HoloCell

T(16) = 136 as the eigenvalue of fundamental physics constants.

Installation

pip install holocell

Requires GEPEvolver (installed automatically).

Quick Start

from holocell import T, B, S, CRYSTAL, verify_all

# The seed
print(T(16))  # 136

# Verify all 5 constants
results = verify_all()
# {'mp/me': True, 'R∞': True, 'α⁻¹': True, 'μ/me': True, 'sin²θW': True}

# Access a specific crystal constant
proton = CRYSTAL["mp/me"]
print(f"Computed:  {proton.computed}")
print(f"Measured:  {proton.measured}")
print(f"Error:     {proton.error_percent:.2e}%")

The Discovery

Five fundamental physics constants emerge from a single seed: T(16) = 136.

Constant	Expression	Error
mp/me	T(136) × 3 × (9/2) + (11 - 1/T(16))/72	1.21×10⁻⁷%
R∞	B(T(11) × (√(T(16) + e) + 1/36 + 666)⁻¹)	1.02×10⁻⁵%
α⁻¹	T(16) + (((e/36 + T(16)) + π) / (T(16) - φ))	1.35×10⁻⁵%
μ/me	(16 + T(16) + T(16)/28 + 44) + B(S(T(16))/60)	1.40×10⁻⁵%
sin²θW	√((28 - (π + 36/T(16))⁻¹ - 9)⁻¹)	4.67×10⁻⁴%

Six Modes of Sight

HoloCell provides six evolutionary modes for discovering and validating architectural structure:

from holocell.modes import (
    evolve_constant,      # Mode 1: Fixed Focus
    evolve_coherent,      # Mode 2: Coherent Zoom
    evolve_seth,          # Mode 3: Seth Mode
    run_moon_pools,       # Mode 4: Moon Pools
    run_coherence_sweep,  # Mode 5: Coherence Test
    weave,                # Mode 6: Weave
)

Mode 1: Fixed Focus

Standard GEP evolution with fixed terminals.

result = evolve_constant("alpha", seed_value=136)

Mode 2: Coherent Zoom

Co-evolve the integer set itself across all constants simultaneously.

result = evolve_coherent(integer_set_size=6)
print(f"Discovered integers: {result.discovered_integers}")

Mode 3: Seth Mode

Dual set partition — discover which constants need the full archive vs filtered subset.

result = evolve_seth()
print(f"Archive: {result.archive}")
print(f"Transmitted: {result.transmitted}")

Mode 4: Moon Pools

Multi-pool eigenvalue triangulation — find crossing bands.

result = run_moon_pools(num_pools=4, max_runtime_seconds=180)

Mode 5: Coherence Test

N-node corruption sweep — measure fault tolerance threshold.

result = run_coherence_sweep(max_corruption=8)
print(f"Fault tolerance: {result.fault_tolerance_threshold} nodes")

Mode 6: Weave

Incremental corruption and restoration — reveal healing dynamics.

Instead of batch corruption (Mode 5), weave between states one node at a time:

BATCH (Mode 5):              WEAVE (Mode 6):

corrupt 7 → evolve 1000      corrupt 1 → evolve 50 → measure
           → measure         corrupt 1 → evolve 50 → measure
                             ...
corrupt 7 → evolve 1000      restore 1 → evolve 50 → measure
           → measure         restore 1 → evolve 50 → measure
                             ...

What this reveals:

Metric	Mode 5 (Batch)	Mode 6 (Weave)
Threshold	Yes	Yes
Healing dynamics	No	Per-step trajectory
Hysteresis	No	Does path matter?
Phase transitions	Coarse	Sharp or gradual?
Selection effects	No	Which nodes matter?

Three selection strategies:

Strategy	Corrupt Order	Restore Order
RANDOM	Any order	Any order
WORST_FIRST	Highest error first	Lowest error first
BEST_FIRST	Lowest error first	Highest error first

Usage:

from holocell import weave, compare_strategies, SelectionStrategy

# Single strategy
result = weave(
    max_corruption=6,
    strategy=SelectionStrategy.RANDOM,
    generations_per_step=100,
)
print(f"Hysteresis: {result.hysteresis_score:.1%}")
print(f"Recovery: {'✓' if result.recovery_complete else '✗'}")

# Compare all strategies
results = compare_strategies(max_corruption=6)
for strategy, result in results.items():
    print(f"{strategy.value}: hysteresis={result.hysteresis_score:.1%}")

Key insight: If the manifold is a true basin of attraction, the restore trajectory mirrors the degrade trajectory (hysteresis ≈ 0%). If there's memory of damage, hysteresis > 0%.

Self-Healing Networks

The optimal seed geometry is the octahedron: 6 nodes forming 3 bilateral pairs.

This minimal Platonic solid outperforms all tested alternatives including the buckyball (60 nodes) and vortex engine (144 nodes). The center must remain empty — adding a hub node degrades performance.

Seed	Frozen	Avg Rate	Steps to 90%
octahedron	6	0.0259	24.7
tetrahedron	4	0.0248	39.7
buckyball	60	0.0242	27.3
vortex_engine	144	0.0242	31.0

The HoloCell Geometry:

• Octahedron = outer shell (6 vertices, 3 bilateral pairs on Trinition axes)
• T(16) = 136 = eigenvalue at center (not a node — a frequency)
• 408 = T(16) × 3 = scale invariance marker

The eigenvalue isn't a physical node. It's what the structure resonates at. The octahedron is the antenna; T(16) is the frequency.

from holocell.networks import test_egyptian_candidates

results = test_egyptian_candidates()
for n, analysis in sorted(results.items()):
    print(f"N={n}: self-healing={analysis.is_self_healing}")

Operators

Three architectural operators from Egyptian cosmological mathematics:

from holocell import T, B, S

T(16)    # 136 — Triangular number: n(n+1)/2
B(T(16)) # 137 — Bilateral covenant: x + 1
S(9)     # 19.5 — Six-nine harmonic: x×6/9 + x×9/6

CLI

# Verify crystallized expressions
holocell verify

# Mode 1: Fixed Focus
holocell evolve alpha
holocell seed-test

# Mode 2: Coherent Zoom
holocell coherent

# Mode 3: Seth Mode
holocell seth

# Mode 4: Moon Pools
holocell moonpools

# Mode 5: Coherence Test
holocell sweep

# Mode 6: Weave
holocell weave                    # Random strategy
holocell weave --strategy worst   # Worst-first
holocell weave --strategy best    # Best-first
holocell weave --compare          # Compare all strategies

License

CC0 1.0 Universal — Public Domain

Citation

@software{brown2025holocell,
  title={HoloCell: T(16) = 136 as the Eigenvalue of Fundamental Physics Constants},
  author={Brown, Nicholas David},
  year={2025},
  doi={10.5281/zenodo.18183435}
}