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Let $\Sigma_{2n}$ be the set of all partitions of the even integers from the interval $(4,2n], n>2,$ into two odd prime parts. We select a partition from the set $\Sigma_{2n}$ uniformly at random. Let $2G_n$ be the number partitioned by…

Number Theory · Mathematics 2015-08-20 Ljuben Mutafchiev

Suppose $\Pi$ is an exchangeable random partition of the positive integers and $\Pi_n$ is its restriction to $\{1, ..., n\}$. Let $K_n$ denote the number of blocks of $\Pi_n$, and let $K_{n,r}$ denote the number of blocks of $\Pi_n$…

Probability · Mathematics 2010-07-14 Jason Schweinsberg

Maximum mean discrepancies (MMDs) like the kernel Stein discrepancy (KSD) have grown central to a wide range of applications, including hypothesis testing, sampler selection, distribution approximation, and variational inference. In each…

Machine Learning · Statistics 2025-03-26 Alessandro Barp , Carl-Johann Simon-Gabriel , Mark Girolami , Lester Mackey

In parameterized algorithmics, the process of kernelization is defined as a polynomial time algorithm that transforms the instance of a given problem to an equivalent instance of a size that is limited by a function of the parameter. As,…

Computational Complexity · Computer Science 2019-03-01 Jouke Witteveen , Ralph Bottesch , Leen Torenvliet

Kerning is the task of setting appropriate horizontal spaces for all possible letter pairs of a certain font. One of the difficulties of kerning is that the appropriate space differs for each letter pair. Therefore, for a total of 52…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Kei Nakatsuru , Seiichi Uchida

We reprove the well known fact that the energy distance defines a metric on the space of Borel probability measures on a Hilbert space with finite first moment by a new approach, by analyzing the behavior of the Gaussian kernel on Hilbert…

Functional Analysis · Mathematics 2021-02-02 Jean Carlo Guella

The proper thinness of a graph is an invariant that generalizes the concept of a proper interval graph. Every graph has a numerical value of proper thinness and the graphs with proper thinness~1 are exactly the proper interval graphs. A…

Combinatorics · Mathematics 2025-05-19 Flavia Bonomo-Braberman , Ignacio Maqueda , Nina Pardal

We critically discuss the measure of very short time intervals. By means of a Gedankenexperiment, we describe an ideal clock based on the occurrence of completely random events. Many previous thought experiments have suggested fundamental…

General Relativity and Quantum Cosmology · Physics 2016-03-14 Luciano Burderi , Tiziana Di Salvo , Rosario Iaria

In kernel methods, the median heuristic has been widely used as a way of setting the bandwidth of RBF kernels. While its empirical performances make it a safe choice under many circumstances, there is little theoretical understanding of why…

Statistics Theory · Mathematics 2018-10-31 Damien Garreau , Wittawat Jitkrittum , Motonobu Kanagawa

There is a well-known bijection between finite binary sequences and integer partitions. Sequences of length r correspond to partitions of perimeter r+1. Motivated by work on rational numbers in the Calkin-Wilf tree, we classify partitions…

Combinatorics · Mathematics 2024-07-04 David J. Hemmer , Karlee J. Westrem

It is argued that there are characteristic intervals associated with any particle that can be derived without reference to the speed of light $c$. Such intervals are inferred from zeros of wavefunctions which are solutions to the…

General Physics · Physics 2015-01-12 Mark D. Roberts

On $\mathbb R^N$ equipped with a normalized root system $R$ and a multiplicity function $k\geq 0$ let us consider a (non-radial) kernel $K(\mathbf x)$ which has properties similar to those from the classical theory. We prove that a singular…

Functional Analysis · Mathematics 2019-10-16 Jacek Dziubański , Agnieszka Hejna

As it was recently shown, the colour singlet BFKL kernel, taken in Moebius representation in the space of impact parameters, can be written in quasi-conformal shape, which is unbelievably simple compared with the conventional form of the…

High Energy Physics - Theory · Physics 2015-06-05 V. S. Fadin , R. Fiore , A. Papa

In Einstein gravity, matter with an arbitrarily small density can be a black hole. Pressure in the star diverges if size of the star is smaller than 9/8 of the Schwarzschild radius, implying the gravitational collapse into a black hole. By…

High Energy Physics - Theory · Physics 2026-03-27 Yoshinori Matsuo

We investigate classical-quantum correspondence for kicked Harper model for extremely small values of the Planck constant $\hbar$. In the asymmetric case a pure quantum state shows clear signature of classical diffusive as well as super…

Chaotic Dynamics · Physics 2007-05-23 Indubala I Satija , Tomaz Prosen

These classical inequalities allow one to estimate the number of negative eigenvalues and the sums $S_{\gamma}=\sum |\lambda_i|^{\gamma}$ for a wide class of Schr\"{o}dinger operators. We provide a detailed proof of these inequalities for…

Mathematical Physics · Physics 2016-04-04 S. Molchanov , B. Vainberg

The pairing gap for $^{53}$Ca obtained from new experimental data on the masses of $^{52-54}$Ca has the smallest value yet observed. This is explained in the framework of the nuclear shell model with schematic and realistic Hamiltonians as…

Nuclear Theory · Physics 2014-11-26 B. Alex Brown

In this paper, we concern the kernel of linear operator for a class of Grushin equation. First, we study the kernel space of linear operator for a general Grushin equation. Then, we provide an exact expression for the kernel space of linear…

Analysis of PDEs · Mathematics 2024-09-17 Yawei Wei , Xiaodong Zhou

We study the loss of quantumness caused by time dilation [1] for a Schr\"odinger cat state. We give a holistic view of the quantum to classical transition by comparing the dynamics of several nonclassicality indicators, such as the Wigner…

Quantum Physics · Physics 2017-08-02 Boris Sokolov , Iiro Vilja , Sabrina Maniscalco

We introduce kernel density machines (KDM), an agnostic kernel-based framework for learning the Radon-Nikodym derivative (density) between probability measures under minimal assumptions. KDM applies to general measurable spaces and avoids…

Machine Learning · Statistics 2026-03-27 Andrea Della Vecchia , Damir Filipovic , Paul Schneider