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We make progress on a question by Vemuri on the optimal Gaussian decay of harmonic oscillators, proving the original conjecture up to an arithmetic progression of times. The techniques used are a suitable translation of the problem at hand…

Classical Analysis and ODEs · Mathematics 2022-08-16 Aleksei Kulikov , Lucas Oliveira , João P. G. Ramos

We show that the ratio of a discrete Toeplitz/Hankel determinant and its continuous counterpart equals a Freholm determinant involving continuous orthogonal polynomials. This identity is used to evaluate a triple asymptotic of some discrete…

Probability · Mathematics 2013-05-20 Jinho Baik , Zhipeng Liu

We consider a walker that at each step keeps the same direction with a probabilitythat depends on the time already spent in the direction the walker is currently moving. In this paper, we study some asymptotic properties of this persistent…

Probability · Mathematics 2015-09-15 Peggy Cénac , Basile De Loynes , Arnaud Le Ny , Yoann Offret

Our interest is in the cumulative probabilities Pr(L(t) \le l) for the maximum length of increasing subsequences in Poissonized ensembles of random permutations, random fixed point free involutions and reversed random fixed point free…

Mathematical Physics · Physics 2009-11-07 Alexei Borodin , Peter J. Forrester

In his Ph.D. thesis, Ira Gessel proved a reciprocity formula for noncommutative symmetric functions which enables one to count words and permutations with restrictions on the lengths of their increasing runs. We generalize Gessel's theorem…

Combinatorics · Mathematics 2017-05-15 Yan Zhuang

Our starting point is a basic problem in Hermite interpolation theory, namely determining the least degree of a homogeneous polynomial that vanishes to some specified order at every point of a given finite set. We solve this problem if the…

Commutative Algebra · Mathematics 2018-11-07 Uwe Nagel , Bill Trok

Assuming that both a function and its Fourier transform are dominated by a Gaussian of large variance, it is shown that the Hermite coefficients of the function decay exponentially. A sharp estimate for the rate of exponential decay is…

Analysis of PDEs · Mathematics 2008-01-16 M. K. Vemuri

In this paper, we take the first step towards an extension of the nonlinear steepest descent method of Deift, Its and Zhou to the case of operator Riemann-Hilbert problems. In particular, we provide long range asymptotics for a Fredholm…

Functional Analysis · Mathematics 2007-05-23 Spyridon Kamvissis

Besides using the laser beam, it is very tempting to directly testify the Bell inequality at high energy experiments where the spin correlation is exactly what the original Bell inequality investigates. In this work, we follow the proposal…

High Energy Physics - Phenomenology · Physics 2011-03-31 Xi-Qing Hao , Hong-Wei Ke , Yi-Bing Ding , Peng-Nian Shen , Xue-Qian Li

Consider an iterated function system consisting of similarities on the complex plane of the form $g_{i}(z) = \lambda_i z + t_i,\ \lambda_i, t_i \in \mathbb{C},\ |\lambda_i|<1, i=1,\ldots, k$. We prove that for almost every choice of…

Dynamical Systems · Mathematics 2023-08-31 Boris Solomyak , Adam Śpiewak

We generalize standard credal set models for imprecise probabilities to include higher order credal sets -- confidences about confidences. In doing so, we specify how an agent's higher order confidences (credal sets) update upon observing…

Statistics Theory · Mathematics 2021-07-20 Justus Hibshman , Tim Weninger

In this paper we revisit Talagrand's proof of concentration inequality for empirical processes. We give a different shorter proof of the main technical lemma that guarantees the existence of a certain kernel. Our proof provides the almost…

Probability · Mathematics 2021-04-13 Dmitry Panchenko

General potential theories concern the study of functions which are subharmonic with respect to a suitable constraint set (called a subequation) in the space of 2-jets. While interesting in their own right, general potential theories are…

Analysis of PDEs · Mathematics 2025-09-18 F. Reese Harvey , Kevin R. Payne

Stochastic gradient descent (SGD) and its variants have established themselves as the go-to algorithms for large-scale machine learning problems with independent samples due to their generalization performance and intrinsic computational…

Machine Learning · Statistics 2025-08-25 Hao Chen , Lili Zheng , Raed Al Kontar , Garvesh Raskutti

Wavelet-type random series representations of the well-known Fractional Brownian Motion (FBM) and many other related stochastic processes and fields have started to be introduced since more than two decades. Such representations provide…

Probability · Mathematics 2023-03-10 Antoine Ayache , Julien Hamonier , Laurent Loosveldt

A key issue in the handling of temporal data is the treatment of persistence; in most approaches it consists in inferring defeasible confusions by extrapolating from the actual knowledge of the history of the world; we propose here a…

Artificial Intelligence · Computer Science 2013-03-08 Dimiter Driankov , Jerome Lang

We propose an iterative estimating equations procedure for analysis of longitudinal data. We show that, under very mild conditions, the probability that the procedure converges at an exponential rate tends to one as the sample size…

Statistics Theory · Mathematics 2007-12-18 Jiming Jiang , Yihui Luan , You-Gan Wang

We study the effective estimation of the diffusivity and Hurst parameter for the homogenized limit of a class of slow/fast systems. Depending on the system parameters, this limit solves a stochastic differential equation driven by either a…

Probability · Mathematics 2026-05-01 Pablo Ramses Alonso-Martin

We give an estimate of the general divided differences $[x_0,\dots,x_m;f]$, where some of the $x_i$'s are allowed to coalesce (in which case, $f$ is assumed to be sufficiently smooth). This estimate is then applied to significantly…

Classical Analysis and ODEs · Mathematics 2019-01-15 K. A. Kopotun , D. Leviatan , I. A. Shevchuk

A celebrated result by Gordon allows one to compare the min-max behavior of two Gaussian processes if certain inequality conditions are met. The consequences of this result include the Gaussian min-max (GMT) and convex Gaussian min-max…

Machine Learning · Computer Science 2024-10-16 Danil Akhtiamov , David Bosch , Reza Ghane , K Nithin Varma , Babak Hassibi