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We address the formation and propagation of multi-spot soliton packets in saturable Kerr nonlinear media with an imprinted harmonic transverse modulation of the refractive index. We show that, in sharp contrast to homogeneous media where…

Optics · Physics 2009-11-10 Yaroslav V. Kartashov , Victor A. Vysloukh , Lluis Torner

Thermal statistical models are simple and effective tool to describe particle production in high energy heavy ion collision. It is shown that for higher moments finite volume corrections become important observable quantities. They make…

High Energy Physics - Theory · Physics 2008-12-18 Ludwik Turko

We calculate reduced moments $\overline \xi_q$ of the matter density fluctuations, up to order $q=5$, from counts in cells produced by Particle--Mesh numerical simulations with scale--free Gaussian initial conditions. We use power--law…

Astrophysics · Physics 2009-10-22 F. Lucchin , S. Matarrese , A. L. Melott , L. Moscardini

In this paper, we investigate certain combinatorial numbers, the \textit{moment generating Stirling numbers}. They are a special case of Hsu's generalized Stirling numbers and satisfy many more properties and combinatorial identities than…

Combinatorics · Mathematics 2022-06-20 Ludwig Frank

This paper introduces a machine learning approach to take a nonlinear differential-equation model that exhibits qualitative agreement with a physical experiment over a range of parameter values and produce a hybrid model that also exhibits…

Dynamical Systems · Mathematics 2022-08-24 K. H. Lee , D. A. W. Barton , L. Renson

Ordinal Patterns are a time-series data analysis tool used as a preliminary step to construct the Permutation Entropy which itself allows the same characterization of dynamics as chaotic or regular as more theoretical constructs such as the…

Adaptation and Self-Organizing Systems · Physics 2021-02-24 I. Gunther , Arjendu K. Pattanayak , Andrés Aragoneses

A mixture of Gaussians fit to a single curved or heavy-tailed cluster will report that the data contains many clusters. To produce more appropriate clusterings, we introduce a model which warps a latent mixture of Gaussians to produce…

Machine Learning · Computer Science 2014-08-12 Tomoharu Iwata , David Duvenaud , Zoubin Ghahramani

A mixture of Gaussians fit to a single curved or heavy-tailed cluster will report that the data contains many clusters. To produce more appropriate clusterings, we introduce a model which warps a latent mixture of Gaussians to produce…

Machine Learning · Statistics 2013-03-25 Tomoharu Iwata , David Duvenaud , Zoubin Ghahramani

Eigenvalues are defined for any element of an algebra of observables and do not require a representation in terms of wave functions or density matrices. A systematic algebraic derivation based on moments is presented here for the harmonic…

Quantum Physics · Physics 2021-07-01 Martin Bojowald , Jonathan Guglielmon , Martijn van Kuppeveld

Multivariate longitudinal data of mixed-type are increasingly collected in many science domains. However, algorithms to cluster this kind of data remain scarce, due to the challenge to simultaneously model the within- and between-time…

Machine Learning · Statistics 2025-09-16 Francesco Amato , Julien Jacques

Mixed-moment models, introduced before for one space dimension, are a modification of the method of moments applied to a (linear) kinetic equation, by choosing mixtures of different partial moments. They are well-suited to handle such…

Analysis of PDEs · Mathematics 2018-01-11 Florian Schneider , Jochen Kall , Andreas Roth

We introduce a new method for studying murmurations, based on random matrix theory. With this method, we exhibit murmurations or similar phenomena: assuming ratios conjectures, for elliptic curves ordered by height, quadratic twists of a…

Number Theory · Mathematics 2025-04-23 Alex Cowan

The main purpose of this paper is to apply the theory of vector lattices and the related abstract modular convergence to the context of Mellin-type kernels and (non)linear vector lattice-valued operators, following the construction of an…

Functional Analysis · Mathematics 2022-11-29 Antonio Boccuto , Anna Rita Sambucini

Transformers have emerged as a powerful neural network architecture capable of tackling a wide range of learning tasks. In this work, we provide a theoretical analysis of their ability to automatically extract structure from data in an…

Machine Learning · Statistics 2025-10-29 Rodrigo Maulen-Soto , Pierre Marion , Claire Boyer

We construct moment functions that are Neyman-orthogonal to a chosen order in parametric moment condition models. These moment functions reduce sensitivity to nuisance estimation error and, as such, offer a unified and tractable route to…

Econometrics · Economics 2026-05-12 Stéphane Bonhomme , Koen Jochmans , Whitney K. Newey , Martin Weidner

We apply the bootstrap technique to find the moments of certain multi-trace and multi-matrix random matrix models suggested by noncommutative geometry. Using bootstrapping we are able to find the relationships between the coupling constant…

High Energy Physics - Theory · Physics 2022-02-09 Hamed Hessam , Masoud Khalkhali , Nathan Pagliaroli

Linear mixed models with large imbalanced crossed random effects structures pose severe computational problems for maximum likelihood estimation and for Bayesian analysis. The costs can grow as fast as $N^{3/2}$ when there are N…

Methodology · Statistics 2017-05-30 K. Gao , A. B. Owen

We have embedded an artificial atom, a superconducting transmon qubit, in a 1D open space and investigated the scattering properties of an incident microwave coherent state. By studying the statistics of the reflected and transmitted…

Quantum Physics · Physics 2012-06-28 Io-Chun Hoi , Tauno Palomaki , Göran Johansson , Joel Lindkvist , Per Delsing , C. M. Wilson

In this note, we provide a refined analysis of Mitra's algorithm \cite{mitra2008clustering} for classifying general discrete mixture distribution models. Built upon spectral clustering \cite{mcsherry2001spectral}, this algorithm offers…

Machine Learning · Computer Science 2024-05-31 Mohamed Seif , Yanxi Chen

The Mellin transform is usually applied in probability theory to the product of independent random variables. In recent times the machinery of the Mellin transform has been adopted to describe the L\'evy stable distributions, and more…

Probability · Mathematics 2007-05-23 Francesco Mainardi , Gianni Pagnini , Rudolf Gorenflo