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Sampling theory in spaces other than the space of band-limited functions has recently received considerable attention. This is in part because the band-limitedness assumption is not very realistic in many applications. In addition,…

Classical Analysis and ODEs · Mathematics 2007-05-23 Cristina Blanco , Carlos Cabrelli , Sigrid Heineken

We consider a length functional for $C^1$ curves of fixed degree in graded manifolds equipped with a Riemannian metric. The first variation of this length functional can be computed only if the curve can be deformed in a suitable sense, and…

Metric Geometry · Mathematics 2021-10-14 Giovanna Citti , Gianmarco Giovannardi , Manuel Ritoré

We classify all invariants of the functor $I^n$ (powers of the fundamental ideal of the Witt ring) with values in $A$, that it to say functions $I^n(K)\rightarrow A(K)$ compatible with field extensions, in the cases where $A(K)=W(K)$ is the…

K-Theory and Homology · Mathematics 2020-06-24 Nicolas Garrel

The classical and quantal features of a quadrupole coherent state and its projections over angular momentum and boson number are quantitatively analyzed in terms of the departure of the Heisenberg uncertainty relations from the classical…

Nuclear Theory · Physics 2015-06-12 A. A. Raduta , C. M. Raduta

We study smooth function spaces of Gelfand-Shilov type, with global behavior governed through a translation-invariant Banach function space and localized via a weight function system. We clarify the roles of the translation-invariant Banach…

Functional Analysis · Mathematics 2025-10-31 Lenny Neyt , Yoshihiro Sawano

In this study, we introduce a method for learning group (known or unknown) equivariant functions by learning the associated quadratic form $x^T A x$ corresponding to the group from the data. Certain groups, known as orthogonal groups,…

Machine Learning · Computer Science 2025-10-16 Pavan Karjol , Vivek V Kashyap , Rohan Kashyap , Prathosh A P

Deep learning models lack shift invariance, making them sensitive to input shifts that cause changes in output. While recent techniques seek to address this for images, our findings show that these approaches fail to provide…

Machine Learning · Computer Science 2025-02-28 Berken Utku Demirel , Christian Holz

Invariant functions and metrics are studied on various classes of domains in $\Bbb C^n.$

Complex Variables · Mathematics 2012-09-03 Nikolai Nikolov

It is well known that Brownian motion enjoys several distributional invariances such as the scaling property and the time reversal. In this paper, we prove another invariance of Brownian motion that is compatible with the time reversal. The…

Probability · Mathematics 2023-10-20 Yuu Hariya

One of basic difficulties of machine learning is handling unknown rotations of objects, for example in image recognition. A related problem is evaluation of similarity of shapes, for example of two chemical molecules, for which direct…

Machine Learning · Computer Science 2018-01-04 Jarek Duda

We prove a conjecture of Boucksom-Demailly-P\u{a}un-Peternell, namely that on a projective manifold $X$ the cone of pseudoeffective classes in $H^{1,1}_{\mathbb{R}}(X)$ is dual to the cone of movable classes in $H^{n-1,n-1}_{\mathbb{R}}(X)$…

Complex Variables · Mathematics 2016-12-06 David Witt Nyström , Sébastien Boucksom

We give an introductory account of the recently identified gauge invariance of the equilibrium statistical mechanics of classical many-body systems [J. M\"uller et al., Phys. Rev. Lett. Phys. Rev. Lett. 133, 217101 (2024)]. The gauge…

Statistical Mechanics · Physics 2025-03-26 Johanna Müller , Florian Sammüller , Matthias Schmidt

We consider a generalization of the weighted random ball model. The model is driven by a random Poisson measure with a product heavy tailed intensity measure. Such a model typically represents the transmission of a network of stations with…

Probability · Mathematics 2010-03-01 Jean-Christophe Breton , Clement Dombry

We study real-valued, continuous and translation invariant valuations defined on the space of quasi-concave functions of N variables. In particular, we prove a homogeneous decomposition theorem of McMullen type, and we find a representation…

Metric Geometry · Mathematics 2017-03-21 Andrea Colesanti , Nico Lombardi , Lukas Parapatits

Determination of quasi-invariant generalized functions is important for a variety of problems in representation theory, notably character theory and restriction problems. In this note, we review some new and easy-to-use techniques to show…

Representation Theory · Mathematics 2012-12-27 Dihua Jiang , Binyong Sun , Chen-Bo Zhu

We explore the Bohr inequality involving the Fourier transforms of complex valued integrable and square integrable functions defined on a second countable compact topological group. We also investigate the connection of the Bohr phenomenon…

Functional Analysis · Mathematics 2020-11-26 Bappaditya Bhowmik , Nilanjan Das

There is a natural conjugation action on the set of endomorphism of $\P^N$ of fixed degree $d \geq 2$. The quotient by this action forms the moduli of degree $d$ endomorphisms of $\P^N$, denoted $\mathcal{M}_d^N$. We construct invariant…

Dynamical Systems · Mathematics 2019-08-09 Benjamin Hutz

Boole polynomials play an important role in the area of number theory, algebra and umbral calculus. In this paper, we investigate some properties of Boole polynomials and consider Witt-type formulas for the Boole numbers and polynomials.…

Number Theory · Mathematics 2013-10-31 Dae San Kim , Taekyun Kim

We apply a new bosonization technique to relativistic field theories of fermions whose partition function is dominated by bosonic composites, and derive the effective action for these bosons. The derivation respects all symmetries,…

High Energy Physics - Lattice · Physics 2010-10-27 Sergio Caracciolo , Victor Laliena , Fabrizio Palumbo

W-transforms are introduced as uniformity-preserving univariate transformations on the unit interval induced by distribution functions and piecewise strictly monotone functions, and their properties are investigated. When applied…

Methodology · Statistics 2025-10-01 Marius Hofert , Zhiyuan Pang