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.gitignore

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# === HUF Project Additions ===
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# Jupyter artifacts
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.ipynb_checkpoints/
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*.ipynb_checkpoints
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# Python bytecode
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__pycache__/
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*.pyc
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*.pyo
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# OS files
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.DS_Store
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Thumbs.db
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desktop.ini
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# LibreOffice lock files
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.~lock.*
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# Temporary files
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*.tmp
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*~
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# === Node.js (original template) ===
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# Logs
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logs
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*.log

.ipynb_checkpoints/Untitled-checkpoint.ipynb

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CITATION.cff

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authors:
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- family-names: Higgins
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given-names: Peter
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email: peterhiggins2016@gmail.com
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email: PeterHiggins@RogueWaveAudio.com
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date-released: "2026-03-11"
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version: "Phase 3"
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repository-code: "https://github.com/peterhiggins/HUF"

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README.md

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---
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## New Discovery: Entropy-Invariant Time Transformer (EITT)
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**April 2026.** Shannon entropy appears empirically near-invariant under geometric-mean temporal decimation of compositional time series in the energy datasets we tested.
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Measured: **0.18% variation** across a 341:1 compression ratio (daily → annual European electricity compositions, 8 carriers, 4089 trading days). Confirmed independently on 6 countries at **1.02% mean variation**, then driven to **0.029%** on a third independent test (EMBER monthly data, Copilot calibrator suite).
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For comparison, Aitchison variance drops 55% and total variation drops 99.7% across the same ladder. Shannon entropy changed very little in the tested ladders.
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In the tested datasets, the geometric mean — a central operation in CoDa — appeared to act as an entropy-stabilizing temporal filter. Whether this generalizes, and why, remains open.
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**Cross-domain confirmation (April 9, 2026).** EITT has now been tested on five domains beyond energy: hardware degradation (Backblaze drive stats, K=4, 24 months — 0.03%), a 120-stock price-level portfolio (K=9, 74 months — 0.08%; price-level weighted, not market-cap), cosmological observation (Planck 353 GHz half-mission temporal split — 0.3%), and commodities (gold/silver ratio, K=2, 338 years — fails at 6.7%, holds at 0.38% when reconstructed to K=4, validated out-of-sample). Bootstrap confidence intervals computed for all domains. The EITT inversion principle: when EITT fails on K parts, increasing K until it holds reveals the system's true dimensionality. **Honesty notes:** The Planck spatial EITT claim has been retracted (HEALPix NESTED pixel ordering does not preserve spatial locality). The financial composition is from a personal stock selection, not a standard index. At 2:1 compression, arithmetic-mean decimation also preserves entropy; the geometric mean's advantage appears at higher compression ratios. See code/analysis/honesty_tests_results_2026april9.txt for full adversarial test results.
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We are presenting this as an empirical finding with a mapped boundary, not as a theorem.
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**Exploratory: d(CoDa)/dt.** Alongside EITT, we are exploring a temporal derivative chain for compositions: perturbation velocity (scalar speed on the simplex), ILR balance trajectory (structural path), and balance derivative dB/dt (directed rate of structural change along each partition). This is a promising extension, not a settled result. It has been implemented in the tools and produces interpretable outputs on the tested datasets, but it has not been independently validated or formally connected to EITT. We include it here as work in progress.
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| What to read | File | Time |
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|--------------|------|------|
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| The finding, the numbers, the mechanism | [`EITT_FINDING.md`](drafts/codawork-2026/EITT_FINDING.md) | 10 min |
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| Plain-language explanation of everything | [`EITT_COMPLETE_EXPLANATION.md`](drafts/codawork-2026/EITT_COMPLETE_EXPLANATION.md) | 15 min |
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| What this offers CoDa specifically | [`EITT_CODA_POSITION.md`](drafts/codawork-2026/EITT_CODA_POSITION.md) | 10 min |
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| How EITT relates to 10 entropy territories | [`EITT_ENTROPY_LANDSCAPE.md`](drafts/codawork-2026/EITT_ENTROPY_LANDSCAPE.md) | 20 min |
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| Adversarial testing (10 pass, 7 fail, boundary mapped) | [`EITT_Adversarial_001.json`](data/codawork-samples/S016/EITT_Adversarial_001.json) | 10 min |
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| Copilot's calibrator lab and boundary condition | [`data/eitt_lab/`](data/eitt_lab/) | 30 min |
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| The residual explained (Hessian footprint) | [`EITT_Residual_Analysis_001.json`](data/codawork-samples/S016/EITT_Residual_Analysis_001.json) | 15 min |
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**Posture:** We found this empirically. We can't prove it. Can you?
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---
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## What HUF claims
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- Composition can be monitored directly, rather than treated only as a statistical correction or secondary view.
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| Directory | Function | Description |
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|-----------|----------|-------------|
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| [`huf-gov/`](huf-gov/) | **Observation** | The open-loop instrument. Science, evidence, governance, tools. |
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| [`huf-cls/`](huf-cls/) | **Control** | The closed-loop actuator. Published for transparency, not for deployment. |
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| [`huf-cls/`](huf-cls/) | **Control** | The closed-loop actuator. Included for transparency. Not part of the Coimbra / CoDaWork ask. |
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| [`reference/`](reference/) | **Foundation** | 68 machine-readable JSON specifications, technical notes, pillar documents. |
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### Supporting material
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| [`context-books/`](context-books/) | Four audience-specific editions of the core theory (general, engineering, physics, sciences). |
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| [`math-books/`](math-books/) | Formal mathematical foundations. 42 numbered items with full proofs. |
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| [`process/`](process/) | How this was built — collective review traces, session ledgers, governance documents. |
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| [`drafts/`](drafts/) | Submission papers (pre-validation), the Human-AI Accord. Work in progress. |
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| [`drafts/`](drafts/) | Submission papers (pre-validation), the Human-AI Accord, EITT materials. Work in progress. |
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| [`data/`](data/) | Reproducible datasets: EMBER energy, CoDaWork samples, EITT lab (calibration, adversarial, residual). |
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| [`code/`](code/) | Analysis scripts (Backblaze, energy, HellTest stress tests), diagnostic tools. |
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| [`src/`](src/) | Document generation build system (JS builders + shared modules + Python validation). |
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| [`notebooks/`](notebooks/) | Onboarding Jupyter series (5 interactive tutorials). |
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| [`docs/`](docs/) | Generated canonical documents: explorations, governance, 7 academic paper drafts, reference. |
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### Governance documents
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### CoDaWork 2026 Conference Materials
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Abstract accepted by Prof. Juan Jose Egozcue, Chair of the Scientific Committee. Conference: June 1-6, 2026, Coimbra, Portugal. See [`drafts/codawork-2026/`](drafts/codawork-2026/) for the full preparation suite (18 files) including formulas, vocabulary, researcher profiles, battle card, executive summary, core explanation, and the HUF-CoDa translator.
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Abstract accepted by Prof. Juan Jose Egozcue, Chair of the Scientific Committee. Conference: June 1-6, 2026, Coimbra, Portugal. See [`drafts/codawork-2026/`](drafts/codawork-2026/) for the full preparation suite including formulas, vocabulary, researcher profiles, battle card, executive summary, core explanation, the HUF-CoDa translator, and all EITT materials.
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**New in April 2026 — EITT:** The Entropy-Invariant Time Transformer discovery. Shannon entropy near-invariant under geometric-mean temporal decimation. Full finding, adversarial testing, residual analysis, calibration lab, boundary conditions, and an entropy landscape mapping EITT against 10 existing entropy territories. See [`EITT_FINDING.md`](drafts/codawork-2026/EITT_FINDING.md) and [`data/eitt_lab/`](data/eitt_lab/).
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**New entry point for CoDa community:** [`START_HERE.md`](START_HERE.md) — includes a "For CoDa / Compositional Data Analysts" section with direct links to all relevant materials.
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**Entry point for CoDa community:** [`START_HERE.md`](START_HERE.md) — includes a "For CoDa / Compositional Data Analysts" section with direct links to all relevant materials including EITT.
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REPO_MAP.md

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# HUF Repository Map
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*Updated: 2026-04-09 (S016 — EITT discovery, repo reorganization)*
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## Folder Structure
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```
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HUF/
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├── docs/ # Canonical documents (latest versions only)
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│ ├── index.md # Reading order and document status
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│ ├── pillars/ # The four core HUF papers
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│ │ ├── HUF_Sufficiency_Frontier_v3.6.docx
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│ │ ├── HUF_Fourth_Category_v2.6.docx
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│ │ ├── HUF_Triad_Synthesis_v1.6.docx
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│ │ └── HUF_Collective_Trace_v5.10.docx
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│ ├── governance/ # Review tracking and category classification
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│ │ ├── review_catalog.md
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│ │ ├── HUF_Category_Class_Structure_Tree_v1.4.docx
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│ │ └── HUF_Collective_Review_March2026.docx
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│ ├── explorations/ # Case studies, proofs, formal explorations
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│ ├── reviews/ # Individual AI system review documents
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│ └── appendices/ # Code appendix, methodology appendix
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├── src/ # Source code
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├── README.md # What HUF claims, EITT discovery, how to test it
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├── START_HERE.md # Tiered entry paths (60s, 5m, 30m) + CoDa welcome
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├── CITATION.cff # Academic citation metadata
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├── CONTRIBUTING.md # 5-AI collective development model
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├── VERSION_MANIFEST.json # Machine-readable version tracking
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├── package.json # Node.js dependency (docx-js) for build system
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├── huf-gov/ # The open-loop instrument
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│ ├── science/ # MONITOR-001 taxonomy, papers
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│ ├── evidence/case-studies/ # Energy, GDP, Backblaze, Ramsar, Planck, Toronto
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│ ├── governance/ # LOOP-001, KILL-001, SAFE-001, HANDOFF-001
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│ └── tools/spectrum-analyzer/ # v3 HTML analyzer + JSX source
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├── huf-cls/ # The closed-loop actuator (published for transparency)
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│ ├── architecture/ # CL-01 through CL-05
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│ ├── formulas/ # Sigmoid actuator, K_eff, amplifier
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│ └── calibration/ # CL-05 sensitivity analysis
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├── reference/ # Foundation
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│ ├── machine-readable/ # 68+ JSON specifications
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│ ├── pillars/ # Theory, methodology, architecture (.docx)
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│ ├── technical-notes/ # PLL, calibration, architecture, interaction studies
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│ └── wiki/ # Quick-reference articles
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├── data/ # Reproducible datasets
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│ ├── manifests/ # Data, benchmark, and release manifests
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│ ├── checksums/ # SHA256 document integrity hashes
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│ ├── codawork-samples/S016/ # EITT adversarial, midrange confirmation, residual
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│ └── eitt_lab/ # ★ EITT calibration lab
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│ ├── copilot_outputs/ # Calibrator suite, boundary condition, PCA variants
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│ └── claude_analysis/ # Residual analysis (Hessian footprint)
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├── drafts/ # Submission papers, conference materials, work in progress
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│ ├── codawork-2026/ # CoDaWork 2026 full preparation suite
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│ │ ├── EITT_FINDING.md # ★ The EITT discovery
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│ │ ├── EITT_CODA_POSITION.md # ★ What EITT offers CoDa
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│ │ ├── EITT_ENTROPY_LANDSCAPE.md # ★ EITT vs 10 entropy territories
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│ │ ├── EITT_COMPLETE_EXPLANATION.md # ★ Plain-language walkthrough
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│ │ ├── DANCE_CARD.md # Conference strategy + 8 union territories
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│ │ ├── THE_CORE.md # Coherence chain for CoDa community
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│ │ ├── FORMULA_REFERENCE.md # HUF↔CoDa formula reference
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│ │ ├── BATTLE_CARD.md # 10 hardest questions
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│ │ └── ... # Abstract, translator, explorer, ternary, etc.
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│ ├── accord/ # Human-AI Accord
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│ └── papers/ # Academic submissions
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├── docs/ # Generated canonical documents
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│ ├── explorations/ # Case studies (Backblaze, energy, CDN, Planck, TTC)
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│ ├── governance/ # Review catalog, governance explainer, provenance
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│ ├── papers/ # 7 academic submissions (CBD, CoDa, GEOBON, IEEE, etc.)
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│ ├── reference/ # Handbooks, math foundations, Ramsar package
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│ ├── appendices/ # Code appendix, methodology appendix
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│ └── wiki/ # Quick-reference markdown articles
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├── src/ # Document build system
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│ ├── builders/ # JavaScript docx-js builder scripts
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│ │ ├── pillars/ # Pillar document builders
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│ │ ├── volumes/ # Volume builders (Triad Synthesis)
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│ │ ├── governance/ # Trace and tree builders
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│ └── validation/ # Document validation scripts
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├── code/ # Executable code and experiments
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│ └── helltest/ # MC-4 detection stress test
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│ ├── scripts/ # Python scripts
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│ ├── notebooks/ # Jupyter notebooks
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│ └── results/ # Generated figures and reports
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│ └── validation/ # validate.py (docx integrity checker)
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├── code/ # Executable analysis tools
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│ ├── analysis/ # Backblaze, energy analysis scripts
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│ ├── helltest/ # MC-4 detection stress test (scripts, notebooks, results)
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│ └── tools/ # JSX diagnostic utilities
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│ └── onboarding/ # HUF onboarding notebook series (00-04)
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├── data/ # Manifests and integrity data
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│ ├── manifests/ # Data, benchmark, and release manifests
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│ └── checksums/ # SHA256 document integrity hashes
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├── archive/ # Non-canonical historical artifacts
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│ └── onboarding/ # HUF onboarding series (00-04)
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├── context-books/ # 4 audience editions (general, engineering, physics, sciences)
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├── math-books/ # Formal proofs (42 numbered items)
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├── process/ # Development record
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│ ├── collective-reports/ # AI collective reviews and master packages
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│ ├── governance-docs/ # Voting register, decision log, deployment strategy
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│ ├── review-traces/ # Version-traced review documents (v1.0-v5.10)
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│ └── session-ledgers/ # Per-session JSON records
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├── archive/ # Preserved history (nothing deleted, just organized)
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│ ├── HUFv4/ # Pre-Phase 3 working directory (version histories)
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│ ├── concepts/ # Experimental research (Kardashev, unity-vcore)
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│ ├── legacy-builders/ # Superseded builder scripts
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│ ├── legacy-generated-docs/ # Superseded .docx outputs
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│ ├── legacy-traces/ # Early review traces
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│ ├── papers-v1/ # First-draft academic papers
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│ ├── legacy-generated-docs/ # Superseded .docx (prefer git history)
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│ └── legacy-builders/ # Superseded builder scripts
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│ ├── ramsar-pre-standardized/ # Early Ramsar materials
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│ ├── superseded/ # Explicitly superseded items
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│ └── tools-pre-coda/ # Pre-CoDa analyzer versions
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└── .github/workflows/ # CI: validate and build
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```
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★ = New in S016 (April 2026) — EITT discovery materials
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## Document Status Legend
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| Status | Meaning |
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| **Canonical** | Current latest version, lives in `docs/` |
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| **Superseded** | Replaced by a newer version; preserved in git history |
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| **Archival** | Historical artifact; lives in `archive/` if needed |
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| **Experimental** | Work in progress; lives in `code/` or working branch |
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| **Active Draft** | Work in progress, lives in `drafts/` |
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| **Superseded** | Replaced by newer version; preserved in git history or `archive/` |
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| **Archival** | Historical artifact; lives in `archive/` with provenance note |
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| **Experimental** | Exploratory work; lives in `code/` or `archive/concepts/` |
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## Release Policy
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Only canonical documents live on `main`. Superseded versions are accessible through git tags, commit history, or GitHub Releases (binary attachments). The `VERSION_MANIFEST.json` tracks what is current.
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## For CoDa Researchers
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If you're arriving from CoDaWork 2026 or the compositional data analysis community, start with [`START_HERE.md`](START_HERE.md) — the "For CoDa" section points directly to the EITT finding and all supporting materials. The short version: we found that Shannon entropy is near-invariant under geometric-mean temporal decimation, and we think the CoDa community is best positioned to prove (or disprove) it.

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