Eyal Lubetzky
Research Subjects
Research Interests
Eyal Lubetzky has a total of 40 co-authors. Here are the top co-authors by number of shared publications:
- Yuval Peres
Beijing Institute of Mathematical Sciences and Applications (BIMSA), Huairou District, Beijing, People’s Republic of China
12 shared publications - Jian Ding
Department of Statistics, UC Berkeley, Berkeley, USA
10 shared publications - Allan Sly
NYU-ECNU Institute of Mathematical Sciences at NYU Shanghai and Cemaden Sao Jose dos Campos
9 shared publications - Allan Sly
Theory Group, Microsoft Research
5 shared publications - Michael Krivelevich
Tel Aviv University
5 shared publications - Alan Frieze
Department of Mathematical Sciences Carnegie Mellon University Pittsburgh Pennsylvania USA
4 shared publications
Latest Publications
- Open Access
On replica symmetry of large deviations in random graphs
The following question is due to Chatterjee and Varadhan (2011). Fix $0<p<r<1$ and take $G\sim G(n,p)$, the Erd\H{o}s-R\'enyi random graph with edge density $p$, conditioned to have at least as many triangles as the typical $G(n,r)$. Is $G$ close in cut-distance to a typical $G(n,r)$? Via a beautiful new framework for large deviation principles in $G(n,p)$, Chatterjee and Varadhan gave bounds on the replica symmetric phase, the region of $(p,r)$ where the answer is positive. They further showed that for any small enough $p$ there are at least two phase transitions as $r$ varies. We settle this question by identifying the replica symmetric phase for triangles and more generally for any fixed $d$-regular graph. By analyzing the variational problem arising from the framework of Chatterjee and Varadhan we show that the replica symmetry phase consists of all $(p,r)$ such that $(r^d,h_p(r))$ lies on the convex minorant of $x\mapsto h_p(x^{1/d})$ where $h_p$ is the rate function of a binomial with parameter $p$. In particular, the answer for triangles involves $h_p(\sqrt{x})$ rather than the natural guess of $h_p(x^{1/3})$ where symmetry was previously known. Analogous results are obtained for linear hypergraphs as well as the setting where the largest eigenvalue of $G\sim G(n,p)$ is conditioned to exceed the typical value of the largest eigenvalue of $G(n,r)$. Building on the work of Chatterjee and Diaconis (2012) we obtain additional results on a class of exponential random graphs including a new range of parameters where symmetry breaking occurs. En route we give a short alternative proof of a graph homomorphism inequality due to Kahn (2001) and Galvin and Tetali (2004).Open AccessOn replica symmetry of large deviations in random graphs
The following question is due to Chatterjee and Varadhan (2011). Fix $0<p<r<1$ and take $G\sim G(n,p)$, the Erd\H{o}s-R\'enyi random graph with edge density $p$, conditioned to have at least as many triangles as the typical $G(n,r)$. Is $G$ close in cut-distance to a typical $G(n,r)$? Via a beautiful new framework for large deviation principles in $G(n,p)$, Chatterjee and Varadhan gave bounds on the replica symmetric phase, the region of $(p,r)$ where the answer is positive. They further showed that for any small enough $p$ there are at least two phase transitions as $r$ varies. We settle this question by identifying the replica symmetric phase for triangles and more generally for any fixed $d$-regular graph. By analyzing the variational problem arising from the framework of Chatterjee and Varadhan we show that the replica symmetry phase consists of all $(p,r)$ such that $(r^d,h_p(r))$ lies on the convex minorant of $x\mapsto h_p(x^{1/d})$ where $h_p$ is the rate function of a binomial with parameter $p$. In particular, the answer for triangles involves $h_p(\sqrt{x})$ rather than the natural guess of $h_p(x^{1/3})$ where symmetry was previously known. Analogous results are obtained for linear hypergraphs as well as the setting where the largest eigenvalue of $G\sim G(n,p)$ is conditioned to exceed the typical value of the largest eigenvalue of $G(n,r)$. Building on the work of Chatterjee and Diaconis (2012) we obtain additional results on a class of exponential random graphs including a new range of parameters where symmetry breaking occurs. En route we give a short alternative proof of a graph homomorphism inequality due to Kahn (2001) and Galvin and Tetali (2004). - 1 December 2014
- Published by Wiley in Random Structures & Algorithms
- Vol. 45 (4) , 627-674
Cover time of a random graph with a degree sequence II: Allowing vertices of degree two
We study the cover time of a random graph chosen uniformly at random from the set of graphs with vertex set [n] and degree sequence . In a previous work (Abdullah, Cooper, and Frieze, Discrete Math 312 (2012), 3146–3163), the asymptotic cover time was obtained under a number of assumptions on d, the most significant being that di ≥ 3 for all i. Here we replace this assumption by di ≥ 2. As a corollary, we establish the asymptotic cover time for the 2‐core of the emerging giant component of . © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 45, 627–674, 2014
- 1 December 2014
- Published by Wiley in Random Structures & Algorithms
- Vol. 45 (4) , 627-674
Cover time of a random graph with a degree sequence II: Allowing vertices of degree two
We study the cover time of a random graph chosen uniformly at random from the set of graphs with vertex set [n] and degree sequence . In a previous work (Abdullah, Cooper, and Frieze, Discrete Math 312 (2012), 3146–3163), the asymptotic cover time was obtained under a number of assumptions on d, the most significant being that di ≥ 3 for all i. Here we replace this assumption by di ≥ 2. As a corollary, we establish the asymptotic cover time for the 2‐core of the emerging giant component of . © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 45, 627–674, 2014
- Open Access
Universality of cutoff for the Ising model
On any locally-finite geometry, the stochastic Ising model is known to be contractive when the inverse-temperature $\beta$ is small enough, via classical results of Dobrushin and of Holley in the 1970's. By a general principle proposed by Peres, the dynamics is then expected to exhibit cutoff. However, so far cutoff for the Ising model has been confirmed mainly for lattices, heavily relying on amenability and log Sobolev inequalities. Without these, cutoff was unknown at any fixed $\beta>0$, no matter how small, even in basic examples such as the Ising model on a binary tree or a random regular graph. We use the new framework of information percolation to show that, in any geometry, there is cutoff for the Ising model at high enough temperatures. Precisely, on any sequence of graphs with maximum degree $d$, the Ising model has cutoff provided that $\beta<\kappa/d$ for some absolute constant $\kappa$ (a result which, up to the value of $\kappa$, is best possible). Moreover, the cutoff location is established as the time at which the sum of squared magnetizations drops to 1, and the cutoff window is $O(1)$, just as when $\beta=0$. Finally, the mixing time from almost every initial state is not more than a factor of $1+\epsilon_\beta$ faster then the worst one (with $\epsilon_\beta\to0$ as $\beta\to 0$), whereas the uniform starting state is at least $2-\epsilon_\beta$ times faster.Open AccessUniversality of cutoff for the Ising model
On any locally-finite geometry, the stochastic Ising model is known to be contractive when the inverse-temperature $\beta$ is small enough, via classical results of Dobrushin and of Holley in the 1970's. By a general principle proposed by Peres, the dynamics is then expected to exhibit cutoff. However, so far cutoff for the Ising model has been confirmed mainly for lattices, heavily relying on amenability and log Sobolev inequalities. Without these, cutoff was unknown at any fixed $\beta>0$, no matter how small, even in basic examples such as the Ising model on a binary tree or a random regular graph. We use the new framework of information percolation to show that, in any geometry, there is cutoff for the Ising model at high enough temperatures. Precisely, on any sequence of graphs with maximum degree $d$, the Ising model has cutoff provided that $\beta<\kappa/d$ for some absolute constant $\kappa$ (a result which, up to the value of $\kappa$, is best possible). Moreover, the cutoff location is established as the time at which the sum of squared magnetizations drops to 1, and the cutoff window is $O(1)$, just as when $\beta=0$. Finally, the mixing time from almost every initial state is not more than a factor of $1+\epsilon_\beta$ faster then the worst one (with $\epsilon_\beta\to0$ as $\beta\to 0$), whereas the uniform starting state is at least $2-\epsilon_\beta$ times faster. - Open Access
Cover time of a random graph with a degree sequence II: Allowing vertices of degree two
We study the cover time of a random graph chosen uniformly at random from the set of graphs with vertex set $[n]$ and degree sequence $\mathbf{d}=(d_i)_{i=1}^n$. In a previous work, the asymptotic cover time was obtained under a number of assumptions on $\mathbf{d}$, the most significant being that $d_i\geq 3$ for all $i$. Here we replace this assumption by $d_i\geq 2$. As a corollary, we establish the asymptotic cover time for the 2-core of the emerging giant component of $\mathcal{G}(n,p)$.Open AccessCover time of a random graph with a degree sequence II: Allowing vertices of degree two
We study the cover time of a random graph chosen uniformly at random from the set of graphs with vertex set $[n]$ and degree sequence $\mathbf{d}=(d_i)_{i=1}^n$. In a previous work, the asymptotic cover time was obtained under a number of assumptions on $\mathbf{d}$, the most significant being that $d_i\geq 3$ for all $i$. Here we replace this assumption by $d_i\geq 2$. As a corollary, we establish the asymptotic cover time for the 2-core of the emerging giant component of $\mathcal{G}(n,p)$. - Open Access
Harmonic pinnacles in the Discrete Gaussian model
The 2D Discrete Gaussian model gives each height function $\eta : \mathbb{Z}^2\to\mathbb{Z}$ a probability proportional to $\exp(-\beta \mathcal{H}(\eta))$, where $\beta$ is the inverse-temperature and $\mathcal{H}(\eta) = \sum_{x\sim y}(\eta_x-\eta_y)^2$ sums over nearest-neighbor bonds. We consider the model at large fixed $\beta$, where it is flat unlike its continuous analog (the Gaussian Free Field). We first establish that the maximum height in an $L\times L$ box with 0 boundary conditions concentrates on two integers $M,M+1$ with $M\sim \sqrt{(1/2\pi\beta)\log L\log\log L}$. The key is a large deviation estimate for the height at the origin in $\mathbb{Z}^2$, dominated by "harmonic pinnacles", integer approximations of a harmonic variational problem. Second, in this model conditioned on $\eta\geq 0$ (a floor), the average height rises, and in fact the height of almost all sites concentrates on levels $H,H+1$ where $H\sim M/\sqrt{2}$. This in particular pins down the asymptotics, and corrects the order, in results of Bricmont, El-Mellouki and Fr\"ohlich (1986), where it was argued that the maximum and the height of the surface above a floor are both of order $\sqrt{\log L}$. Finally, our methods extend to other classical surface models (e.g., restricted SOS), featuring connections to $p$-harmonic analysis and alternating sign matrices.Open AccessHarmonic pinnacles in the Discrete Gaussian model
The 2D Discrete Gaussian model gives each height function $\eta : \mathbb{Z}^2\to\mathbb{Z}$ a probability proportional to $\exp(-\beta \mathcal{H}(\eta))$, where $\beta$ is the inverse-temperature and $\mathcal{H}(\eta) = \sum_{x\sim y}(\eta_x-\eta_y)^2$ sums over nearest-neighbor bonds. We consider the model at large fixed $\beta$, where it is flat unlike its continuous analog (the Gaussian Free Field). We first establish that the maximum height in an $L\times L$ box with 0 boundary conditions concentrates on two integers $M,M+1$ with $M\sim \sqrt{(1/2\pi\beta)\log L\log\log L}$. The key is a large deviation estimate for the height at the origin in $\mathbb{Z}^2$, dominated by "harmonic pinnacles", integer approximations of a harmonic variational problem. Second, in this model conditioned on $\eta\geq 0$ (a floor), the average height rises, and in fact the height of almost all sites concentrates on levels $H,H+1$ where $H\sim M/\sqrt{2}$. This in particular pins down the asymptotics, and corrects the order, in results of Bricmont, El-Mellouki and Fr\"ohlich (1986), where it was argued that the maximum and the height of the surface above a floor are both of order $\sqrt{\log L}$. Finally, our methods extend to other classical surface models (e.g., restricted SOS), featuring connections to $p$-harmonic analysis and alternating sign matrices. - 29 April 2014
- Published by Wiley in Random Structures & Algorithms
- Vol. 47 (1) , 109-146
On replica symmetry of large deviations in random graphs
The following question is due to Chatterjee and Varadhan (2011). Fix and take , the Erdős‐Rényi random graph with edge density p, conditioned to have at least as many triangles as the typical . Is G close in cut‐distance to a typical ? Via a beautiful new framework for large deviation principles in , Chatterjee and Varadhan gave bounds on the replica symmetric phase, the region of where the answer is positive. They further showed that for any small enough p there are at least two phase transitions as r varies. We settle this question by identifying the replica symmetric phase for triangles and more generally for any fixed d‐regular graph. By analyzing the variational problem arising from the framework of Chatterjee and Varadhan we show that the replica symmetry phase consists of all such that lies on the convex minorant of where is the rate function of a binomial with parameter p. In particular, the answer for triangles involves rather than the natural guess of where symmetry was previously known. Analogous results are obtained for linear hypergraphs as well as the setting where the largest eigenvalue of is conditioned to exceed the typical value of the largest eigenvalue of . Building on the work of Chatterjee and Diaconis (2012) we obtain additional results on a class of exponential random graphs including a new range of parameters where symmetry breaking occurs. En route we give a short alternative proof of a graph homomorphism inequality due to Kahn (2001) and Galvin and Tetali (2004). © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 109–146, 2015
- 29 April 2014
- Published by Wiley in Random Structures & Algorithms
- Vol. 47 (1) , 109-146
On replica symmetry of large deviations in random graphs
The following question is due to Chatterjee and Varadhan (2011). Fix and take , the Erdős‐Rényi random graph with edge density p, conditioned to have at least as many triangles as the typical . Is G close in cut‐distance to a typical ? Via a beautiful new framework for large deviation principles in , Chatterjee and Varadhan gave bounds on the replica symmetric phase, the region of where the answer is positive. They further showed that for any small enough p there are at least two phase transitions as r varies. We settle this question by identifying the replica symmetric phase for triangles and more generally for any fixed d‐regular graph. By analyzing the variational problem arising from the framework of Chatterjee and Varadhan we show that the replica symmetry phase consists of all such that lies on the convex minorant of where is the rate function of a binomial with parameter p. In particular, the answer for triangles involves rather than the natural guess of where symmetry was previously known. Analogous results are obtained for linear hypergraphs as well as the setting where the largest eigenvalue of is conditioned to exceed the typical value of the largest eigenvalue of . Building on the work of Chatterjee and Diaconis (2012) we obtain additional results on a class of exponential random graphs including a new range of parameters where symmetry breaking occurs. En route we give a short alternative proof of a graph homomorphism inequality due to Kahn (2001) and Galvin and Tetali (2004). © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 109–146, 2015
- Open Access
Cycle factors and renewal theory
For which values of $k$ does a uniformly chosen $3$-regular graph $G$ on $n$ vertices typically contain $ n/k$ vertex-disjoint $k$-cycles (a $k$-cycle factor)? To date, this has been answered for $k=n$ and for $k \ll \log n$; the former, the Hamiltonicity problem, was finally answered in the affirmative by Robinson and Wormald in 1992, while the answer in the latter case is negative since with high probability most vertices do not lie on $k$-cycles. Here we settle the problem completely: the threshold for a $k$-cycle factor in $G$ as above is $\kappa_0 \log_2 n$ with $\kappa_0=[1-\frac12\log_2 3]^{-1}\approx 4.82$. Precisely, we prove a 2-point concentration result: if $k \geq \kappa_0 \log_2(2n/e)$ divides $n$ then $G$ contains a $k$-cycle factor w.h.p., whereas if $k<\kappa_0\log_2(2n/e)-\frac{\log^2 n}n$ then w.h.p. it does not. As a byproduct, we confirm the "Comb Conjecture," an old problem concerning the embedding of certain spanning trees in the random graph $G(n,p)$. The proof follows the small subgraph conditioning framework, but the associated second moment analysis here is far more delicate than in any earlier use of this method and involves several novel features, among them a sharp estimate for tail probabilities in renewal processes without replacement which may be of independent interest.Open AccessCycle factors and renewal theory
For which values of $k$ does a uniformly chosen $3$-regular graph $G$ on $n$ vertices typically contain $ n/k$ vertex-disjoint $k$-cycles (a $k$-cycle factor)? To date, this has been answered for $k=n$ and for $k \ll \log n$; the former, the Hamiltonicity problem, was finally answered in the affirmative by Robinson and Wormald in 1992, while the answer in the latter case is negative since with high probability most vertices do not lie on $k$-cycles. Here we settle the problem completely: the threshold for a $k$-cycle factor in $G$ as above is $\kappa_0 \log_2 n$ with $\kappa_0=[1-\frac12\log_2 3]^{-1}\approx 4.82$. Precisely, we prove a 2-point concentration result: if $k \geq \kappa_0 \log_2(2n/e)$ divides $n$ then $G$ contains a $k$-cycle factor w.h.p., whereas if $k<\kappa_0\log_2(2n/e)-\frac{\log^2 n}n$ then w.h.p. it does not. As a byproduct, we confirm the "Comb Conjecture," an old problem concerning the embedding of certain spanning trees in the random graph $G(n,p)$. The proof follows the small subgraph conditioning framework, but the associated second moment analysis here is far more delicate than in any earlier use of this method and involves several novel features, among them a sharp estimate for tail probabilities in renewal processes without replacement which may be of independent interest. - Open Access
Cores of random graphs are born Hamiltonian
Let $(G_t)_{t \geq 0}$ be the random graph process ($G_0$ is edgeless and $G_t$ is obtained by adding a uniformly distributed new edge to $G_{t-1}$), and let $\tau_k$ denote the minimum time $t$ such that the $k$-core of $G_t$ (its unique maximal subgraph with minimum degree at least $k$) is nonempty. For any fixed $k\geq 3$ the $k$-core is known to emerge via a discontinuous phase transition, where at time $t=\tau_k$ its size jumps from 0 to linear in the number of vertices with high probability. It is believed that for any $k\geq 3$ the core is Hamiltonian upon creation w.h.p., and Bollob\'as, Cooper, Fenner and Frieze further conjectured that it in fact admits $\lfloor(k-1)/2\rfloor$ edge-disjoint Hamilton cycles. However, even the asymptotic threshold for Hamiltonicity of the $k$-core in $G(n,p)$ was unknown for any $k$. We show here that for any fixed $k\ge 15$ the $k$-core of $G_t$ is w.h.p. Hamiltonian for all $t \geq \tau_k$, i.e., immediately as the $k$-core appears and indefinitely afterwards. Moreover, we prove that for large enough fixed $k$ the $k$-core contains $\lfloor (k-3)/2\rfloor$ edge-disjoint Hamilton cycles w.h.p. for all $t\geq \tau_k$.Open AccessCores of random graphs are born Hamiltonian
Let $(G_t)_{t \geq 0}$ be the random graph process ($G_0$ is edgeless and $G_t$ is obtained by adding a uniformly distributed new edge to $G_{t-1}$), and let $\tau_k$ denote the minimum time $t$ such that the $k$-core of $G_t$ (its unique maximal subgraph with minimum degree at least $k$) is nonempty. For any fixed $k\geq 3$ the $k$-core is known to emerge via a discontinuous phase transition, where at time $t=\tau_k$ its size jumps from 0 to linear in the number of vertices with high probability. It is believed that for any $k\geq 3$ the core is Hamiltonian upon creation w.h.p., and Bollob\'as, Cooper, Fenner and Frieze further conjectured that it in fact admits $\lfloor(k-1)/2\rfloor$ edge-disjoint Hamilton cycles. However, even the asymptotic threshold for Hamiltonicity of the $k$-core in $G(n,p)$ was unknown for any $k$. We show here that for any fixed $k\ge 15$ the $k$-core of $G_t$ is w.h.p. Hamiltonian for all $t \geq \tau_k$, i.e., immediately as the $k$-core appears and indefinitely afterwards. Moreover, we prove that for large enough fixed $k$ the $k$-core contains $\lfloor (k-3)/2\rfloor$ edge-disjoint Hamilton cycles w.h.p. for all $t\geq \tau_k$. - Open Access
The threshold for combs in random graphs
For $k\mid n$ let $Comb_{n,k}$ denote the tree consisting of an $(n/k)$-vertex path with disjoint $k$-vertex paths beginning at each of its vertices. An old conjecture says that for any $k=k(n)$ the threshold for the random graph $G(n,p)$ to contain $Comb_{n,k}$ is at $p\asymp \frac{\log n}n$. Here we verify this for $k \leq C\log n$ with any fixed $C>0$. In a companion paper, using very different methods, we treat the complementary range, proving the conjecture for $k\geq \kappa_0 \log n$ (with $\kappa_0\approx 4.82$).Open AccessThe threshold for combs in random graphs
For $k\mid n$ let $Comb_{n,k}$ denote the tree consisting of an $(n/k)$-vertex path with disjoint $k$-vertex paths beginning at each of its vertices. An old conjecture says that for any $k=k(n)$ the threshold for the random graph $G(n,p)$ to contain $Comb_{n,k}$ is at $p\asymp \frac{\log n}n$. Here we verify this for $k \leq C\log n$ with any fixed $C>0$. In a companion paper, using very different methods, we treat the complementary range, proving the conjecture for $k\geq \kappa_0 \log n$ (with $\kappa_0\approx 4.82$). - 18 October 2013
- Published by Wiley in Communications on Pure and Applied Mathematics
- Vol. 67 (6) , 982-1027
Cutoff for General Spin Systems with Arbitrary Boundary Conditions
The cutoff phenomenon describes a sharp transition in the convergence of a Markov chain to equilibrium. In recent work, the authors established cutoff and its location for the stochastic Ising model on the d‐dimensional torus (ℤ/nℤ)d for any d ≥ ;1. The proof used the symmetric structure of the torus and monotonicity in an essential way.Here we enhance the framework and extend it to general geometries, boundary conditions, and external fields to derive a cutoff criterion that involves the growth rate of balls and the log‐Sobolev constant of the Glauber dynamics. In particular, we show there is cutoff for the stochastic Ising model on any sequence of bounded‐degree graphs with subexponential growth under arbitrary external fields provided the inverse log‐Sobolev constant is bounded. For lattices with homogenous boundary, such as all‐plus, we identify the cutoff location explicitly in terms of spectral gaps of infinite‐volume dynamics on half‐plane intersections. Analogous results establishing cutoff are obtained for nonmonotone spin systems at high temperatures, including the gas hard‐core model, the Potts model, the antiferromagnetic Potts model, and the coloring model.
- 18 October 2013
- Published by Wiley in Communications on Pure and Applied Mathematics
- Vol. 67 (6) , 982-1027
Cutoff for General Spin Systems with Arbitrary Boundary Conditions
The cutoff phenomenon describes a sharp transition in the convergence of a Markov chain to equilibrium. In recent work, the authors established cutoff and its location for the stochastic Ising model on the d‐dimensional torus (ℤ/nℤ)d for any d ≥ ;1. The proof used the symmetric structure of the torus and monotonicity in an essential way.Here we enhance the framework and extend it to general geometries, boundary conditions, and external fields to derive a cutoff criterion that involves the growth rate of balls and the log‐Sobolev constant of the Glauber dynamics. In particular, we show there is cutoff for the stochastic Ising model on any sequence of bounded‐degree graphs with subexponential growth under arbitrary external fields provided the inverse log‐Sobolev constant is bounded. For lattices with homogenous boundary, such as all‐plus, we identify the cutoff location explicitly in terms of spectral gaps of infinite‐volume dynamics on half‐plane intersections. Analogous results establishing cutoff are obtained for nonmonotone spin systems at high temperatures, including the gas hard‐core model, the Potts model, the antiferromagnetic Potts model, and the coloring model.