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S. Spektor

Publications and source records attributed to S. Spektor.

8 recordsLinked to original sources

Quantitative stability of the intersection body operator near the ball, and the dynamical origin of the two--dimensional degeneracy

Let $\IB$ denote the intersection body operator on star bodies in $\R^n$. A recent theorem of Milman, Shabelman and Yehudayoff establishes that for $n\ge 3$ the equation $\IB^2 K = cK$ holds if and only if $K$ is a centered ellipsoid, thereby resolving the fixed--point problem for $\IB^2$ and, as a consequence, the long--standing conjecture $\IB K = cK \Leftrightarrow K$ is a ball. We complement this qualitative rigidity with a \emph{quantitative} analysis in a neighbourhood of the ball. Linearizing the associated shape dynamics on $L^2(\Sph)$, we compute the full spectrum of the operator $\IB^2$ at the ball in closed form for every dimension: the degree--two (ellipsoidal) harmonics are neutral with multiplier exactly $1$, while all higher harmonics are contracted, with a sharp spectral gap \[ \mathrm{gap}(n)\;=\;\frac{(n-2)(n+4)}{(n+1)^2}. \] This yields an explicit linear stability constant $C(n)=(n+1)^2/\big((n-2)(n+4)\big)$, and, via a center--manifold reduction, a local quantitative stability statement for $\IB^2$ near the ball valid in each fixed dimension $n\ge 3$. The gap degenerates precisely as $n\to 2^+$, giving a transparent \emph{dynamical} explanation of the well--known exceptional status of the plane, where $\IB K = 2K$ for every origin--symmetric star body. We also record the reduced normal form of $\IB$ on the ellipsoidal directions and observe that the centered ellipsoids constitute a normally attracting invariant manifold for the shape under iterated intersection bodies. The methods are perturbative and do not address the global periodic problem $\IB^m K = cK$ for $m\ge 3$, which we discuss.

math.MG

Two Multi--Draw Coupon Collector models with different retention rules

In this paper we study two variants of the generalized coupon collector's problem, where our collector receives at each run d distinct coupons and keeps all the new observed coupons (Problem I), while he chooses the least--collected coupon at each run (Problem II). In both cases we derive explicit formulae for the average of the random variable denoting the number of trials for a complete set of N different types of coupons, which are uniformly distributed. In both cases we present the asymptotic expansion up to the fourth term including the corresponding error term. Then, for both problems we derive the full asymptotic expansion as N\rightarrow \infty. We further obtain the leading-order behaviour of the variance, showing that in both problems \mathrm{Var}\sim \frac{π^2}{6}\frac{N^2}{d^2}, and we establish a rate of convergence to the limiting law. Our analysis is based on the Nørlund--Rice integral method applied to an alternating binomial sum and classical tools from asymptotic analysis. The leading asymptotic term for Problem II was obtained by W. Xu and A. K. Tang [\textit{J. Appl. Probab.} \textbf{48} (2011), 1081--1094]. Finally, for both problems, we derive the limiting distribution under the appropriate normalization. As expected, the limit is standard Gumbel; however, the normalization differs between Problems I and II. As an application, we show that Problem~I describes exactly the sequencing-coverage process in combinatorial motif-based DNA data storage, and our expansions yield closed-form coverage estimates for that setting.

math.PR

Equal probabilities maximize the expected deficit in the siblings of the coupon collector

In the siblings (or brotherhood) variant of the coupon collector's problem, a main collector draws coupons until her own album is complete and passes every duplicate down a chain of siblings; the $j$th collector is then left with $U_j^N$ empty places, $j\ge 2$. It has been conjectured [stated as an open problem in the work that introduced the model] that, for every fixed number of coupon types $N$ and every $j\ge 2$, the expected deficit $\E[U_j^N]$ is maximized by the equiprobable coupon distribution. We prove this in a sharp, finite-$N$ form: $\E[U_j^N]$ is strictly larger at the uniform vector than at any other probability vector, and indeed strictly increases along every ray running from an arbitrary distribution toward the uniform one. The proof is exact and elementary in its ingredients. An inclusion--exclusion step turns the governing Poissonized integral into a one-dimensional integral with a separable integrand; a single integration by parts then rewrites the radial derivative of $\E[U_j^N]$ as a positively weighted covariance of an increasing function, whose sign is settled by Chebyshev's correlation inequality. We show that $\E[U_j^N]$ is \emph{not} Schur-concave, so that no majorization or pairwise-smoothing argument can yield the result, and we explain why the recent variance-extremality method of Long~[Long, arXiv:2604.25108, 2026] does not transfer. As by-products we obtain a finite closed form for $\E[U_j^N]$ over subsets of the coupon set and the exact Hessian of $\E[U_j^N]$ at the uniform vector. The argument extends without change to all real $j>1$.

math.PR

Kolmogorov-Type Maximal Inequalities for Independent and Dependent Negative Binomial Random Variables: Sharp Bounds, Sub-Exponential Refinements, and Applications to Overdispersed Count Data

This paper develops Kolmogorov-type maximal inequalities for sums of Negative Binomial random variables under both independence and dependence structures. For independent heterogeneous Negative Binomial variables we derive sharp Markov-type deviation inequalities and Kolmogorov-type bounds expressed in terms of Tweedie dispersion parameters, providing explicit control limits for NB2 generalized linear model monitoring. For dependent count data arising through a shared Gamma mixing variable, we establish a \emph{sub-exponential Bernstein-type refinement} that exploits the Poisson-Gamma hierarchical structure to yield exponentially decaying tail probabilities -- this refinement is new in the literature. Through moment-matched Monte Carlo experiments ($n=20$, 2{,}000 replications), we document a 55\% reduction in mean maximum deviation under appropriate dependence structures, a stabilization effect we explain analytically. A concrete epidemiological application with NB2 parameters calibrated from COVID-19 surveillance data demonstrates practical utility. These results materially advance the applicability of classical maximal inequalities to overdispersed and dependent count data prevalent in public health, insurance, and ecological modeling.

math.ST

Boundedness of Positive Integral Operators on Lorentz-Gamma Spaces

We characterize the boundedness of a positive integral operator $T_K$, with kernel $K\in M_+(\R^{2n})$, between Lorentz-Gamma spaces $Γ_{p,ϕ_2}(\R^n)$ and $Γ_{q,ϕ_1}(\R^n)$, $1<p\le q<\infty$. The key step reduces the $n$-dimensional problem to a one-dimensional weighted norm inequality for the composed operator $T_LS$, where $L=(K^{*_2})^{*_1}$ is the iterated rearrangement of $K$ introduced by Blozinski~\cite{B} and $S$ is the Stieltjes transform. Explicit Muckenhoupt-type conditions are obtained for the case $L(t,s)=(t+s)^{-1}$, corresponding to the iterated Stieltjes operator $S^2$.

math.FA

Increasingly global convergence of Hermite serie

We study the convergence of the Hermite series of measurable functions on the real line. We characterize the norm convergence of truncated partial Hermite sums in rearrangement invariant spaces provided that the truncations vanish sufficiently slowly. Moreover, we provide the necessary and sufficient conditions for convergence in the Orlicz modular.

math.FA

A New Proof Of The Asymptotic Limit Of The $Lp$ Norm Of The Sinc Function

We improve on the inequality $\displaystyle{\frac{1}π\int_{-\infty}^{\infty} (\frac{\sin^2 t}{t^2})^pdt\leq \frac{1}{\sqrt p}, {0.2 cm}p\geq 1,}$ showing that $\displaystyle{\frac{1}π\int_{-\infty}^{\infty} (\frac{\sin^2 t}{t^2})^pdt\leq C(p) \frac{\sqrt{3/π}}{\sqrt p},}$ with $\displaystyle{\lim_{p\longrightarrow \infty} C(p)=1,}$ and indeed that {align*} \displaystyle{\lim_{p\longrightarrow \infty}\frac{1}π\int_{-\infty}^{\infty} (\frac{\sin^2 t}{t^2})^pdt/ \frac{\sqrt{3/π}}{\sqrt p}=1.} {align*}

math.FA