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S. R. S. Varadhan

Publications and source records attributed to S. R. S. Varadhan.

16 recordsLinked to original sources

Effective Mass of the Fröhlich Polaron and the Landau-Pekar-Spohn Conjecture

We prove that there is a constant $\overline C\in (0,\infty)$ such that the effective mass $m(α)$ of the Fröhlich Polaron satisfies $m(α) \geq \overline C α^4$, which is sharp according to a long-standing prediction of Landau-Pekar [19] from 1948 and of Spohn [36] from 1987. The method of proof, which demonstrates how the sharp quartic divergence rate of $m(α)$ appears in a natural way, is based on analyzing the Gaussian representation of the Polaron measure and that of the associated tilted Poisson point process developed in [26]. Additionally, our technique here leads to accompanying results including, 1) an explicit identification of local interval process from [26] in the strong coupling limit in terms of functionals of the Pekar process [27], 2) strict monotonicity of the effective mass $m(α)$ for all $α>0$ and 3) the quartic divergence of $m(α)$ for a generalized class of Polaron type interactions.

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Atypical behaviors of a tagged particle in asymmetric simple exclusion

Consider the asymmetric nearest-neighbor exclusion process (ASEP) on ${\mathbb Z}$ with single particle drift $γ>0$, starting from a Bernoulli product invariant measure $ν_ρ$ with density $ρ$. It is known that the position $X_{N}$ of a tagged particle, say initially at the origin, at time $N$ satisfies an a.s. law of large numbers $\frac{1}{N}X_N \rightarrow γ(1-ρ)$ as $N\uparrow\infty$. In this context, we study the `typical' behavior of the tagged particle and `bulk' density evolution subject to `atypical' events $\{X_N\geq AN\}$ or $\{X_N\leq AN\}$ for $A\neq γ(1-ρ)$. We detail different structures, depending on whether $A<0$, $0\leq A< γ(1-ρ)$, $γ(1-ρ)<A< γ$, or $A\geq γ$, under which these atypical events are achieved, and compute associated large deviation costs. Among our results is an `upper tail' large deviation principle in scale $N$ for $\frac{1}{N}X_N$.

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Identification of the Polaron measure I: Fixed coupling regime and the central limit theorem for large times

We consider the Fröhlich model of the Polaron whose path integral formulation leads to the transformed path measure $$ \widehat{\mathbb P}_{α,T}(\mathrm dω)= Z_{α,T}^{-1}\,\, \exp\bigg\{\fracα{2}\int_{-T}^T\int_{-T}^T\frac{e^{-|t-s|}}{|ω(t)-ω(s)|} \, d s \, d t\bigg\}\,\mathbb P(\mathrm dω) $$ with respect to $\mathbb P$ which governs the law of the increments of the three dimensional Brownian motion on a finite interval $[-T,T]$, and $ Z_{α,T}$ is the partition function or the normalizing constant and $α>0$ is a constant. The Polaron measure reflects a self attractive interaction. According to a conjecture of Pekar that was proved in [DV83] $$ g_0=\lim_{α\to\infty}\frac{1}{α^2}\bigg[\lim_{T\to\infty}\frac{\log Z_{α,T}}{2T}\bigg] $$ exists and has a variational formula. In this article we show that for any $α>0$, the infinite-volume limit $\widehat{\mathbb P}_α=\lim_{T\to\infty}\widehat{\mathbb P}_{α,T}$ exists which is also identified explicitly. As a corollary, we deduce the central limit theorem (for any $α>0$ and as $T\to\infty$) for the distribution of $\frac{ω(T)-ω(-T)}{\sqrt{2T}}$ both under the finite-volume Polaron measure $\widehat{\mathbb P}_{α,T}$ and its infinite-volume counterpart $\widehat{\mathbb P}_α$, and obtain an expression for the limiting variance.

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Identification of the Polaron measure in strong coupling and the Pekar variational formula

The path measure corresponding to the Fröhlich Polaron appearing in quantum statistical mechanics is defined as the tilted measure $$ \widehat{\mathbb P}_{\varepsilon,T}= \frac{1}{Z(\varepsilon,T)}\exp\bigg(\frac{1}{2}\int_{-T}^T\int_{-T}^T \frac{\varepsilon\mathrm e^{-\varepsilon |t-s|}}{|ω(t)-ω(s)|} \mathrm d s \,\mathrm d t\bigg)\mathrm d\mathbb P. $$ Here $\varepsilon>0$ is the Kac parameter (or the inverse-coupling), and $\mathbb P$ is the law of $3d$ Brownian increments. In [13] it was shown that the (thermodynamic) limit $\lim_{T\to\infty}\widehat{\mathbb P}_{\varepsilon,T}=\widehat{\mathbb P}_\varepsilon$ exists as a process with stationary increments and this limit was identified explicitly as a mixture of Gaussian processes. In the present article, the strong coupling limit or the vanishing Kac parameter limit $\lim_{\varepsilon\to 0} \widehat{\mathbb P}_\varepsilon$ is investigated. It is shown that this limit exists and coincides with the increments of the Pekar process, which is a stationary diffusion process with generator $\frac 12 Δ+ (\nablaψ/ψ)\cdot \nabla$, where $ψ$ is the unique (modulo shifts) maximizer of the Pekar variational problem $$ g_0=\sup_{\|ψ\|_2=1} \Big\{\int_{\mathbb R^3}\int_{\mathbb R^3}\,ψ^2(x) ψ^2(y)|x-y|^{-1}\mathrm d x\mathrm d y -\frac 12\|\nabla ψ\|_2^2\Big\}. $$ As shown in [12,6,1], the Pekar process is itself approximated by the limiting "mean-field Polaron measures", and thus, the present identification of the strong coupling Polaron is a rigorous justification of the "mean-field approximation" (on the level of path measures) conjectured by Spohn in [15]. This approximation in the vanishing Kac limit ($\varepsilon\to 0$) is also shown to hold for a general class of Kac-Interaction of the form $H(t,x)=\varepsilon \mathrm e^{-\varepsilon|t|} V(x)$ where $V$ is any continuous function vanishing at infinity.

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Strong coupling limit of the Polaron measure and the Pekar process

The {\it{Polaron measure}} is defined as the transformed path measure $$\widehat{\mathbb P}_{ε,T}= Z_{ε,T}^{-1}\,\, \exp\bigg\{\frac{1}{2}\int_{-T}^T\int_{-T}^T\frac{ε\e^{-ε|t-s|}}{|ω(t)-ω(s)|} \,\d s \,\d t\bigg\}\d\mathbb P$$ with respect to the law $\mathbb P$ of three dimensional Brownian increments on a finite interval $[-T,T]$, and $ Z_{ε,T}$ is the partition function with $ε>0$ being a constant. The logarithmic asymptotic behavior of the partition function $Z_{ε,T}$ was analyzed in \cite{DV83} showing that $$ g_0=\lim_{ε\to 0}\bigg[\lim_{T\to\infty}\frac{\log Z_{\eps,T}}{2T}\bigg]=\sup_{\heap{ψ\in H^1(\R^3)}{\|ψ\|_2=1}} \bigg\{\int_{\mathbb R^3}\int_{\mathbb R^3}\d x\d y\,\frac {ψ^2(x) ψ^2(y)}{|x-y|} -\frac 12\big\|\nabla ψ\big\|_2^2\bigg\}. $$ In \cite{MV18} we analyzed the actual path measures and showed that the limit ${\widehat {\mathbb P}}_{\eps}=\lim_{T\to\infty}\widehat{\mathbb P}_{\eps,T}$ exists and identified this limit explicitly, and as a corollary, we also deduced the central limit theorem for $(2T)^{-1/2}(ω(T)-ω(-T))$ under $\widehat{\mathbb P}_{\eps,T}$ and obtained an expression for the limiting variance $σ^2(\eps)$. In the present article, we investigate the {\it{strong coupling limit}} $\lim_{\eps\to 0} \lim_{T\to\infty} \widehat{\mathbb P}_{\eps,T}=\lim_{\eps\to 0} \widehat {\mathbb P}_\eps$ and show that this limit coincides with the increments of the stationary Pekar process with generator $$ \frac 12 Δ+ \bigg(\frac{\nablaψ}ψ\bigg)\cdot \nabla $$ for any maximizer $ψ$ of the free enrgy $g_0$. The Pekar process was also earlier identified in \cite{MV14}, \cite{KM15} and \cite{BKM15} as the limiting object of the {\it{mean-field Polaron}} measures.}

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Brownian Occupation Measures, Compactness and Large Deviations

In proving large deviation estimates, the lower bound for open sets and upper bound for compact sets are essentially local estimates. On the other hand, the upper bound for closed sets is global and compactness of space or an exponential tightness estimate is needed to establish it. In dealing with the occupation measure $L_t(A)=\frac{1}{t}\int_0^t{\1}_A(W_s) \d s$ of the $d$ dimensional Brownian motion, which is not positive recurrent, there is no possibility of exponential tightness. The space of probability distributions $\mathcal {M}_1(\R^d)$ can be compactified by replacing the usual topology of weak convergence by the vague toplogy, where the space is treated as the dual of continuous functions with compact support. This is essentially the one point compactification of $\R^d$ by adding a point at $\infty$ that results in the compactification of $\mathcal M_1(\R^d)$ by allowing some mass to escape to the point at $\infty$. If one were to use only test functions that are continuous and vanish at $\infty$ then the compactification results in the space of sub-probability distributions $\mathcal {M}_{\le 1}(\R^d)$ by ignoring the mass at $\infty$. The main drawback of this compactification is that it ignores the underlying translation invariance. More explicitly, we may be interested in the space of equivalence classes of orbits $\widetilde{\mathcal M}_1=\widetilde{\mathcal M}_1(\R^d)$ under the action of the translation group $\R^d$ on $\mathcal M_1(\R^d)$. There are problems for which it is natural to compactify this space of orbits. We will provide such a compactification, prove a large deviation principle there and give an application to a relevant problem.

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Tails of polynomials of random variables and stable limits for nonconventional sums

We obtain first decay rates of probabilities of tails of multivariate polynomials built on independent random variables with heavy tails. Then we derive stable limit theorems for nonconventional sums of the form $\sum_{Nt\geq n\geq 1}F(X(q_1(n)),...,X(q_\ell(n)))$ where $F$ is a polynomial, $1\leq q_1(n)<\cdots <q_\ell(n)$ are integer valued increasing functions satisfying certain conditions and $X(n),\, n\geq 0$ is a sequence of independent random variables with heavy tails.

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Nonconventional limit theorems in discrete and continuous time via martingales

We obtain functional central limit theorems for both discrete time expressions of the form $1/\sqrt{N}\sum_{n=1}^{[Nt]}(F(X(q_1(n)),\ldots, X(q_{\ell}(n)))-\bar{F})$ and similar expressions in the continuous time where the sum is replaced by an integral. Here $X(n),n\geq0$ is a sufficiently fast mixing vector process with some moment conditions and stationarity properties, $F$ is a continuous function with polynomial growth and certain regularity properties, $\bar{F}=\int F\,d(μ\times\cdots\timesμ)$, $μ$ is the distribution of $X(0)$ and $q_i(n)=in$ for $i\le k\leq\ell$ while for $i>k$ they are positive functions taking on integer values on integers with some growth conditions which are satisfied, for instance, when $q_i$'s are polynomials of increasing degrees. These results decisively generalize [Probab. Theory Related Fields 148 (2010) 71-106], whose method was only applicable to the case $k=2$ under substantially more restrictive moment and mixing conditions and which could not be extended to convergence of processes and to the corresponding continuous time case. As in [Probab. Theory Related Fields 148 (2010) 71-106], our results hold true when $X_i(n)=T^nf_i$, where $T$ is a mixing subshift of finite type, a hyperbolic diffeomorphism or an expanding transformation taken with a Gibbs invariant measure, as well as in the case when $X_i(n)=f_i({Υ}_n)$, where ${Υ}_n$ is a Markov chain satisfying the Doeblin condition considered as a stationary process with respect to its invariant measure. Moreover, our relaxed mixing conditions yield applications to other types of dynamical systems and Markov processes, for instance, where a spectral gap can be established. The continuous time version holds true when, for instance, $X_i(t)=f_i(ξ_t)$, where $ξ_t$ is a nondegenerate continuous time Markov chain with a finite state space or a nondegenerate diffusion on a compact manifold. A partial motivation for such limit theorems is due to a series of papers dealing with nonconventional ergodic averages.

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Large deviations for the current and tagged particle in 1D nearest-neighbor symmetric simple exclusion

Laws of large numbers, starting from certain nonequilibrium measures, have been shown for the integrated current across a bond, and a tagged particle in one-dimensional symmetric nearest-neighbor simple exclusion [Ann. Inst. Henri Poincare Probab. Stat. 42 (2006) 567-577]. In this article, we prove corresponding large deviation principles and evaluate the rate functions, showing different growth behaviors near and far from their zeroes which connect with results in [J. Stat. Phys. 136 (2009) 1-15].

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Large Deviations for Random Matrices

We prove a large deviation result for a random symmetric n x n matrix with independent identically distributed entries to have a few eigenvalues of size n. If the spectrum S survives when the matrix is rescaled by a factor of n, it can only be the eigenvalues of a Hilbert-Schmidt kernel k(x,y) on [0,1] x [0,1]. The rate function for k is $I(k)=1/2\int h(k(x,y) dxdy$ where h is the Cramer rate function for the common distribution of the entries that is assumed to have a tail decaying faster than any Gaussian. The large deviation for S is then obtained by contraction.

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Nonconventional Large Deviations Theorems

We obtain large deviations theorems for nonconventional sums with underlying process being a Markov process satisfying the Doeblin condition or a dynamical system such as subshift of finite type or hyperbolic or expanding transformation.

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The large deviation principle for the Erdős-Rényi random graph

What does an Erdos-Renyi graph look like when a rare event happens? This paper answers this question when p is fixed and n tends to infinity by establishing a large deviation principle under an appropriate topology. The formulation and proof of the main result uses the recent development of the theory of graph limits by Lovasz and coauthors and Szemeredi's regularity lemma from graph theory. As a basic application of the general principle, we work out large deviations for the number of triangles in G(n,p). Surprisingly, even this simple example yields an interesting double phase transition.

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Special invited paper. Large deviations

This paper is based on Wald Lectures given at the annual meeting of the IMS in Minneapolis during August 2005. It is a survey of the theory of large deviations.

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