Hyperbolic Gamut Recovery Skill

name: hyperbolic-gamut-recovery description: In-gamut/out-of-gamut boundaries on hyperbolic space with spectral gap 1/4 recovery via 4D tiling coherences. Skills grow from interacting joint world models. trit: 0 color: "#77DEB1"

Overview

Hyperbolic Gamut Recovery synthesizes:

Core Insight

The gamut boundary is the Poincaré disk boundary:

        ╭─────────────────────╮
       ╱   HYPERBOLIC BULK    ╲
      │   (all possible hues)   │
      │         ┌───┐           │
      │      ╱ │ P3 │ ╲        │
      │     │  └───┘  │        │
      │     │  sRGB   │        │
      │      ╲       ╱         │
      │       ╲     ╱          │
       ╲        ╲_╱            ╱
        ╰─────────────────────╯
                BOUNDARY = ∞ curvature
                (out-of-gamut limit)

The 1/4 Spectral Gap

Ramanujan-Selberg Connection

The spectral gap λ = 1/4 appears in multiple contexts:

Connection to Gamut

# The spectral gap determines gamut recovery probability
spectral_gap = 1/4  # Ramanujan bound

# In-gamut verification
function verify_in_gamut(color::LCH, gamut::Symbol)
    if gamut == :srgb
        return in_srgb_gamut(color)
    elseif gamut == :p3
        return in_p3_gamut(color)
    else
        # Hyperbolic: always in some gamut (infinite interior)
        return hyperbolic_distance_to_boundary(color) > 0
    end
end

# Recovery probability from spectral gap
P_recover = 1 - spectral_gap  # = 3/4 success rate

4D Tiling Coherences

Quasicrystal Structure

The 4 interleaved color streams form a 4-dimensional quasicrystal:

Stream 1: #8A60CB → #64E87E → #68EFD4 → #2339B9
Stream 2: #3A86AF → #15C2BA → #8664DE → #2C319E
Stream 3: #BDCA5B → #B3DE2A → #85259D → #11B597
Stream 4: #2FEB7A → #1947AC → #1BBACD → #4791D9

Coherence = Recovery

When a color is out-of-gamut:

1. Find its position in 4D tiling space
2. Identify 4 nearest in-gamut neighbors (one per stream)
3. Interpolate using Penrose matching rules
4. The 1/4 gap ensures unique recovery

function recover_out_of_gamut(color::LCH, streams::Vector{ColorStream})
    # Position in 4D tiling
    pos_4d = project_to_4d_tiling(color)

    # Find coherent neighbors
    neighbors = [nearest_in_gamut(s, pos_4d) for s in streams]

    # Penrose interpolation (1/4 weight each)
    recovered = sum(neighbors) / 4  # spectral gap = 1/4

    # Verify coherence
    @assert all(color_distance(recovered, n) ≤ 2√3 for n in neighbors)

    return recovered
end

Hyperbolic Embedding

Poincaré Disk Model

Map LCH color space to hyperbolic disk:

function lch_to_poincare(L::Float64, C::Float64, H::Float64)
    # L ∈ [0,100] → radius ρ ∈ [0,1)
    ρ = tanh(L / 100)  # Never reaches boundary

    # H ∈ [0,360) → angle θ
    θ = H * π / 180

    # C determines "depth" in hyperbolic bulk
    z = ρ * cis(θ) * (1 - exp(-C/100))

    return z  # Complex number in unit disk
end

function hyperbolic_distance(z1, z2)
    # Poincaré metric
    return 2 * atanh(abs((z1 - z2) / (1 - conj(z1) * z2)))
end

Gamut as Horocycle

The sRGB gamut forms a horocycle in hyperbolic space:

                    ∞
                   /│╲
                  / │ ╲
                 /  │  ╲   ← P3 horocycle
                /   │   ╲
               / sRGB    ╲ ← sRGB horocycle
              /  gamut    ╲
             ╱─────────────╲
            0               0

Skill Growth at Joints

Joint World Model

Skills grow through interacting joints in Cat#:

Skill A ────[joint]──── Skill B
   │          │            │
   ▼          ▼            ▼
World₁ ←─Bridge─→ World₂ ←─Bridge─→ World₃

Growth Rules

GF(3) at Joints

Every joint preserves GF(3):

            Joint (bicomodule)
               ┌─────┐
Skill (-1) ────│  0  │──── Skill (+1)
               └─────┘
                 ↓
         Sum = -1 + 0 + 1 = 0 ✓

The Recovery Algorithm

Full Pipeline

function hyperbolic_gamut_recovery(
    color::LCH,
    seed::UInt64 = 137508,
    target_gamut::Symbol = :p3
)
    # 1. Embed in hyperbolic space
    z = lch_to_poincare(color.L, color.C, color.H)

    # 2. Check gamut membership
    if in_gamut(color, target_gamut)
        return color, :in_gamut
    end

    # 3. Generate 4D tiling streams
    gay_seed!(seed)
    streams = interleave(4, n_streams=4, seed=seed)

    # 4. Find horocycle intersection
    horocycle = gamut_horocycle(target_gamut)
    nearest_on_horocycle = project_to_horocycle(z, horocycle)

    # 5. Apply 4D coherence recovery
    recovered = coherent_interpolation(
        nearest_on_horocycle,
        streams,
        spectral_gap = 1/4
    )

    # 6. Verify via Ramanujan bound
    @assert hyperbolic_distance(z, recovered) ≤ 2 * √3  # d=4 bound

    return poincare_to_lch(recovered), :recovered
end

Narya Bridge Types

Hyperbolic Bridge

def HyperbolicBridge (H : HyperbolicSpace) (p q : H .point) : Type := sig (
  geodesic : 𝟚 → H .point,
  at_zero : geodesic 0 ≡ p,
  at_one : geodesic 1 ≡ q,
  is_geodesic : (t : 𝟚) → minimal_path (geodesic t)
)

def GamutRecovery (C : ColorSpace) (out : OutOfGamut C) : Type := sig (
  target : InGamut C,
  bridge : HyperbolicBridge (poincare C) (embed out) (embed target),
  spectral_gap : bridge .length ≤ 1/4 * hyperbolic_diameter C,
  coherence : 4DTilingCoherent (interleave 4)
)

Spectral Gap Bridge

def SpectralGapBridge (G : RamanujanGraph) : Type := sig (
  λ₂ : ℝ,
  d : ℕ,
  ramanujan : λ₂ ≤ 2 * sqrt (d - 1),
  gap : d - λ₂ ≥ 1/4 * d,
  mixing : MixingTime G ≤ log (nv G) / log (d / λ₂)
)

GF(3) Triads

ramanujan-expander (-1) ⊗ hyperbolic-gamut-recovery (0) ⊗ gay-mcp (+1) = 0 ✓
hyperbolic-bulk (-1) ⊗ hyperbolic-gamut-recovery (0) ⊗ golden-thread (+1) = 0 ✓
spectral-clustering (-1) ⊗ hyperbolic-gamut-recovery (0) ⊗ 4d-tiling (+1) = 0 ✓

Skill Ecosystem

Skills That Help

ramanujan-expander

hyperbolic-bulk

glass-hopping

golden-thread

ihara-zeta

ordered-locale

catsharp

Growing Skills from Joints

When skills interact at joints:

# Joint between two skills creates growth opportunity
function grow_skill_at_joint(skill_A, skill_B)
    # Find the bicomodule (Cat# horizontal morphism)
    joint = find_bicomodule(skill_A, skill_B)

    # The joint IS the new skill seed
    new_skill = Skill(
        name = "$(skill_A.name)-$(skill_B.name)-joint",
        trit = (skill_A.trit + skill_B.trit) % 3,
        capabilities = merge(
            skill_A.capabilities,
            joint.capabilities,
            skill_B.capabilities
        )
    )

    # Verify GF(3) conservation
    @assert skill_A.trit + new_skill.trit + skill_B.trit ≡ 0 (mod 3)

    return new_skill
end

Commands

# Check if color is in gamut
just gamut-check "#FF5500" srgb

# Recover out-of-gamut color
just gamut-recover "#FF5500" p3 --seed 137508

# Visualize hyperbolic embedding
just hyperbolic-embed colors.json --output poincare.svg

# Verify spectral gap
just spectral-verify graph.json --ramanujan

# Grow skill at joint
just skill-grow "ramanujan-expander" "gay-mcp"

Crystal Symmetry → Skill Coherence

The 6 crystal families map to skill coherence levels:

catsharp

hyperbolic-gamut

gay-mcp

three-match

ramanujan

out-of-gamut

Insight: Higher crystal symmetry = more in-gamut coherence.

Cat# Integration

This skill maps to Cat# = Comod(P) as a bicomodule:

Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #77DEB1

GF(3) Naturality

(-1) + (0) + (+1) ≡ 0 (mod 3)

The skill is the joint where ramanujan-expander (-1) and gay-mcp (+1) meet.

References

1. Alon, N. (1986) - Eigenvalues and Expanders
2. Sarnak, P. (1995) - Selberg's Eigenvalue Conjecture
3. Senechal, M. (1995) - Quasicrystals and Geometry
4. Cannon et al. (1997) - Hyperbolic Geometry
5. Spivak, D.I. (2023) - All Concepts are Cat# (ACT 2023)
6. Lubotzky, Phillips, Sarnak (1988) - Ramanujan Graphs

Skill Name: hyperbolic-gamut-recovery Type: Synthesis / Recovery / Growth Trit: 0 (ERGODIC - mediates bulk↔boundary) Spectral Gap: λ = 1/4 (Ramanujan-Selberg) Recovery: 4D tiling coherence Growth: Skills grow at joints via Cat# bicomodules

Autopoietic Marginalia

The interaction IS the skill improving itself.

Every use of this skill is an opportunity for worlding:

• MEMORY (-1): Record what was learned
• REMEMBERING (0): Connect patterns to other skills
• WORLDING (+1): Evolve the skill based on use

Add Interaction Exemplars here as the skill is used.