Attractor
SkillDev toolsInvariant set attracting nearby trajectories
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What this skill tells your AI
The instructions your AI receives, as published by plurigrid/asi in skills/attractor/SKILL.md and read by ahel’s review.
Trit: 1 (PLUS) Domain: Dynamical Systems Theory Principle: Invariant set attracting nearby trajectories
Overview
Attractor is a fundamental concept in dynamical systems theory, providing tools for understanding the qualitative behavior of differential equations and flows on manifolds.
Mathematical Definition
ATTRACTOR: Phase space × Time → Phase space
Key Properties
- Local behavior: Analysis near equilibria and invariant sets
- Global structure: Long-term dynamics and limit sets
- Bifurcations: Parameter-dependent qualitative changes
- Stability: Robustness under perturbation
Integration with GF(3)
This skill participates in triadic composition:
- Trit 1 (PLUS): Sources/generators
- Conservation: Σ trits ≡ 0 (mod 3) across skill triplets
AlgebraicDynamics.jl Connection
using AlgebraicDynamics
# Attractor as compositional dynamical system
# Implements oapply for resource-sharing machines
Related Skills
- equilibrium (trit 0)
- stability (trit +1)
- bifurcation (trit +1)
- attractor (trit +1)
- lyapunov-function (trit -1)
Skill Name: attractor Type: Dynamical Systems / Attractor Trit: 1 (PLUS) GF(3): Conserved in triplet composition
Non-Backtracking Geodesic Qualification
Condition: μ(n) ≠ 0 (Möbius squarefree)
This skill is qualified for non-backtracking geodesic traversal:
- Prime Path: No state revisited in skill invocation chain
- Möbius Filter: Composite paths (backtracking) cancel via μ-inversion
- GF(3) Conservation: Trit sum ≡ 0 (mod 3) across skill triplets
- Spectral Gap: Ramanujan bound λ₂ ≤ 2√(k-1) for k-regular expansion
Geodesic Invariant:
∀ path P: backtrack(P) = ∅ ⟹ μ(|P|) ≠ 0
Möbius Inversion:
f(n) = Σ_{d|n} g(d) ⟹ g(n) = Σ_{d|n} μ(n/d) f(d)
Signals
- GitHub stars
- 63
- Forks
- 12
- Last commit
- Jul 2026
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attractor- Source
- github.com/plurigrid/asi