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Round 1 v0.1 2026-07-26

Support-Skew Linear Programming, Finite-Curve Pressure, and the First Adversarial Search

Implements the curve-to-convex-container containment problem as two linear programs: fixed rotation solving for the minimal container scale, and fixed scale solving for the minimal positive skew. Tests 35 candidate curves using 192 support directions and 60–120 initial rotation phases, completing 5 generations of lightweight adversarial curve search.

Exploratory computation; not a formal proof; not a universal covering certificate — Stage status as self-declared by the in-package documents, reproduced verbatim. Program scale: 192 support directions, 60–120 initial rotation phases, and linear programming at fixed phase to solve for the optimal translation or minimal scale.

Connections · Connections

Relationship to other packages, stated as far as possible in the document's own words, not my interpretation.

Round progress1 / 15
“At fixed phase, the translation term occupies only the Fourier expansion's first-order sine and cosine modes… what actually stresses the container is the higher-order peaks that persist after translation — corresponding to the corners and long edges of the curve's convex hull and its asymmetric structure, mismatches between the container's normal sectors and the curve's normal sectors, and jumps in the optimal contact set. This carries more research information than simply recording whether the curve ‘fits.’” — excerpted from Section 4, “Preliminary Structural Findings,” of this package's main document.

Core Content of Round 1

Full formulation of both linear programs; three benchmark containers (a disk, a 30° sector, and the certified Wetzel triangle); critical-scale ranking of the 35 candidate curves; results from 5 generations of adversarial search; preliminary structural findings; and 5 candidate directions for the next round.

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Files · Files

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