Claude-skill-registry gay-monte-carlo

Gay Monte Carlo Measurements

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/gay-monte-carlo" ~/.claude/skills/majiayu000-claude-skill-registry-gay-monte-carlo && rm -rf "$T"
manifest: skills/data/gay-monte-carlo/SKILL.md
source content

Gay Monte Carlo Measurements


name: gay-monte-carlo description: Monte Carlo uncertainty propagation with Gay.jl deterministic coloring and Enzyme.jl autodiff for gamut-aware probability distributions. trit: 1 color: "#77DEB1"

Overview

GayMonteCarloMeasurements.jl extends MonteCarloMeasurements.jl with Gay.jl chromatic identity for deterministic color-coded uncertainty propagation.

Core Concepts

Particles as Colored Distributions

using MonteCarloMeasurements
using Gay

# Construct uncertain parameters with color tracking
gay_seed!(0xcd0a0fde6e0a8820)
a = π ± 0.1  # Particles{Float64,2000}

# Propagate through nonlinear functions
sin(a)  # → Particles with full distribution

Enzyme Gamut Learning

using Enzyme

# Learnable colorspace parameters
params = OkhslParameters()

function loss(params, seed, target_gamut=:srgb_boundary)
    color = forward_color(params, projection, seed)
    gamut_penalty = out_of_gamut_distance(color, target_gamut)
    bandwidth_reward = color_distinctiveness(color)
    return gamut_penalty - 0.1 * bandwidth_reward
end

∂params = Enzyme.gradient(Reverse, loss, params, seed)

Features

  • Nonlinear uncertainty propagation - Handles x², sign(x), integration
  • Correlated quantities - Multivariate particles
  • Distribution fitting -
    fit(Gamma, p)
    for any Particles
  • Visualization -
    plot(p)
    shows histogram,
    density(p)
    shows KDE
  • SPI verification - Fingerprint matching across network

GF(3) Integration

TritRoleOperation
+1PLUSGenerative sampling
0ERGODICDistribution transport
-1MINUSConstraint verification

Self-Avoiding Walk

next_color() → visited check
     │
     ├─ fresh → XOR into fingerprint
     │
     └─ collision → triadic fork

Repository

  • Source: bmorphism/GayMonteCarloMeasurements.jl
  • Seed:
    0xcd0a0fde6e0a8820
  • Index: 103/1055

Related Skills

  • gay-julia
    - Core Gay.jl integration
  • spi-parallel-verify
    - Fingerprint verification
  • fokker-planck-analyzer
    - Equilibrium analysis

SDF Interleaving

This skill connects to Software Design for Flexibility (Hanson & Sussman, 2021):

Primary Chapter: 4. Pattern Matching

Concepts: unification, match, segment variables, pattern

GF(3) Balanced Triad

gay-monte-carlo (○) + SDF.Ch4 (+) + [balancer] (−) = 0

Skill Trit: 0 (ERGODIC - coordination)

Secondary Chapters

  • Ch7: Propagators

Connection Pattern

Pattern matching extracts structure. This skill recognizes and transforms patterns.