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We study the Gross-Pitaevskii hierarchy on the spatial domain $\mathbb{T}^3$. By using an appropriate randomization of the Fourier coefficients in the collision operator, we prove an averaged form of the main estimate which is used in order…

Analysis of PDEs · Mathematics 2015-09-07 Vedran Sohinger , Gigliola Staffilani

Sufficient conditions for comparing the convolutions of heterogeneous gamma random variables in terms of the usual stochastic order are established. Such comparisons are characterized by the Schur convexity properties of the cumulative…

Probability · Mathematics 2016-01-20 Farbod Roosta-Khorasani , Gabor J. Szekely

We develop a new approach of extension calculus in the category of strict polynomial functors, based on Troesch complexes. We obtain new short elementary proofs of numerous classical Ext-computations as well as new results. In particular,…

Representation Theory · Mathematics 2012-10-18 Antoine Touzé

We consider the roots of uniformly chosen complex and real reciprocal polynomials of degree $N$ whose Mahler measure is bounded by a constant. After a change of variables this reduces to a generalization of Ginibre's complex and real…

Classical Analysis and ODEs · Mathematics 2019-12-02 Christopher D. Sinclair , Maxim L. Yattselev

We present positivity conjectures for the Schur expansion of Jack symmetric functions in two bases given by binomial coefficients. Partial results suggest that there are rich combinatorics to be found in these bases, including Eulerian…

Combinatorics · Mathematics 2019-07-02 Per Alexandersson , James Haglund , George Wang

This article studies the inhomogeneous geometric polynuclear growth model, the distribution of which is related to Schur functions. We explain a method to derive its distribution functions in both space-like and time-like directions,…

Probability · Mathematics 2022-03-29 Kurt Johansson , Mustazee Rahman

We analyze Su-Schrieffer-Heeger (SSH) models using the doubling method for orthogonal polynomial sequences. This approach yields the analytical spectrum and exact eigenstates of the models. We demonstrate that the standard SSH model is…

Mathematical Physics · Physics 2026-05-06 Nicolas Crampé , Quentin Labriet , Lucia Morey , Gilles Parez , Luc Vinet

A wide range of numerical methods exists for computing polynomial approximations of solutions of ordinary differential equations based on Chebyshev series expansions or Chebyshev interpolation polynomials. We consider the application of…

Symbolic Computation · Computer Science 2014-07-11 Alexandre Benoit , Mioara Joldes , Marc Mezzarobba

We establish exponential inequalities for a class of V-statistics under strong mixing conditions. Our theory is developed via a novel kernel expansion based on random Fourier features and the use of a probabilistic method. This type of…

Statistics Theory · Mathematics 2020-01-07 Yandi Shen , Fang Han , Daniela Witten

Schubert polynomials are a basis for the polynomial ring that represent Schubert classes for the flag manifold. In this paper, we introduce and develop several new combinatorial models for Schubert polynomials that relate them to other…

Combinatorics · Mathematics 2020-03-05 Sami Assaf

We describe in detail the solution of the extension of the chiral Gaussian Unitary Ensemble (chGUE) into the complex plane. The correlation functions of the model are first calculated for a finite number of N complex eigenvalues, where we…

High Energy Physics - Theory · Physics 2008-11-26 G. Akemann

The product of any finite number of factorial Schur functions can be expanded as a $Z[y]$-linear combination of Schur functions. We give a rule for computing the coefficients in such an expansion which generalizes a specialization of the…

Combinatorics · Mathematics 2008-03-04 V. Kreiman

We study a multi-symmetric generalization of the classical Schur functions called the multi-symmetric Schur functions. These functions form an integral basis for the ring of multi-symmetric functions indexed by tuples of partitions and are…

Combinatorics · Mathematics 2025-09-23 Milo Bechtloff Weising

We describe a generalization of Hashimoto and Kurano's Cauchy filtration for divided powers algebras. This filtration is then used to provide a cellular structure for generalized Schur algebras associated to an arbitrary cellular algebra.…

Representation Theory · Mathematics 2020-02-10 Jonathan D. Axtell

This publication is an exercise which extends to two variables the Christoffel's construction of orthogonal polynomials for potentials of one variable with external sources. We generalize the construction to biorthogonal polynomials. We…

High Energy Physics - Theory · Physics 2007-05-23 M. C. Bergère

Correlation functions for matrix ensembles with orthogonal and unitarysymplectic rotation symmetry are more complicated to calculate than in the unitary case. The supersymmetry method and the orthogonal polynomials are two techniques to…

Mathematical Physics · Physics 2010-03-19 Mario Kieburg , Thomas Guhr

In this paper we generalize and specialize generating functions for classical orthogonal polynomials, namely Jacobi, Gegenbauer, Chebyshev and Legendre polynomials. We derive a generalization of the generating function for Gegenbauer…

Classical Analysis and ODEs · Mathematics 2013-06-27 Howard Cohl , Connor MacKenzie

We consider the scaling solutions of Smoluchowski's equation of irreversible aggregation, for a non gelling collision kernel. The scaling mass distribution f(s) diverges as s^{-tau} when s->0. tau is non trivial and could, until now, only…

Statistical Mechanics · Physics 2016-08-31 Stephane Cueille , Clement Sire

Multivariate extensions of the Krawtchouk polynomials have been studied by numerous authors in recent decades by exploring new connections to probability, representation theory and quantum integrability. We develop a theory of multivariate…

Representation Theory · Mathematics 2026-05-07 Plamen Iliev , Songhao Zhu

A fundamental drawback of kernel-based statistical models is their limited scalability to large data sets, which requires resorting to approximations. In this work, we focus on the popular Gaussian kernel and on techniques to linearize…

Machine Learning · Statistics 2022-04-13 Jonas Wacker , Maurizio Filippone
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