smithery/plurigrid

initial-value-problem

Existence and uniqueness of solutions to ODEs with initial conditions

Installation

$ npx skills add smithery/plurigrid --skill initial-value-problem

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,167 B
  • docs SUMMARY.md 98 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Initial Value Problem

Trit: -1 (MINUS) Domain: Dynamical Systems Theory Principle: Existence and uniqueness of solutions to ODEs with initial conditions

Overview

Initial Value Problem is a fundamental concept in dynamical systems theory, providing tools for understanding the qualitative behavior of differential equations and flows on manifolds.

Mathematical Definition

INITIAL_VALUE_PROBLEM: Phase space × Time → Phase space

Key Properties

  1. Local behavior: Analysis near equilibria and invariant sets
  2. Global structure: Long-term dynamics and limit sets
  3. Bifurcations: Parameter-dependent qualitative changes
  4. Stability: Robustness under perturbation

Integration with GF(3)

This skill participates in triadic composition:

  • Trit -1 (MINUS): Sinks/absorbers
  • Conservation: Σ trits ≡ 0 (mod 3) across skill triplets

AlgebraicDynamics.jl Connection

using AlgebraicDynamics

# Initial Value Problem 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: initial-value-problem Type: Dynamical Systems / Initial Value Problem Trit: -1 (MINUS) 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:

  1. Prime Path: No state revisited in skill invocation chain
  2. Möbius Filter: Composite paths (backtracking) cancel via μ-inversion
  3. GF(3) Conservation: Trit sum ≡ 0 (mod 3) across skill triplets
  4. 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)