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We propose a new mapping tool for supervised and unsupervised analysis of multivariate binary data with multiple items, questions, or response variables. The mapping assumes an underlying proximity response function, where participants can…

Computation · Statistics 2025-01-23 Mark de Rooij , Dion Woestenburg , Frank Busing

Recent progress concerning regularization of supersymmetric theories is reviewed. Dimensional reduction is reformulated in a mathematically consistent way, and an elegant and general method is presented that allows to study the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Dominik Stöckinger

Given an autohomeomorphism on an ordered topological space or its subspace, we show that it is sometimes possible to introduce a new topology-compatible order on that space so that the same map is monotonic with respect to the new ordering.…

General Topology · Mathematics 2023-06-27 Raushan Buzyakova

We consider extensions of quasiconformal maps and the uniformization theorem to the setting of metric spaces $X$ homeomorphic to $\mathbb R^2$. Given a measure $\mu$ on such a space, we introduce $\mu$-quasiconformal maps $f:X \to \mathbb…

Complex Variables · Mathematics 2021-05-25 Kai Rajala , Martti Rasimus , Matthew Romney

This paper presents and explores a theory of \emph{multiholomorphic maps}. This group of ideas generalizes the theory of pseudoholomorphic curves in a direction suggested by consideration of the kinds of compatible geometric structures that…

Differential Geometry · Mathematics 2012-05-01 Aaron M. Smith

Capacity constrained optimal transport is a variant of optimal transport, which adds extra constraints on the set of feasible couplings in the original optimal transport problem to limit the mass transported between each pair of source and…

Optimization and Control · Mathematics 2025-02-13 Tianhao Wu , Qihao Cheng , Zihao Wang , Chaorui Zhang , Bo Bai , Zhongyi Huang , Hao Wu

The paper deals with a comprehensive theory of mappings, whose local behavior can be described by means of linear subspaces, contained in the graphs of two (primal and dual) generalized derivatives. This class of mappings includes the…

Optimization and Control · Mathematics 2021-12-08 Helmut Gfrerer , Jiri V. Outrata

For theories with multiple couplings we construct simple expressions for the four-dimensional (or, in general, integer-dimensional) renormalization constants assuming that all divergences are logarithmical. These expressions allow relating…

High Energy Physics - Theory · Physics 2025-12-17 Gleb Kovyrshin , Nikolai Meshcheriakov , Victoria Shatalova , Konstantin Stepanyantz

This investigation seeks to establish the practicality of numerical frame approximations. Specifically, it develops a new method to approximate the inverse frame operator and analyzes its convergence properties. It is established that…

Numerical Analysis · Mathematics 2012-03-30 Guohui Song , Anne Gelb

We discuss renormalizability of a recently established, massive gravity theory with particular higher derivative terms in three space-time dimensions. It is shown that this massive gravity is certainly renormalizable as well as unitary, so…

High Energy Physics - Theory · Physics 2009-05-29 Ichiro Oda

We extend monotone quasiconformal mappings from dimension n to n+1 while preserving both monotonicity and quasiconformality. The extension is given explicitly by an integral operator. In the case n=1 it yields a refinement of the…

Complex Variables · Mathematics 2011-02-08 Leonid V. Kovalev , Jani Onninen

We study of the effect of weak noise on critical one dimensional maps; that is, maps with a renormalization theory. We establish a one dimensional central limit theorem for weak noises and obtain Berry--Esseen estimates for the rate of this…

Dynamical Systems · Mathematics 2007-05-23 Oliver Diaz-Espinosa , Rafael de la Llave

We present a scheme for the analytic computation of renormalization functions on the lattice, using a symbolic manipulation computer language. Our first nontrivial application is a new three-loop result for the topological susceptibility.

High Energy Physics - Lattice · Physics 2009-10-22 B. Alles , M. Campostrini , A. Feo , H. Panagopoulos

A perturbative description of Large Scale Structure is a cornerstone of our understanding of the observed distribution of matter in the universe. Renormalization is an essential and defining step to make this description physical and…

High Energy Physics - Theory · Physics 2016-06-08 Ali Akbar Abolhasani , Mehrdad Mirbabayi , Enrico Pajer

The period doubling renormalization operator was introduced by M. Feigenbaum and by P. Coullet and C. Tresser in the nineteen-seventieth to study the asymptotic small scale geometry of the attractor of one-dimensional systems which are at…

Dynamical Systems · Mathematics 2007-10-04 V. V. M. S. Chandramouli , M. Martens , W. de Melo , C. P. Tresser

We develop a renormalization theory for analytic homeomorphisms of the circle with two cubic critical points. We prove a renormalization hyperbolicity theorem. As a basis for the proofs, we develop complex a priori bounds for multi-critical…

Dynamical Systems · Mathematics 2019-12-10 Michael Yampolsky

We develop the foundations of the theory of quasi-visual approximations of bounded metric spaces. Roughly speaking, these are sequences of covers of a given space for which the diameters of the sets in the covers shrink to zero and for…

Complex Variables · Mathematics 2026-01-22 Mario Bonk , Mikhail Hlushchanka , Daniel Meyer

In this paper, we discuss positive maps induced by (irreducibly) covariant linear operators for finite groups. The application of group theory methods allows deriving some new results of a different kind. In particular, a family of…

Quantum Physics · Physics 2020-09-07 Piotr Kopszak , Marek Mozrzymas , Michał Studziński

We employ techniques from optimal transport in order to prove decay of transfer operators associated to iterated functions systems and expanding maps, giving rise to a new proof without requiring a Doeblin-Fortet (or Lasota-Yorke)…

Dynamical Systems · Mathematics 2015-08-25 Benoit Kloeckner , Artur Lopes , Manuel Stadlbauer

Optimal transport maps define a one-to-one correspondence between probability distributions, and as such have grown popular for machine learning applications. However, these maps are generally defined on empirical observations and cannot be…

Statistics Theory · Mathematics 2021-02-18 Lucas de Lara , Alberto González-Sanz , Jean-Michel Loubes
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