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In this paper, we give tight bounds for the normalized Laplacian eigenvalues of hypergraphs that are not necessarily uniform, and provide an edge version interlacing theorem, a Cheeger inequality, and a discrepancy inequality that are…

Combinatorics · Mathematics 2025-04-15 Leyou Xu , Bo Zhou

In meta analysis, multiple hypothesis testing and many other methods, p-values are utilized as inputs and assumed to be uniformly distributed over the unit interval under the null hypotheses. If data used to generate p-values have discrete…

Methodology · Statistics 2026-02-24 Joshua Habiger , Pratyaydipta Rudra

We estimate the magnetic Laplacian energy norm in appropriate planar domains under a weak regularity hypothesis on the magnetic field. Our main contribution is an averaging estimate, valid in small cells, allowing us to pass from…

Spectral Theory · Mathematics 2021-11-30 Ayman Kachmar , Mohammad Wehbe

In this paper, we show that the diagonal of a high-dimensional sample covariance matrix stemming from $n$ independent observations of a $p$-dimensional time series with finite fourth moments can be approximated in spectral norm by the…

Probability · Mathematics 2022-01-05 Johannes Heiny

We provide explicit upper bounds for the eigenvalues of the Laplacian on a finite metric tree subject to standard vertex conditions. The results include estimates depending on the average length of the edges or the diameter. In particular,…

Spectral Theory · Mathematics 2016-07-28 Jonathan Rohleder

It is shown that the fundamental eigenvalue ratio \lambda_2 / \lambda_1 of the p-Laplacian is bounded by a quantity depending only on the dimension N and p.

Spectral Theory · Mathematics 2007-05-23 J. Fleckinger , E. M. Harrell , F. de Thélin

Mean value formulas are of great importance in the theory of partial differential equations: many very useful results are drawn, for instance, from the well known equivalence between harmonic functions and mean value properties. In the…

Analysis of PDEs · Mathematics 2021-05-28 Claudia Bucur , Marco Squassina

We present three equivalent definitions of the fractional $p$-Laplacian $(-\Delta_{\mathbb{H}^{n}})^{s}_{p}$, $0<s<1$, $p>1$, with normalizing constants, on hyperbolic spaces. The explicit values of the constants enable us to study the…

Analysis of PDEs · Mathematics 2026-02-03 Jongmyeong Kim , Minhyun Kim , Ki-Ahm Lee

We prove large and moderate deviation principles for the distribution of an empirical mean conditioned by the value of the sum of discrete i.i.d. random variables. Some applications for combinatoric problems are discussed.

Probability · Mathematics 2007-07-11 Fabrice Gamboa , Thierry Klein , Clémentine Prieur

This note presents an example of an increasing sequence $(\lambda_l)_{l=1}^\infty$ such that the maximal operators associated to normalized discrete spherical convolution averages \[ \sup_{l\geq…

Classical Analysis and ODEs · Mathematics 2018-09-20 Brian Cook

Let $p$ be an odd prime, and suppose $f$ is an $L^2$-normalised newform for $\Gamma_0(p^n)$ with bounded spectral parameters and trivial central character. We prove the optimal $L^4$-norm bound $\lVert f \rVert_4…

Number Theory · Mathematics 2026-02-24 Marius Fischer

We introduce methods to bound the mean of a discrete distribution (or finite population) based on sample data, for random variables with a known set of possible values. In particular, the methods can be applied to categorical data with…

Statistics Theory · Mathematics 2021-11-16 Eric Bax , Frédéric Ouimet

This paper demonstrates that basic statistics (mean, variance) of the logarithm of the variate itself can be used in the calculation of differential entropy among random variables known to be multiples and powers of a common underlying…

Information Theory · Computer Science 2009-01-26 Thomas M. Eccardt

Persistent Laplacians are matrix operators that track how the shape and structure of data transform across scales and are popularly adopted in biology, physics, and machine learning. Their eigenvalues are concise descriptors of geometric…

Machine Learning · Computer Science 2025-06-27 Le Vu Anh , Mehmet Dik , Nguyen Viet Anh

The spectrum of the normalized graph Laplacian yields a very comprehensive set of invariants of a graph. In order to understand the information contained in those invariants better, we systematically investigate the behavior of this…

Combinatorics · Mathematics 2012-10-19 Anirban Banerjee , Jürgen Jost

We study perturbations of the discrete Laplacian associated to discrete analogs of cusps and funnels. We perturb the metric and the potential in a long-range way. We establish a propagation estimate and a Limiting Absorption Principle away…

Spectral Theory · Mathematics 2020-03-31 Nassim Athmouni , Marwa Ennaceur , Sylvain Golenia

We develop a Hellmann--Feynman type perturbation theory for the discrete signed $p$-Laplacian and apply it to a parametrized perturbation by edge cuts. We show that the eigenvalues of the signed $p$-Laplacian can be characterized as citical…

Analysis of PDEs · Mathematics 2025-09-09 Gregory Berkolaiko , Matthias Hofmann

We provide a unified strategy to show that solutions of dynamic programming principles associated to the $p$-Laplacian converge to the solution of the corresponding Dirichlet problem. Our approach includes all previously known cases for…

Analysis of PDEs · Mathematics 2020-03-18 Félix del Teso , Juan J. Manfredi , Mikko Parviainen

We obtain some regularity results for solutions to vectorial $p$-Laplace equations $$ -{\boldsymbol \Delta}_p{\boldsymbol u}=-\operatorname{\bf div}(|D{\boldsymbol u}|^{p-2}D{\boldsymbol u}) = {\boldsymbol f}(x,{\boldsymbol u})\,\, \mbox{…

Analysis of PDEs · Mathematics 2024-03-13 Luigi Montoro , Luigi Muglia , Berardino Sciunzi , Domenico Vuono

Inspired by persistent homology in topological data analysis, we introduce the homological eigenvalues of the graph $p$-Laplacian $\Delta_p$, which allows us to analyse and classify non-variational eigenvalues. We show the stability of…

Spectral Theory · Mathematics 2023-11-28 Dong Zhang
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