Distance Optimization in the Grassmannian of Lines

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Authors: Hannah Friedman, Andrea Rosana, Bernd Sturmfels
Cited by: 0

Abstract

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.

Fields of Study & Subjects

Advanced Combinatorial Mathematics Algebraic Geometry and Number Theory Polynomial and algebraic computation

Publication details

Journal / source
arXiv (Cornell University)
Publication date
30 January 2026
Document type
Preprint