted alternately from their respective bases and perform random walk. On encountering a particle of the opposite color they remove it and occupy its position. We consider competitive erosion on discretizations of `smooth', planar, simply connected domains. The main result of this article shows that at stationarity, with high probability, the blue and the red regions are separated by the level curves of the Green function, with Neumann boundary conditions, which are orthogonal circular arcs on the disc and hyperbolic geodesics on a general simply connected domain. This establishes $conformal\,invariance$ of the model.

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