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Remove Documents/beast-build/fractal_echo_hunt.py

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Scruff-AI
2026-03-31 18:07:20 +07:00
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#!/usr/bin/env python3
"""
Find the fractal echo - hydrogen series in coherence/asymmetry patterns
Look for self-similar ratios like we did with periodic table
"""
import csv
import math
PHI = 1.618033988749895
def load_sweep_data():
"""Load sweep data."""
data = []
with open('/mnt/d/Resonance_Engine/beast-build/sweep_results.csv', 'r') as f:
reader = csv.DictReader(f)
for row in reader:
if row['value'] == 'value':
continue
try:
data.append({
'parameter': row['parameter'],
'value': float(row['value']),
'coh_mean': float(row['coh_mean']),
'asym_mean': float(row['asym_mean']),
'vort_mean': float(row['vort_mean'])
})
except:
continue
return data
def find_fractal_echo(values, name):
"""Look for self-similar ratios in a list of values."""
print(f"\n=== {name} FRACTAL ECHO ANALYSIS ===")
# Sort and get unique values
unique_vals = sorted(set(values))
print(f" {len(unique_vals)} unique values")
# Check all pairs for harmonic ratios
harmonic_ratios = []
for i, v1 in enumerate(unique_vals):
for v2 in unique_vals[i+1:]:
if v1 == 0:
continue
ratio = v2 / v1
# Check for hydrogen series ratios
hydrogen_targets = {
'Lyman-\u03b1 (2\u21921)': 0.75,
'Lyman-\u03b2 (3\u21921)': 0.888889,
'Balmer-\u03b1 (3\u21922)': 0.138889,
'Balmer-\u03b2 (4\u21922)': 0.1875,
'Paschen-\u03b1 (4\u21923)': 0.048611,
}
for h_name, target in hydrogen_targets.items():
if abs(ratio - target) < 0.01:
harmonic_ratios.append((v1, v2, ratio, h_name, target))
# Check phi-harmonic
phi_targets = [PHI, PHI**2, 1/PHI, 2*PHI, 3*PHI]
for target in phi_targets:
if abs(ratio - target) < 0.01:
harmonic_ratios.append((v1, v2, ratio, f'Phi-{target:.3f}', target))
# Sort by closeness to target
harmonic_ratios.sort(key=lambda x: abs(x[2] - x[4]))
print(f"\n Found {len(harmonic_ratios)} harmonic relationships:")
for v1, v2, ratio, name, target in harmonic_ratios[:20]:
diff = abs(ratio - target)
print(f" {v1:.6f} \u2192 {v2:.6f}: ratio={ratio:.6f} \u2248 {name} (diff: {diff:.6f})")
return harmonic_ratios
def analyze_coherence_levels(data):
"""Look for discrete coherence levels (energy levels)."""
print("\n=== COHERENCE ENERGY LEVELS ===")
# Get all coherence values
coh_vals = [d['coh_mean'] for d in data]
coh_vals.sort()
# Bin coherence values (looking for discrete levels)
bins = {}
bin_size = 0.0005 # Very fine binning
for c in coh_vals:
bin_key = round(c / bin_size) * bin_size
bins[bin_key] = bins.get(bin_key, 0) + 1
# Find populated bins (energy levels)
energy_levels = [k for k, v in bins.items() if v > 2]
energy_levels.sort()
print(f" Found {len(energy_levels)} coherence energy levels:")
for i, level in enumerate(energy_levels[:10]):
print(f" Level {i+1}: {level:.6f}")
# Check ratios between levels
if len(energy_levels) >= 3:
print("\n Energy level ratios:")
for i in range(len(energy_levels)-1):
for j in range(i+1, len(energy_levels)):
ratio = energy_levels[j] / energy_levels[i]
print(f" Level {i+1}\u2192{j+1}: {energy_levels[i]:.6f} \u2192 {energy_levels[j]:.6f} = {ratio:.6f}")
return energy_levels
def analyze_asymmetry_series(data):
"""Look for hydrogen series in asymmetry values."""
print("\n=== ASYMMETRY HYDROGEN SERIES ===")
# Get asymmetry values for omega sweep
omega_data = [d for d in data if d['parameter'] == 'omega']
asym_vals = [d['asym_mean'] for d in omega_data]
# Look for discrete asymmetry levels
unique_asym = sorted(set(round(a, 3) for a in asym_vals))
print(f" {len(unique_asym)} unique asymmetry levels")
print(" Levels:", ", ".join(f"{a:.3f}" for a in unique_asym[:10]))
# Check ratios
harmonic_pairs = []
for i, a1 in enumerate(unique_asym):
for a2 in unique_asym[i+1:]:
if a1 == 0:
continue
ratio = a2 / a1
# Hydrogen series check
targets = {
'Lyman-\u03b1': 0.75,
'Balmer-\u03b1': 0.138889,
'Paschen-\u03b1': 0.048611,
}
for name, target in targets.items():
if abs(ratio - target) < 0.05:
harmonic_pairs.append((a1, a2, ratio, name, target))
if harmonic_pairs:
print("\n Hydrogen-like ratios found in asymmetry:")
for a1, a2, ratio, name, target in harmonic_pairs:
print(f" {a1:.3f} \u2192 {a2:.3f}: {ratio:.6f} \u2248 {name}")
else:
print("\n No hydrogen series found in asymmetry ratios")
return harmonic_pairs
def main():
print("=" * 80)
print("FRACTAL ECHO HUNT - HYDROGEN SERIES IN LATTICE DATA")
print("=" * 80)
data = load_sweep_data()
print(f"Loaded {len(data)} data points")
# 1. Look for hydrogen series in coherence values
coh_vals = [d['coh_mean'] for d in data]
find_fractal_echo(coh_vals, "COHERENCE")
# 2. Look for discrete energy levels
energy_levels = analyze_coherence_levels(data)
# 3. Look for hydrogen series in asymmetry
harmonic_pairs = analyze_asymmetry_series(data)
# 4. Check vorticity for patterns
vort_vals = [d['vort_mean'] for d in data]
find_fractal_echo(vort_vals, "VORTICITY")
print("\n" + "=" * 80)
print("CONCLUSION")
print("=" * 80)
if harmonic_pairs:
print("\n\u2705 HYDROGEN SERIES FOUND IN ASYMMETRY")
print(" The lattice shows hydrogen-like energy quantization")
elif energy_levels:
print("\n\u26a0\ufe0f DISCRETE ENERGY LEVELS FOUND")
print(" The lattice quantizes coherence, but not in hydrogen pattern")
else:
print("\n\u274c NO CLEAR FRACTAL ECHO FOUND")
print(" The hydrogen series may be encoded differently")
print(" Try looking at: velocity ratios, vorticity harmonics, or combined metrics")
if __name__ == '__main__':
main()