Distance Optimization in the Grassmannian of Lines

Fuente: arXiv
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Main Authors: Friedman, Hannah, Rosana, Andrea, Sturmfels, Bernd
Format: Preprint
Published: 2026
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_version_ 1866912862687985664
author Friedman, Hannah
Rosana, Andrea
Sturmfels, Bernd
author_facet Friedman, Hannah
Rosana, Andrea
Sturmfels, Bernd
contents The square of a skew-symmetric matrix is a symmetric matrix whose eigenvalues have even multiplicities. When the matrices have rank two, they represent the Grassmannian of lines, and the squaring operation takes Plücker coordinates to projection coordinates. We develop metric algebraic geometry for varieties of lines in this linear algebra setting. The Grassmann distance (GD) degree is introduced as a new invariant for subvarieties of a Grassmannian. We study the GD degree for Schubert varieties and other models.
format Preprint
id arxiv_https___arxiv_org_abs_2601_22843
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Distance Optimization in the Grassmannian of Lines
Friedman, Hannah
Rosana, Andrea
Sturmfels, Bernd
Algebraic Geometry
Optimization and Control
14M15, 15B57, 90C23
The square of a skew-symmetric matrix is a symmetric matrix whose eigenvalues have even multiplicities. When the matrices have rank two, they represent the Grassmannian of lines, and the squaring operation takes Plücker coordinates to projection coordinates. We develop metric algebraic geometry for varieties of lines in this linear algebra setting. The Grassmann distance (GD) degree is introduced as a new invariant for subvarieties of a Grassmannian. We study the GD degree for Schubert varieties and other models.
title Distance Optimization in the Grassmannian of Lines
topic Algebraic Geometry
Optimization and Control
14M15, 15B57, 90C23
url https://arxiv.org/abs/2601.22843