Experiment Evidence — hotSpring

hotSpring has accumulated 181 experiments across 12 physics categories, reproducing 22 published papers and building a science ladder from quenched QCD through sovereign GPU compute to NUCLEUS composition validation.

Data sources: experiment_catalog.json, security_convergence.json

Reproduce: See EXPERIMENT_INDEX.md for per-experiment reproduction commands.

For other springs: Replace the physics categories with your domain categories. The experiment catalog structure and science ladder pattern are reusable.

import json
from pathlib import Path
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np

RESULTS = Path('..') / 'experiments' / 'results'

def load(name):
    with open(RESULTS / name) as f:
        return json.load(f)

catalog = load('experiment_catalog.json')
security = load('security_convergence.json')

print(f"Total experiments: {catalog['total_experiments']}")
print(f"Categories: {len(catalog['categories'])}")
print(f"Papers reproduced: {catalog['papers_reproduced']}")
print(f"Total science cost: {catalog['total_science_cost']}")
print(f"Science ladder: {len(catalog['science_ladder'])} milestones")

Experiment Categories

181 experiments organized by physics domain — from molecular dynamics (Phase A) through lattice QCD production (Phase H) to sovereign GPU and multi-GPU hardware validation (Phase K).

C_PASS = '#2ecc71'
C_INFO = '#3498db'
C_GPU  = '#9b59b6'

cats = catalog['categories']
cat_names = [k.replace('_', ' ').title() for k in cats]
cat_counts = [cats[k]['count'] for k in cats]

palette = ['#2ecc71', '#3498db', '#9b59b6', '#1abc9c', '#f39c12',
           '#e67e22', '#e74c3c', '#16a085', '#2c3e50', '#8e44ad',
           '#d35400', '#27ae60']

fig, axes = plt.subplots(1, 2, figsize=(14, 6))

# Bar chart by category
y = np.arange(len(cat_names))
axes[0].barh(y, cat_counts, color=palette[:len(cat_names)])
axes[0].set_yticks(y)
axes[0].set_yticklabels(cat_names, fontsize=8)
axes[0].set_xlabel('Experiments')
axes[0].set_title(f'{catalog["total_experiments"]} Experiments Across {len(cats)} Categories')
axes[0].invert_yaxis()

# Timeline
timeline = catalog['timeline']
phases = list(timeline.keys())
added = [timeline[p]['experiments_added'] for p in phases]
phase_labels = [timeline[p]['period'] for p in phases]
axes[1].bar(phase_labels, added, color=[C_PASS, C_INFO, C_GPU, '#f39c12'])
axes[1].set_ylabel('Experiments Added')
axes[1].set_title('Experiment Growth Timeline')
for i, v in enumerate(added):
    axes[1].text(i, v + 1, str(v), ha='center', fontweight='bold')

fig.suptitle(f'hotSpring: {catalog["total_experiments"]} Experiments, {catalog["papers_reproduced"]} Papers Reproduced', fontsize=13, fontweight='bold')
plt.tight_layout()
plt.savefig('/tmp/hotspring_03_experiments.png', dpi=150, bbox_inches='tight')
plt.show()

Science Ladder

The science ladder traces hotSpring’s evolution from basic quenched QCD through increasingly sophisticated physics to the current state: NUCLEUS composition validation with sovereign GPU compute on multiple hardware generations.

ladder = catalog['science_ladder']

fig, ax = plt.subplots(figsize=(10, 8))

y = np.arange(len(ladder))
colors = []
for i, step in enumerate(ladder):
    if 'QCD' in step or 'N_f' in step or 'Chuna' in step:
        colors.append('#3498db')
    elif 'GPU' in step or 'Sovereign' in step or 'Firmware' in step or 'Dispatch' in step:
        colors.append('#9b59b6')
    elif 'NUCLEUS' in step or 'Composition' in step or 'guideStone' in step or 'Primal' in step or 'Phase' in step:
        colors.append('#2ecc71')
    elif 'K80' in step or 'Ember' in step or 'Debt' in step:
        colors.append('#f39c12')
    else:
        colors.append('#1abc9c')

ax.barh(y, [1]*len(ladder), color=colors, height=0.7)
for i, step in enumerate(ladder):
    ax.text(0.05, i, step, va='center', fontsize=8, fontweight='bold', color='white')

ax.set_yticks([])
ax.set_xticks([])
ax.set_title(f'Science Ladder: {len(ladder)} Milestones')
ax.invert_yaxis()

from matplotlib.patches import Patch
legend_elements = [
    Patch(facecolor='#3498db', label='Lattice QCD'),
    Patch(facecolor='#9b59b6', label='Sovereign GPU'),
    Patch(facecolor='#2ecc71', label='NUCLEUS Composition'),
    Patch(facecolor='#f39c12', label='Hardware Validation'),
    Patch(facecolor='#1abc9c', label='Physics Infrastructure')
]
ax.legend(handles=legend_elements, loc='lower right', fontsize=8)

plt.tight_layout()
plt.savefig('/tmp/hotspring_03_ladder.png', dpi=150, bbox_inches='tight')
plt.show()

Evolution Timeline

Test count growth tracks the science ladder — each milestone adds coverage.

timeline = security['evolution_timeline']
dates = [t['date'] for t in timeline]
test_counts = [t['tests'] for t in timeline]
events = [t['event'].split(' — ')[1] if ' — ' in t['event'] else t['event'] for t in timeline]

fig, ax = plt.subplots(figsize=(12, 5))
ax.plot(dates, test_counts, 'o-', color=C_PASS, linewidth=2, markersize=8)
for i, (d, t, e) in enumerate(zip(dates, test_counts, events)):
    ax.annotate(f'{t}\n{e}', (d, t), textcoords='offset points',
                xytext=(0, 15), ha='center', fontsize=7, rotation=20)

ax.set_xlabel('Date')
ax.set_ylabel('Library Tests')
ax.set_title('Test Count Evolution: 120 → 993')
plt.xticks(rotation=30, ha='right')
plt.tight_layout()
plt.savefig('/tmp/hotspring_03_evolution.png', dpi=150, bbox_inches='tight')
plt.show()

Validation Summary

Provenance: All data from experiments/results/experiment_catalog.json.
Full index: EXPERIMENT_INDEX.md in repo root.
Source: hotSpring on GitHub · primals.eco