Directionally Fine Families of Cones: Construction Principles, Approximation, and Separation
Abstract
We introduce the notion of a directionally fine family of cones, a local geometric property expressing the possibility of selecting arbitrarily narrow cones around every direction of a normed space. We show that this local property provides a common mechanism for finite separation and approximation. In particular, directionally compact sets can be separated from closed cones by finitely many members of the family, while locally compact cones admit finite outer approximations with quantitative Hausdorff control on their sets of directions and on bounded sections. These finite constructions lead naturally to max-type positively homogeneous separators and do not require convexity of the cones to be separated. We then study two complementary realizations of the framework. For the classical family of Bishop--Phelps cones, directional fineness is characterized by the requirement that every point of the unit sphere be a denting point of the unit ball, equivalently, by property~(G); in Banach spaces this amounts to rotundity together with the Kadec property. On the other hand, we introduce transversal coercivity as a general axial construction principle. It yields directionally fine families in arbitrary normed spaces, without geometric assumptions on the norm, and includes uniform axial deviation and norm-normalized axial cones as canonical models. Finally, the explicit structure of the former yields penalization and recovery results for optimization over locally compact cones, together with quantitative approximation and convergence estimates.
Related
- A Generalized Lai--Wei Construction and New Families of Area-Minimizing Hypercones
- Approximation Families and the Statistical Efficiency of Denoising Score Matching
- Construction of parametrized families of general pseudo-bimagic and bimagic squares
- The APN Property of Two Families of functions over F2n from the Switching Construction
- Approximation of Probability Geometries via Convex Families of Coordinate Charts
BibTeX
@misc{garciacastano2026directionally,
title = {{Directionally Fine Families of Cones: Construction Principles, Approximation, and Separation}},
author = {Fernando García-Castaño and Miguel Ángel Melguizo-Padial},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.15337},
eprint = {2609.15337},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.15337},
}
RIS
TY - UNPB
TI - Directionally Fine Families of Cones: Construction Principles, Approximation, and Separation
AU - Fernando García-Castaño
AU - Miguel Ángel Melguizo-Padial
PY - 2026
DA - 2026/09/14
PB - arXiv
DO - 10.48550/arxiv.2609.15337
UR - https://arxiv.org/abs/2609.15337
AB - We introduce the notion of a directionally fine family of cones, a local geometric property expressing the possibility of selecting arbitrarily narrow cones around every direction of a normed space. We show that this local property provides a common mechanism for finite separation and approximation. In particular, directionally compact sets can be separated from closed cones by finitely many members of the family, while locally compact cones admit finite outer approximations with quantitative Hausdorff control on their sets of directions and on bounded sections. These finite constructions lead naturally to max-type positively homogeneous separators and do not require convexity of the cones to be separated. We then study two complementary realizations of the framework. For the classical family of Bishop--Phelps cones, directional fineness is characterized by the requirement that every point of the unit sphere be a denting point of the unit ball, equivalently, by property~(G); in Banach spaces this amounts to rotundity together with the Kadec property. On the other hand, we introduce transversal coercivity as a general axial construction principle. It yields directionally fine families in arbitrary normed spaces, without geometric assumptions on the norm, and includes uniform axial deviation and norm-normalized axial cones as canonical models. Finally, the explicit structure of the former yields penalization and recovery results for optimization over locally compact cones, together with quantitative approximation and convergence estimates.
ER -