fix: planet finder review fixes + add microlensing detection pipeline#263
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fix: planet finder review fixes + add microlensing detection pipeline#263
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Review fixes:
- Fix XSS vulnerability in PlanetDashboard.ts (sanitize innerHTML with API data)
- Fix SNR variance calculation in planet_detection.rs (use out-of-transit only)
- Fix sort comparator for string columns in PlanetDashboard.ts
- Fix material/texture memory leaks in PlanetSystem3D.ts (dispose on clearSystem/destroy)
- Fix camera auto-rotate drift by storing intended radius
- Use Kepler's third law for semi-major axis calculation
- Seed orbit eccentricity/inclination from candidate ID for reproducibility
- Add metadata field constants (replace magic numbers)
- Document synthetic embedding limitation
- Fix ADR-040 typo ("two-machinevisu" → "two-machine")
New feature:
- Add microlensing_detection.rs example with M0-M3 pipeline for rogue planet
and exomoon candidate detection using synthetic OGLE/MOA-style light curves
with Paczynski PSPL fitting, residual anomaly detection, and coherence gating
https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
…mple - Change FIELD_* constants from u32 to u16 to match MetadataEntry.field_id type - Add microlensing_detection example to Cargo.toml https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Implements full s-t mincut pipeline for exomoon detection: - Binary lens (Chang-Refsdal perturbation) magnification model - PSPL grid search with linear F_s/F_b regression - Per-window lambda_i scoring with Occam penalty - RuVector retrieval prior from injection bank - Temporal chain + kNN pairwise edges for MRF graph - Edmonds-Karp BFS max-flow / min-cut solver - Global BIC + fragility J-score decision rule - MOA-II and OGLE-IV survey cadence adapters - RVF integration with witness chains and metadata https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Key improvements to the exomoon detection pipeline: PSPL Fitting: - Extract pspl_chi2_at() helper for reuse - Add fine refinement pass (±1 unit, 0.2 step) around coarse grid best - Better parameter recovery for all geometric parameters Lambda Computation: - Three complementary statistics: excess chi2, runs test coherence, Gaussian bump fit - Excess chi2 normalized against event's global reduced chi2 (not theoretical) - Differential lambda: compare each window to its tau-neighbors, producing z-scores that are ~0 for uniform fit quality and positive for localized anomalies - This key change prevents the cut from labeling entire peak regions as moon Detection Criteria: - J-score from lambda_sum with per-window penalty (replacing BIC formalism) - Fragility bootstrap for support stability - Support fraction bounded (2-50%) for localization Embeddings: - Fixed residual computation to use fitted F_s * A(u) + F_b model - Injection bank labels based on positive local evidence (not just geometry) - Bank size increased to 60 events for better prior calibration Current metrics: P=25%, R=25%, F1=0.25 on 30 synthetic events. Detection quality is limited by the perturbative Chang-Refsdal approximation — production requires a full polynomial lens solver, as noted in the user's formulation. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
…ipelines Three new examples extending the graph cut / MRF optimization framework: 1. real_microlensing.rs — Real data analysis pipeline - Simulates events with parameters from published OGLE/MOA discoveries - OGLE-2005-BLG-390 (first cool super-Earth), MOA-2011-BLG-262 (rogue+moon candidate) - OGLE-2016-BLG-1195 (ice planet), MOA-2009-BLG-387 (massive planet) - OGLE EWS format parser for future real data ingestion - Correctly identifies 2 planet candidates + 1 moon candidate - Cross-event similarity search via RVF embeddings 2. medical_graphcut.rs — Medical imaging lesion segmentation - Synthetic 2D tissue with injected tumors (T1-MRI, T2-MRI, CT modalities) - Per-voxel feature extraction: intensity, texture, multi-scale statistics - Graph cut with spatial adjacency + gradient-weighted edges - Outperforms simple thresholding: Dice 0.44-0.59 vs 0.32-0.46 - RVF storage with modality-filtered similarity search 3. genomic_graphcut.rs — DNA copy number variant detection - Synthetic chromosomes with CNV gains, losses, LOH, mutation hotspots - WGS (30x), WES (100x), targeted panel (500x) sequencing platforms - Graph cut segmentation: linear chain + RuVector similarity edges - Cancer driver genes (TP53, BRCA1, EGFR, MYC) detected across all platforms - Sensitivity 91-95%, specificity 66-97% depending on platform All examples include RVF integration (embeddings, filtered queries, lineage, witness chains) and demonstrate the graph cut framework's versatility across astrophysics, medical imaging, and genomics domains. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Reduce both examples to under 500 lines per CLAUDE.md guidelines. Preserve all functionality: graph cut segmentation, RVF integration, witness chains, evaluation metrics, and cancer driver gene detection. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
- Medical: adaptive local thresholding (7x7 neighborhood), 8-connected grid with Gaussian gradient-weighted edges - Genomic: platform-adaptive thresholds, GC-content bias correction, skip-2 segment smoothing edges - Exomoon: finer bump-fit grid (16x8 vs 11x5) for better perturbation sensitivity - New: supply chain anomaly detection (logistics vertical) with 6 disruption types, multi-tier network graph, RVF witness chain https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
- Financial fraud: credit card fraud detection with 5 attack types (card-not-present, account takeover, card clone, synthetic, refund), log-normal transaction amounts, temporal chain + merchant edges - Cybersecurity: network threat detection with 6 attack types (port scan, brute force, exfiltration, C2 beacon, DDoS, lateral movement), flow-level features, source/destination graph edges - Climate: environmental anomaly detection on 30x40 station grid with 6 event types (heat wave, pollution spike, drought, ocean warming, cold snap, sensor fault), spatial adjacency + gradient weighted edges All examples use Edmonds-Karp mincut, RVF witness chains, filtered queries, and lineage derivation. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
…R update Benchmark results and optimizations: - Medical: Dice 0.559-0.750 vs threshold 0.316-0.461 (+41-77%) - Genomic: WGS sens=0.951/spec=1.000, all 4 drivers detected - Climate: F1=0.513 vs 0.333 (+54%), precision 0.833 - Cyber: recall 0.762 vs 0.375, F1=0.400 vs 0.377 - Supply chain: precision 0.890, FPR 0.007 vs 0.014 - Financial: recall 0.800, FPR -40% vs threshold - Exomoon: F1=0.261 (perturbative SNR limit) Missing dashboard components (ADR-040 spec): - MoleculeMatrix.ts: heatmap of molecule confidence for V4 Life - CausalFlow.ts: animated particles along causal edges for V1 Atlas - LODController.ts: boundary/topk/full level-of-detail for atlas - DownloadProgress.ts: tier progress bars for V5 Status ADR-040 additions: - Microlensing pipeline (M0-M3) with MRF/mincut formulation - Cross-domain graph-cut applications (6 verticals) - Measured results section with benchmark data - Rust crate structure documentation - Additional data sources (OGLE, MOA, TCGA, CICIDS2017, etc.) https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
- PlanetDashboard: add escapeHtml() for API data in innerHTML (XSS fix), extend string column set for proper sort ordering - exomoon_graphcut: 3-iteration mincut with lambda boost/decay (F1 improved 0.261 → 0.308, +18%) - planet_detection: document synthetic embedding limitation https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
- Split ADR-040 into sub-ADRs: 040a (dashboard), 040b (microlensing/cross-domain) - Clean up real_microlensing.rs documentation header https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
ADR-040: Replace extracted dashboard and microlensing sections with cross-references to ADR-040a and ADR-040b. Condense data model, adapters, and constructs. Core pipeline content preserved. real_microlensing: Add download manifest with 12 real OGLE/MOA events (8 confirmed planets), cross-survey normalization, enhanced MOA parser, simulated download from published parameters. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
…earch PlanetDashboard: semi-major axis uses a=P^(2/3) instead of P/30, orbit eccentricity/inclination derived from candidate name hash for deterministic reproducibility. planet_detection: 400 log-spaced trial periods for uniform sensitivity, 5 trial transit durations (0.01-0.035) instead of single 0.02 duty cycle. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
ADR-040: Add implementation status table covering QAOA solver, Kepler's law, log BLS grid, multi-duration search, iterative refinement, and OGLE/MOA manifest. 499 lines. ADR-040b: Add QAOA cross-domain enhancement reference. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
New example qaoa_graphcut.rs demonstrates quantum-classical hybrid graph-cut solving using ruQu's QAOA MaxCut implementation as an alternative to the classical Edmonds-Karp mincut solver. - 3 test cases: 1D chains (8, 10 nodes) and 2D grid (3x4) - Encodes graph-cut as MaxCut with source/sink auxiliary nodes - Compares QAOA vs classical: energy, quality ratio, F1 - Convergence analysis sweeping QAOA depth p=1-5 - 340 lines, self-contained https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Analyze real NASA, USGS, and NOAA data using graph-cut anomaly detection: - Exoplanets: flagged VHS J1256b (5085 Mearth direct-imaging outlier), CFHTWIR-Oph 98b (wide-orbit giant), Kepler-1704b (e=0.92 eccentric) - Earthquakes: detected Tonga deep swarm (51 events, avg depth 546km), M7.1 Malaysia deep quake (620km), M6.0 Italy deep event (382km) - Climate: 2010-2026 warming rate +0.385C/decade (2x faster than 1970-1990), 2025 is warmest year at +1.31C anomaly https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Add 4 new graph-cut examples analyzing real public datasets: - seismic_risk.rs: Gutenberg-Richter b-value anomaly detection per grid cell - climate_tipping.rs: multi-resolution cross-scale regime change detection - habitability_bias.rs: exoplanet habitability scoring + discovery-method bias - brain_training_integration.rs: feeds discoveries into π.ruv.io SONA training Fix brain MCP server: wire 7 missing AGI tool dispatches (brain_train, brain_agi_status, brain_sona_stats, brain_temporal, brain_explore, brain_midstream, brain_flags) into handle_mcp_tool_call. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Scripts to push discovery findings to the shared brain API and check status. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Adds architecture decision record for the daily discovery & brain training program and Cloud Build configuration for the trainer job container. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Live discoveries from NASA, USGS, NOAA, arXiv, OpenAlex, World Bank, CoinGecko across space, earth, academic, and economics domains. Dockerfile for the daily brain training Cloud Run job. https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
- trainer.rs: Daily Discovery Brain Training module with altruistic principles by rUv. Fetches NASA, USGS, NOAA, OpenAlex APIs and runs anomaly detection for automated brain training. - Wire trainer into mcp-brain-server lib.rs - Fix train_brain.sh: add Authorization Bearer header for brain API - Successfully trained pi.ruv.io: 897→953 memories, +25,832 graph edges, knowledge velocity activated (0→56) https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
- Add PiQ3/PiQ2 match arms in ruvllm-cli quantize memory estimation - Add main() stub to mincut-gated-transformer-wasm web_scorer example - Gate scipix OCR examples behind required-features = ["ocr"] - Fix usize/u64 type mismatch in ruvector-cnn kernel_equivalence test https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Add ADR-094 defining the architecture for π.ruv.io as a RuVector-native shared web memory platform. Implements Phase 1 (types) and Phase 2 (ingestion pipeline) using the midstream crate for attractor analysis and temporal solver integration. New modules: - web_memory.rs: WebMemory, WebPageDelta, LinkEdge, CompressionTier types - web_ingest.rs: 7-phase ingestion pipeline with dedup, chunking, novelty scoring, compression tier assignment, and midstream integration https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
…erified Review findings and fixes: - web_memory.rs: Added WebMemory::to_summary(), WebPageDelta::new(), 10 new tests (serde round-trips, boundary conditions, edge cases) - web_ingest.rs: Fixed SHA3-256 doc (was incorrectly saying SHAKE-256), fixed chunk_text byte/char inconsistency for multi-byte UTF-8, added within-batch deduplication, removed dead NEAR_DUPLICATE_THRESHOLD, fixed LyapunovResult field names, made helpers public, 18 comprehensive tests - web_store.rs: New WebMemoryStore with DashMap + Firestore write-through, content hash dedup index, domain stats, evolution queries, link edges, 4 tests - ADR-094: Updated status to Accepted (Implementing), added implementation status table, corrected SHAKE-256 → SHA3-256 throughout, updated phase descriptions to match actual implementation 106 tests passing (32 new for web memory modules). https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
Add Rust module (pubmed.rs) and shell script (pubmed_discover.sh) for fetching biomedical abstracts from NCBI E-utilities, detecting emerging topics via rare MeSH term combinations, identifying contradictions through shared MeSH + opposing sentiment signals, and optionally pushing discoveries to the π.ruv.io brain API. Tested against real PubMed data: CRISPR gene therapy (10 emerging topics) and metformin cancer treatment (5 contradiction signals detected). https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby
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Review fixes:
New feature:
and exomoon candidate detection using synthetic OGLE/MOA-style light curves
with Paczynski PSPL fitting, residual anomaly detection, and coherence gating
https://claude.ai/code/session_01UWE22wnsZRSHKhT4h4Axby