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We establish a linearization criterion for skew products of contractions in any dimension. We prove their smooth or holomorphic parameter dependence. In the smooth setting, we use the language of tame Fr\'echet spaces. We apply our result…

Dynamical Systems · Mathematics 2022-10-12 Pierre Berger , Bernhard Reinke

This paper sheds new light on several interrelated topics of second-order variational analysis, both in finite and infinite-dimensional settings. We establish new relationships between second-order growth conditions on functions, the basic…

Optimization and Control · Mathematics 2013-04-30 D. Drusvyatskiy , B. S. Mordukhovich , T. T. A. Nghia

We introduce a notion of constructibility for \'etale sheaves with torsion coefficients over a suitable class of adic spaces. This notion is related to the classical notion of constructibility for schemes via the nearby cycles functor. We…

Algebraic Geometry · Mathematics 2017-07-13 Ildar Gaisin , John Welliaveetil

We develop a dimension theory for D-semianalytic sets over an arbitrary non-Archimedean complete field. Our main results are the equivalence of several notions of dimension and a theorem on additivity of dimensions of projections and fibers…

Logic · Mathematics 2007-05-23 Y. Firat Celikler

The problem of finding of analytical gradients (derivatives over atoms coordinates) of solvation energies can be decomposed on two subtasks: at the first stage we search for parameters of the superficial devices (three coordinates, three…

Chemical Physics · Physics 2013-03-19 Oleg Kupervasser , N. E. Wanner

Changes in the extent of local concavity along with changes in surface roughness of binding sites of proteins have long been considered as useful markers to identify functional sites of proteins. However, an algorithm that describes the…

Biomolecules · Quantitative Biology 2011-11-29 Anirban Banerji

We study the interaction of structural subtyping with parametric polymorphism and recursively defined type constructors. Although structural subtyping is undecidable in this setting, we describe a notion of parametricity for type…

Programming Languages · Computer Science 2023-10-30 Henry DeYoung , Andreia Mordido , Frank Pfenning , Ankush Das

In previous work, we introduced a method for modeling a configuration of objects in 2D and 3D images using a mathematical "medial/skeletal linking structure." In this paper, we show how these structures allow us to capture positional…

Computer Vision and Pattern Recognition · Computer Science 2017-06-02 James Damon , Ellen Gasparovic

Let $k \subset K$ be an extension of fields, and let $A \subset M_{n}(K)$ be a $k$-algebra. We study parameter spaces of $m$-dimensional subspaces of $K^{n}$ which are invariant under $A$. The space $\mathbb{F}_{A}(m,n)$, whose $R$-rational…

Algebraic Geometry · Mathematics 2009-02-27 A. Nyman

Dimension is a fundamental property of objects and the space in which they are embedded. Yet ideal notions of dimension, as in Euclidean spaces, do not always translate to physical spaces, which can be constrained by boundaries and…

Physics and Society · Physics 2022-07-06 Robert L. Peach , Alexis Arnaudon , Mauricio Barahona

Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or…

Computation · Statistics 2016-05-03 Tiangang Cui , Youssef M. Marzouk , Karen E. Willcox

We introduce new Lagrangian cycles which encode local contributions of Lefschetz numbers of constructible sheaves into geometric objects. We study their functorial properties and apply them to Lefschetz fixed point formulas with…

Algebraic Geometry · Mathematics 2008-12-25 Yutaka Matsui , Kiyoshi Takeuchi

We define a new geometric object--the stack of local systems with restricted variation. We formulate a version of the categorical geometric Langlands conjecture that makes sense for any constructible sheaf theory (such as l-adic sheaves).…

Algebraic Geometry · Mathematics 2022-04-07 D. Arinkin , D. Gaitsgory , D. Kazhdan , S. Raskin , N. Rozenblyum , Y. Varshavsky

The integrability condition called shape invariance is shown to have an underlying algebraic structure and the associated Lie algebras are identified. These shape-invariance algebras transform the parameters of the potentials such as…

Quantum Physics · Physics 2009-10-30 A. B. Balantekin

This study aims on proposing a new structure for constructing Bernstein-like bases. The structure uses an auxiliary function and a shape parameter to construct a new family of bases from any family of blending functions. The new family of…

Numerical Analysis · Mathematics 2024-05-14 Bahareh Nouri , Jamshid Saeidian

In this paper we consider the dyadic effect introduced in complex networks when nodes are distinguished by a binary characteristic. Under these circumstances two independent parameters, namely dyadicity and heterophilicity, are able to…

Combinatorics · Mathematics 2019-04-12 Matteo Cinelli , Giovanna Ferraro , Antonio Iovanella

We formalize the concept of sheaves of sets on a model site by considering variables thereof, or motifs, and we construct functorially defined derived algebraic stacks from them, thereby eliminating the necessity to choose derived…

Algebraic Geometry · Mathematics 2020-10-19 Renaud Gauthier

We introduce the category of b-analytic manifolds, a natural tool to define constructible sheaves and functions up to infinity. We study with some details the operations on these objects and also recall the Radon transform for constructible…

Algebraic Geometry · Mathematics 2023-02-21 Pierre Schapira

We provide an analytical argument for understanding the likely nature of parameter shifts between those coming from an analysis of a dataset and from a subset of that dataset, assuming differences are down to noise and any intrinsic…

Instrumentation and Methods for Astrophysics · Physics 2020-10-28 Steven Gratton , Anthony Challinor

Sum-product networks (SPNs) are flexible density estimators and have received significant attention due to their attractive inference properties. While parameter learning in SPNs is well developed, structure learning leaves something to be…

Machine Learning · Computer Science 2019-11-05 Martin Trapp , Robert Peharz , Hong Ge , Franz Pernkopf , Zoubin Ghahramani