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We introduce a weak asymptotic version of nonlinear contraction, termed \emph{asymptotic pointwise contraction}. For a mapping on a metric space, this notion requires the existence of a sequence of functions that dominate the distances…

Functional Analysis · Mathematics 2026-04-15 Jie Shi

In this paper, we present some fixed point theorems for operator systems in the line of Krasnosel'skii's theorem in cones. The cone-compression and cone-expansion type conditions are imposed in a component-wise manner. Unlike related…

Functional Analysis · Mathematics 2026-02-27 Laura M. Fernández-Pardo , Jorge Rodríguez-López

We develop a novel numerical bootstrap for unitary, crossing-symmetric conformal field theories, focusing on moment observables defined as weighted averages over conformal data. Providing a global and coarse-grained probe of the operator…

High Energy Physics - Theory · Physics 2026-03-20 Li-Yuan Chiang , David Poland , Gordon Rogelberg

Two-point correlation functions of spin operators in the minimal models ${{\cal M}}_{p,p'}$ perturbed by the field $\Phi_{13}$ are studied in the framework of conformal perturbation theory. The first-order corrections for the structure…

High Energy Physics - Theory · Physics 2015-06-26 A. A. Belavin , V. A. Belavin , A. V. Litvinov , Y. P. Pugai , Al. B. Zamolodchikov

The N = 2, 4 superconformal symmetry constraints in d = 4 for four point functions of chiral primary 1/2-BPS operators are derived. The operators are described by symmetric traceless tensors of the internal R-symmetry group. A substantial…

High Energy Physics - Theory · Physics 2017-06-06 Michael Nirschl

We investigate the addition of constraints on the function image and its derivatives for the incorporation of prior knowledge in symbolic regression. The approach is called shape-constrained symbolic regression and allows us to enforce e.g.…

Neural and Evolutionary Computing · Computer Science 2021-06-01 Gabriel Kronberger , Fabricio Olivetti de França , Bogdan Burlacu , Christian Haider , Michael Kommenda

In [B1, Theorem 2.36] we proved the equivalence of six conditions on a continuous function f on an interval. These conditions define a subset of the set of operator convex functions, whose elements are called strongly operator convex. Two…

Functional Analysis · Mathematics 2018-02-21 Lawrence G. Brown

Averaged operators have played an important role in fixed point theory in Hilbert spaces. They emerged as a necessity to obtain solutions to fixed point problems where the underlying operator is not contractive and thus renders Banach fixed…

Functional Analysis · Mathematics 2025-03-11 Arian Berdellima

Controlling the shape of deformable linear objects using robots and constraints provided by environmental fixtures has diverse industrial applications. In order to establish robust contacts with these fixtures, accurate estimation of the…

Robotics · Computer Science 2024-01-31 Kejia Chen , Zhenshan Bing , Yansong Wu , Fan Wu , Liding Zhang , Sami Haddadin , Alois Knoll

We classify and compute, by means of the six-dimensional embedding formalism in twistor space, all possible three-point functions in four dimensional conformal field theories involving bosonic or fermionic operators in irreducible…

High Energy Physics - Theory · Physics 2016-01-26 Emtinan Elkhidir , Denis Karateev , Marco Serone

Supervised operator learning centers on the use of training data, in the form of input-output pairs, to estimate maps between infinite-dimensional spaces. It is emerging as a powerful tool to complement traditional scientific computing,…

Machine Learning · Computer Science 2024-08-14 Nicholas H. Nelsen , Andrew M. Stuart

We study the problem of regression with interval targets, where only upper and lower bounds on target values are available in the form of intervals. This problem arises when the exact target label is expensive or impossible to obtain, due…

Machine Learning · Computer Science 2025-10-27 Rattana Pukdee , Ziqi Ke , Chirag Gupta

Some concepts, such as non-compactness measure and condensing operators, defined on metric spaces are extended to uniform spaces. Such extensions allow us to locate, in the context of uniform spaces, some classical results existing in…

General Topology · Mathematics 2015-11-25 Raúl Fierro

Recently, two of the authors obtained estimates for the adjoint restriction operator to finite type curves with respect to general measures. Strikingly, it turns out that some of such estimates are sharp, especially when the measures are…

Classical Analysis and ODEs · Mathematics 2019-11-04 Seheon Ham , Hyerim Ko , Sanghyuk Lee

A momentum-space approach to conformal field theory offers a new perspective on cosmological correlators and better reveals the underlying connections to scattering amplitudes. This thesis explores the interplay between integral…

High Energy Physics - Theory · Physics 2024-09-10 Francesca Caloro

In this paper we study the right differentiability of a parametric infimum function over a parametric set defined by equality constraints. We present a new theorem with sufficient conditions for the right differentiability with respect to…

Optimization and Control · Mathematics 2023-06-22 Kevin Sturm

Optimization in engineering requires appropriate models. In this article, a regression method for enhancing the predictive power of a model by exploiting expert knowledge in the form of shape constraints, or more specifically, monotonicity…

$T\bar{T}$-deformed CFTs are known to possess nonlocal conformal symmetries that do not act tractably on the undeformed local operators. In this paper, we explicitly construct two distinct classes of operators: (i) dressed operators, which…

High Energy Physics - Theory · Physics 2025-07-15 Liangyu Chen , Zhengyuan Du , Kangning Liu , Wei Song

A general method for estimating the approximation numbers of composition operators on $\Ht$, using finite-dimensional model subspaces, is studied and applied in the case when the symbol of the operator maps the unit disc to a domain whose…

Functional Analysis · Mathematics 2015-02-23 Hervé Queffélec , Kristian Seip

Regression splines are smooth, flexible, and parsimonious nonparametric function estimators. They are known to be sensitive to knot number and placement, but if assumptions such as monotonicity or convexity may be imposed on the regression…

Applications · Statistics 2008-11-12 Mary C. Meyer