/** * DocsView — Documentation with sidebar navigation and scroll-spy. */ interface Section { id: string; label: string; icon: string; children?: { id: string; label: string }[]; } const SECTIONS: Section[] = [ { id: 'overview', label: 'Overview', icon: '\u2302', children: [{ id: 'what-is-rvf', label: 'What is RVF?' }, { id: 'at-a-glance', label: 'At a Glance' }] }, { id: 'single-file', label: 'Single File', icon: '\u25A3', children: [{ id: 'segments', label: 'Segment Map' }, { id: 'why-one-file', label: 'Why One File?' }] }, { id: 'pipeline', label: 'Pipeline', icon: '\u25B6', children: [{ id: 'stage-ingest', label: 'Data Ingestion' }, { id: 'stage-process', label: 'Signal Processing' }, { id: 'stage-detect', label: 'Candidate Detection' }, { id: 'stage-score', label: 'Scoring' }, { id: 'stage-seal', label: 'Witness Sealing' }] }, { id: 'proof', label: 'Proof', icon: '\u2713', children: [{ id: 'witness-chain', label: 'Witness Chain' }, { id: 'reproducible', label: 'Reproducible' }, { id: 'acceptance', label: 'Acceptance Test' }, { id: 'blind', label: 'Blind Testing' }] }, { id: 'unique', label: 'Why Unique', icon: '\u2605' }, { id: 'capabilities', label: 'Views', icon: '\u25CE', children: [{ id: 'cap-atlas', label: 'Atlas Explorer' }, { id: 'cap-coherence', label: 'Coherence' }, { id: 'cap-boundaries', label: 'Boundaries' }, { id: 'cap-memory', label: 'Memory Tiers' }, { id: 'cap-planets', label: 'Planets' }, { id: 'cap-life', label: 'Life' }, { id: 'cap-witness', label: 'Witness Chain' }, { id: 'cap-solver', label: 'Solver' }, { id: 'cap-blind', label: 'Blind Test' }, { id: 'cap-discover', label: 'Discovery' }, { id: 'cap-dyson', label: 'Dyson Sphere' }, { id: 'cap-status', label: 'Status' }] }, { id: 'solver', label: 'Solver', icon: '\u2699', children: [{ id: 'thompson', label: 'Thompson Sampling' }, { id: 'auto-optimize', label: 'Auto-Optimize' }] }, { id: 'format', label: 'Format Spec', icon: '\u2630', children: [{ id: 'file-header', label: 'File Header' }, { id: 'seg-types', label: 'Segment Types' }, { id: 'witness-format', label: 'Witness Entry' }, { id: 'dashboard-seg', label: 'Dashboard Segment' }] }, { id: 'glossary', label: 'Glossary', icon: '\u2261' }, ]; export class DocsView { private container: HTMLElement | null = null; private contentEl: HTMLElement | null = null; private navLinks: Map = new Map(); private scrollRaf = 0; mount(container: HTMLElement): void { this.container = container; const wrapper = document.createElement('div'); wrapper.style.cssText = 'display:flex;width:100%;height:100%;overflow:hidden'; container.appendChild(wrapper); // Left nav sidebar const nav = this.buildNav(); wrapper.appendChild(nav); // Right content area this.contentEl = document.createElement('div'); this.contentEl.style.cssText = 'flex:1;overflow-y:auto;overflow-x:hidden;scroll-behavior:smooth;-webkit-overflow-scrolling:touch;min-width:0'; wrapper.appendChild(this.contentEl); const inner = document.createElement('div'); inner.style.cssText = 'max-width:820px;margin:0 auto;padding:28px 32px 100px;line-height:1.7;color:var(--text-secondary);font-size:13px'; this.contentEl.appendChild(inner); inner.innerHTML = this.buildContent(); // Scroll spy this.contentEl.addEventListener('scroll', this.onScroll); requestAnimationFrame(() => this.onScroll()); } unmount(): void { cancelAnimationFrame(this.scrollRaf); this.contentEl?.removeEventListener('scroll', this.onScroll); this.navLinks.clear(); this.contentEl = null; this.container = null; } /* ── Nav sidebar ── */ private buildNav(): HTMLElement { const nav = document.createElement('nav'); nav.style.cssText = ` width:220px;min-width:220px;background:var(--bg-panel);border-right:1px solid var(--border); overflow-y:auto;overflow-x:hidden;padding:16px 0;display:flex;flex-direction:column; -webkit-overflow-scrolling:touch;flex-shrink:0 `; // Title const title = document.createElement('div'); title.style.cssText = 'padding:0 16px 14px;font-size:13px;font-weight:600;color:var(--text-primary);letter-spacing:0.3px;border-bottom:1px solid var(--border);margin-bottom:8px'; title.textContent = 'Documentation'; nav.appendChild(title); for (const section of SECTIONS) { // Parent link const link = document.createElement('a'); link.style.cssText = ` display:flex;align-items:center;gap:8px;padding:7px 16px; font-size:12px;font-weight:600;color:var(--text-secondary);cursor:pointer; text-decoration:none;transition:color 0.15s,background 0.15s;border-left:2px solid transparent `; link.innerHTML = `${section.icon} ${section.label}`; link.addEventListener('click', (e) => { e.preventDefault(); this.scrollTo(section.id); }); link.addEventListener('mouseenter', () => { link.style.color = 'var(--text-primary)'; link.style.background = 'rgba(255,255,255,0.02)'; }); link.addEventListener('mouseleave', () => { if (!link.classList.contains('doc-active')) { link.style.color = 'var(--text-secondary)'; link.style.background = ''; } }); nav.appendChild(link); this.navLinks.set(section.id, link); // Child links if (section.children) { for (const child of section.children) { const clink = document.createElement('a'); clink.style.cssText = ` display:block;padding:4px 16px 4px 40px;font-size:11px;color:var(--text-muted); cursor:pointer;text-decoration:none;transition:color 0.15s;border-left:2px solid transparent `; clink.textContent = child.label; clink.addEventListener('click', (e) => { e.preventDefault(); this.scrollTo(child.id); }); clink.addEventListener('mouseenter', () => { clink.style.color = 'var(--text-secondary)'; }); clink.addEventListener('mouseleave', () => { if (!clink.classList.contains('doc-active')) clink.style.color = 'var(--text-muted)'; }); nav.appendChild(clink); this.navLinks.set(child.id, clink); } } } // Bottom spacer const spacer = document.createElement('div'); spacer.style.cssText = 'flex:1;min-height:20px'; nav.appendChild(spacer); // Footer const footer = document.createElement('div'); footer.style.cssText = 'padding:12px 16px;border-top:1px solid var(--border);font-size:9px;color:var(--text-muted);line-height:1.5'; footer.innerHTML = 'Built with RuVector
Rust + WASM + Three.js'; nav.appendChild(footer); return nav; } private scrollTo(id: string): void { const el = this.contentEl?.querySelector(`#${id}`) as HTMLElement | null; if (el && this.contentEl) { this.contentEl.scrollTo({ top: el.offsetTop - 20, behavior: 'smooth' }); } } /* ── Scroll spy ── */ private onScroll = (): void => { cancelAnimationFrame(this.scrollRaf); this.scrollRaf = requestAnimationFrame(() => { if (!this.contentEl) return; const scrollTop = this.contentEl.scrollTop + 60; // Find which section is currently visible let activeId = ''; const allIds = Array.from(this.navLinks.keys()); for (const id of allIds) { const el = this.contentEl.querySelector(`#${id}`) as HTMLElement | null; if (el && el.offsetTop <= scrollTop) activeId = id; } // Update nav highlights this.navLinks.forEach((link, id) => { const isActive = id === activeId; link.classList.toggle('doc-active', isActive); // Check if parent or child const isParent = SECTIONS.some(s => s.id === id); if (isActive) { link.style.color = 'var(--accent)'; link.style.borderLeftColor = 'var(--accent)'; link.style.background = isParent ? 'rgba(0,229,255,0.06)' : 'rgba(0,229,255,0.03)'; } else { link.style.color = isParent ? 'var(--text-secondary)' : 'var(--text-muted)'; link.style.borderLeftColor = 'transparent'; link.style.background = ''; } }); }); }; /* ── Content builder ── */ private buildContent(): string { const S = { h1: 'font-size:26px;font-weight:300;color:var(--text-primary);letter-spacing:0.5px;margin-bottom:6px', h2: 'font-size:19px;font-weight:600;color:var(--text-primary);margin-top:48px;margin-bottom:10px;padding-bottom:8px;border-bottom:1px solid var(--border)', h3: 'font-size:14px;font-weight:600;color:var(--accent);margin-top:28px;margin-bottom:8px', p: 'margin-bottom:14px', card: 'background:var(--bg-panel);border:1px solid var(--border);border-radius:6px;padding:14px 18px;margin-bottom:12px', code: 'font-family:var(--font-mono);font-size:11px;background:var(--bg-surface);border:1px solid var(--border);border-radius:4px;padding:12px 16px;display:block;margin:10px 0 14px;overflow-x:auto;line-height:1.6;color:var(--text-primary)', accent: 'color:var(--accent);font-weight:600', success: 'color:var(--success);font-weight:600', badge: 'display:inline-block;font-size:9px;font-weight:600;padding:2px 8px;border-radius:3px;margin-right:4px', inline: 'background:var(--bg-surface);padding:1px 6px;border-radius:3px;font-family:var(--font-mono);font-size:12px', }; return `
Causal Atlas Documentation
A complete guide to the RVF scientific discovery platform.
What is RVF?
RVF (RuVector Format) is a binary container that holds an entire scientific discovery pipeline — raw telescope data, analysis code, results, cryptographic proofs, and this interactive dashboard — in a single, self-contained file.
Think of it as a shipping container for science. Anyone who receives the file can independently verify every step of the analysis without external tools or databases.
At a Glance
${this.statCard('File Format', 'Binary, segmented', S)} ${this.statCard('Crypto', 'Ed25519 + SHAKE-256', S)} ${this.statCard('Solver', 'WASM + Thompson Sampling', S)} ${this.statCard('Dashboard', 'Three.js + D3', S)} ${this.statCard('Server', 'Rust / Axum', S)} ${this.statCard('Domains', 'Exoplanets, Dyson, Bio', S)}
One File Contains Everything
Traditional scientific data is scattered across files, servers, and packages. RVF packs everything into typed segments inside one binary file.
Segment Map
${this.segRow('HEADER (64 B)', 'File magic, version, segment count', 'var(--text-muted)')} ${this.segRow('DATA_SEG', 'Raw telescope observations (light curves, spectra)', '#FF6B9D')} ${this.segRow('KERNEL_SEG', 'Processing algorithms for analysis', '#FFB020')} ${this.segRow('EBPF_SEG', 'Fast in-kernel data filtering programs', '#9944FF')} ${this.segRow('WASM_SEG', 'Self-learning solver (runs in any browser)', '#2ECC71')} ${this.segRow('WITNESS_SEG', 'Cryptographic proof chain (Ed25519 signed)', 'var(--accent)')} ${this.segRow('DASHBOARD_SEG', 'This interactive 3D dashboard (HTML/JS/CSS)', '#FF4D4D')} ${this.segRow('SIGNATURE', 'Ed25519 signature over all segments', 'var(--text-muted)')}
Why One File?
Portability
Email it, USB drive, or static hosting. No server setup needed.
Reproducibility
Code + data together means anyone can re-run the analysis.
Integrity
Tampering with any segment breaks the signature chain.
Archival
One file to store, back up, and cite. No link rot.
How the Pipeline Works
The pipeline transforms raw observations into verified discoveries through five stages. Each stage is recorded in the witness chain for full traceability.
1. Data Ingestion
Raw photometric data (brightness over time) is ingested from telescope archives. For exoplanet detection, this means light curves — graphs of stellar brightness that dip when a planet transits its star.
2. Signal Processing
Processing kernels clean the data: removing instrumental noise, correcting for stellar variability, and flagging periodic signals. The eBPF programs accelerate filtering at near-hardware speed.
3. Candidate Detection
Cleaned signals are matched against known patterns. For exoplanets: periodic transit-shaped dips. For Dyson spheres: anomalous infrared excess. Each candidate gets derived parameters:
Exoplanets
Radius, period, temperature, HZ membership, ESI score
Dyson Candidates
IR excess ratio, dimming pattern, partial coverage fraction
4. Scoring & Ranking
Candidates are scored multi-dimensionally. The WASM solver uses Thompson Sampling to discover which analysis strategies work best for each difficulty level, continuously improving accuracy without human tuning.
5. Witness Sealing
Every step is recorded in the witness chain: a SHAKE-256 hash of the data, a timestamp, and an Ed25519 signature. This creates an immutable, cryptographically verifiable audit trail.
How Discoveries Are Proven
How do you know the results are real? RVF uses four layers of proof.
Layer 1: Cryptographic Witness Chain
Each processing step writes a witness entry containing:
• Step name — what operation was performed
• Input hash — SHAKE-256 of data going in
• Output hash — SHAKE-256 of data coming out
• Parent hash — links to previous entry (chain)
• Ed25519 signature — proves the entry is authentic
Each entry chains to the previous one. Altering any step breaks all subsequent signatures.
Layer 2: Reproducible Computation
The file contains the actual analysis code (WASM + eBPF) alongside raw data. Anyone can re-run the pipeline from scratch and verify identical results. No "trust us" — the math is in the file.
Layer 3: Acceptance Testing
Mode A (Heuristic) — Can the solver achieve basic accuracy?
Mode B (Compiler) — Accuracy + computational cost reduction?
Mode C (Learned) — Full: accuracy + cost + robustness + zero violations.
All three modes must pass. The manifest is itself recorded in the witness chain.
Layer 4: Blind Testing
The Blind Test page runs the pipeline on unlabeled data, then compares against ground truth. This guards against overfitting — the pipeline must work on data it has never seen.
What Makes This Unique
${this.uniqueCard('Self-Contained', 'One file. No cloud, no databases, no external dependencies. The entire pipeline, visualization, and proof chain travel together.', S)} ${this.uniqueCard('Cryptographically Verified', 'Every step is hashed and signed. Tampering with one part invalidates the entire chain. Mathematical proof, not just peer review.', S)} ${this.uniqueCard('Self-Learning', 'The WASM solver improves over time using Thompson Sampling, discovering which strategies work for different data difficulties.', S)} ${this.uniqueCard('Runs Anywhere', 'WASM solver + HTML dashboard + Rust server. No Python, no Jupyter, no conda. Open the file and explore in any modern browser.', S)} ${this.uniqueCard('Multi-Domain', 'Transit detection, Dyson sphere search, habitability scoring, biosignature analysis — all in one causal event graph.', S)} ${this.uniqueCard('Interactive 3D', 'Embedded Three.js dashboard: explore the causal atlas as a galaxy, rotate planet systems, visualize Dyson sphere geometry.', S)}
Dashboard Views
12 interactive views, each pulling live data from the RVF file.
${this.viewCard('cap-atlas', 'Atlas Explorer', '#/atlas', 'var(--accent)', '3D galaxy-style causal event graph. Each star = a causal event. Edges = cause-effect. Configurable arms, density, and sector labels.', ['3D OrbitControls', 'Time scale selector', 'Galaxy shape config', 'Star map sectors'])} ${this.viewCard('cap-coherence', 'Coherence Heatmap', '#/coherence', '#FFB020', 'Color-mapped surface showing data self-consistency across the observation grid. Blue = stable, red = high uncertainty.', ['Surface plot', 'Epoch scrubber', 'Partition boundaries'])} ${this.viewCard('cap-boundaries', 'Boundaries', '#/boundaries', '#9944FF', 'Tracks how data partition boundaries shift as new observations arrive. Alerts when boundaries change rapidly.', ['Timeline chart', 'Alert feed', 'Sector detail'])} ${this.viewCard('cap-memory', 'Memory Tiers', '#/memory', '#FF6B9D', 'Three-tier storage: Small (hot), Medium (warm), Large (cold). Shows utilization, hit rates, and tier migration.', ['S/M/L gauges', 'Utilization bars', 'Migration flow'])} ${this.viewCard('cap-planets', 'Planet Candidates', '#/planets', '#2ECC71', 'Ranked exoplanet candidates with radius, period, temperature, habitable zone status, and Earth Similarity Index.', ['Sortable table', 'Light curve plots', 'Score radar'])} ${this.viewCard('cap-life', 'Life Candidates', '#/life', '#2ECC71', 'Biosignature analysis: atmospheric spectra for O\u2082, CH\u2084, H\u2082O. Multi-dimensional scoring with confound analysis.', ['Spectrum plots', 'Molecule heatmap', 'Reaction graph'])} ${this.viewCard('cap-witness', 'Witness Chain', '#/witness', 'var(--accent)', 'Complete cryptographic audit trail. Every step with timestamp, hashes, and signature verification status.', ['Scrolling entries', 'Hash verification', 'Pipeline trace'])} ${this.viewCard('cap-solver', 'RVF Solver', '#/solver', '#FFB020', 'WASM self-learning solver with Thompson Sampling. 3D landscape shows bandit arm rewards. Configurable training parameters.', ['3D landscape', 'Training curves', 'A/B/C acceptance', 'Auto-Optimize'])} ${this.viewCard('cap-blind', 'Blind Test', '#/blind-test', '#FF4D4D', 'Pipeline on unlabeled data, then compared against ground truth. The gold standard for preventing overfitting.', ['Unlabeled processing', 'Ground truth compare', 'Accuracy metrics'])} ${this.viewCard('cap-discover', 'Discovery', '#/discover', '#00E5FF', '3D exoplanet systems with host star, orbit, habitable zone. Real KOI parameters. Galaxy background.', ['3D planet system', 'Speed/rotate controls', 'ESI comparison'])} ${this.viewCard('cap-dyson', 'Dyson Sphere', '#/dyson', '#9944FF', 'Dyson swarm detection using Project Hephaistos methodology. IR excess analysis and 3D wireframe visualization.', ['3D Dyson wireframe', 'IR excess analysis', 'SED plots'])} ${this.viewCard('cap-status', 'System Status', '#/status', '#8B949E', 'RVF file health, segment sizes, memory tier utilization, pipeline stage indicators, and live witness log.', ['Segment breakdown', 'Tier gauges', 'Witness log feed'])}
The Self-Learning Solver
The solver is a WebAssembly module compiled from Rust. It runs entirely in your browser using Thompson Sampling.
How Thompson Sampling Works
Imagine 8 different analysis strategies ("arms"). You don't know which works best. Thompson Sampling maintains a Beta distribution for each arm's success rate, samples from these on each attempt, and picks the highest sample. This balances:
Exploration — Trying uncertain arms to gather data
Exploitation — Using known-good arms to maximize results
Over time, the solver converges on optimal strategies per difficulty level. The 3D landscape visually shows which arms have the highest rewards.
Auto-Optimize
The Auto-Optimize button trains in batches of 3 rounds, tests acceptance after each batch, and stops when all three modes pass (max 30 rounds). If accuracy is below 60%, it automatically increases training intensity.
RVF File Format Reference
File Header (64 bytes)
Offset  Size  Field
0x00    4     Magic: 0x52564631 ("RVF1")
0x04    2     Format version (currently 1)
0x06    2     Flags (bit 0 = signed, bit 1 = compressed)
0x08    8     Total file size
0x10    4     Segment count
0x14    4     Reserved
0x18    32    SHAKE-256 hash of all segments
0x38    8     Creation timestamp (Unix epoch)
Segment Types
${this.tableRow('0x01', 'DATA', 'Raw observations (light curves, spectra)')} ${this.tableRow('0x02', 'KERNEL', 'Processing algorithms')} ${this.tableRow('0x03', 'RESULT', 'Computed results and derived parameters')} ${this.tableRow('0x04', 'WITNESS', 'Cryptographic audit trail')} ${this.tableRow('0x05', 'SIGNATURE', 'Ed25519 digital signature')} ${this.tableRow('0x06', 'INDEX', 'Fast lookup table for segments')} ${this.tableRow('0x0F', 'EBPF', 'eBPF bytecode for in-kernel filtering')} ${this.tableRow('0x10', 'WASM', 'WebAssembly solver module')} ${this.tableRow('0x11', 'DASHBOARD', 'Embedded web dashboard (HTML/JS/CSS)')}
ID Name Purpose
Witness Entry Format
struct WitnessEntry {
    step_name:   String,      // "transit_detection"
    timestamp:   u64,         // Unix epoch nanoseconds
    input_hash:  [u8; 32],    // SHAKE-256 of input
    output_hash: [u8; 32],    // SHAKE-256 of output
    parent_hash: [u8; 32],    // Previous entry hash (chain)
    signature:   [u8; 64],    // Ed25519 signature
}
Dashboard Segment
DashboardHeader (64 bytes):
    magic:       0x5256_4442  // "RVDB"
    version:     u16
    framework:   u8           // 0=threejs, 1=react
    compression: u8           // 0=none, 1=gzip, 2=brotli
    bundle_size: u64
    file_count:  u32
    hash:        [u8; 32]     // SHAKE-256 of bundle

Payload: [file_table] [file_data...]
Glossary
${this.glossaryRow('RVF', 'RuVector Format — the binary container')} ${this.glossaryRow('Segment', 'A typed block of data inside an RVF file')} ${this.glossaryRow('Witness Chain', 'Linked list of signed hash entries proving integrity')} ${this.glossaryRow('SHAKE-256', 'Cryptographic hash function (variable output)')} ${this.glossaryRow('Ed25519', 'Digital signature algorithm for witness entries')} ${this.glossaryRow('KOI', 'Kepler Object of Interest — exoplanet candidate')} ${this.glossaryRow('ESI', 'Earth Similarity Index (0-1, higher = more Earth-like)')} ${this.glossaryRow('Transit', 'Planet passing in front of its star, causing a brightness dip')} ${this.glossaryRow('Light Curve', 'Graph of stellar brightness over time')} ${this.glossaryRow('Habitable Zone', 'Orbital region where liquid water could exist')} ${this.glossaryRow('Thompson Samp.', 'Bandit algorithm balancing exploration vs exploitation')} ${this.glossaryRow('eBPF', 'Extended Berkeley Packet Filter — fast kernel programs')} ${this.glossaryRow('WASM', 'WebAssembly — portable code that runs in browsers')} ${this.glossaryRow('Dyson Sphere', 'Hypothetical megastructure around a star for energy')} ${this.glossaryRow('IR Excess', 'More infrared than expected — possible artificial origin')} ${this.glossaryRow('SED', 'Spectral Energy Distribution — brightness vs wavelength')} ${this.glossaryRow('Coherence', 'Self-consistency measure of data in a region')} ${this.glossaryRow('Acceptance', 'Three-mode validation (A/B/C) of solver quality')} ${this.glossaryRow('Blind Test', 'Evaluation on unlabeled data to prevent overfitting')}
Everything in this dashboard was served from a single .rvf file.
`; } /* ── Template helpers ── */ private statCard(label: string, value: string, S: Record): string { return `
${label}
${value}
`; } private segRow(name: string, desc: string, color: string): string { return `
${name}${desc}
`; } private uniqueCard(title: string, desc: string, S: Record): string { return `
${title}
${desc}
`; } private viewCard(id: string, title: string, route: string, color: string, desc: string, features: string[]): string { const badges = features.map(f => `${f}`).join(''); return `
${title} ${route}
${desc}
${badges}
`; } private tableRow(id: string, name: string, purpose: string): string { return `${id}${name}${purpose}`; } private glossaryRow(term: string, def: string): string { return `${term}${def}`; } }