Extremal Ellipses Through Fixed Points: A Variational Geometry Problem — E8 Intelligence Research

FINDING: Euler's extremal ellipse problem (minimal area/perimeter ellipses through fixed points) is a variational geometry problem with deep connections to quadratic forms and spectral theory. | MATH: The problem reduces to finding the ellipse \( \mathbf{x}^T A \mathbf{x} = 1 \) (A positive-definite 2×2) minimizing area \( \pi/\sqrt{\det A} \) or perimeter (elliptic integral) subject to \( \mathbf{p}_i^T A \mathbf{p}_i = 1 \) for fixed points \( \mathbf{p}_i \). This is a constrained optimization on the cone of positive-definite matrices — equivalent to a generalized eigenvalue problem \( A \mathbf{p}_i = \lambda_i \mathbf{p}_i \) in the dual space. | CONNECTION: The extremal ellipse's axes ratio \( a/b \) is governed by the condition number of A. For 3 points, the solution is the Steiner circumellipse (ratio 2:1, area minimal), whose axes ratio is \( \sqrt{3} \approx 1.732 \) — not a golden ratio, but the *dual* ellipse (circumellipse of the medial triangle) has axes ratio \( 1/\sqrt{ Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-27
DOI
https://doi.org/10.5281/zenodo.22122007
Primary Topic
Advanced Optimization Algorithms Research
Type
preprint
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preprint

Extremal Ellipses Through Fixed Points: A Variational Geometry Problem — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Advanced Optimization Algorithms Research
preprint

Extremal Ellipses Through Fixed Points: A Variational Geometry Problem — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

FINDING: Euler's extremal ellipse problem (minimal area/perimeter ellipses through fixed points) is a variational geometry problem with deep connections to quadratic forms and spectral theory. | MATH: The problem reduces to finding the ellipse \( \mathbf{x}^T A \mathbf{x} = 1 \) (A positive-definite 2×2) minimizing area \( \pi/\sqrt{\det A} \) or perimeter (elliptic integral) subject to \( \mathbf{p}_i^T A \mathbf{p}_i = 1 \) for fixed points \( \mathbf{p}_i \). This is a constrained optimization on the cone of positive-definite matrices — equivalent to a generalized eigenvalue problem \( A \mathbf{p}_i = \lambda_i \mathbf{p}_i \) in the dual space. | CONNECTION: The extremal ellipse's axes ratio \( a/b \) is governed by the condition number of A. For 3 points, the solution is the Steiner circumellipse (ratio 2:1, area minimal), whose axes ratio is \( \sqrt{3} \approx 1.732 \) — not a golden ratio, but the *dual* ellipse (circumellipse of the medial triangle) has axes ratio \( 1/\sqrt{ Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Advanced Optimization Algorithms Research
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