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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 |
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| apify | ||
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| meta-cognition-spiking-neural-network | ||
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| onnx-embeddings-wasm | ||
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| pwa-loader | ||
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| robotics | ||
| rust | ||
| ruvLLM | ||
| rvf | ||
| rvf-desktop | ||
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| verified-applications | ||
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| wasm/ios | ||
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| bounded_instance_demo.rs | ||
| README.md | ||
| security_hardened.rvf | ||
RuVector Examples
Comprehensive examples demonstrating RuVector's capabilities across multiple platforms and use cases.
Directory Structure
examples/
├── rust/ # Rust SDK examples
├── nodejs/ # Node.js SDK examples
├── graph/ # Graph database features
├── wasm-react/ # React + WebAssembly integration
├── wasm-vanilla/ # Vanilla JS + WebAssembly
├── agentic-jujutsu/ # AI agent version control
├── exo-ai-2025/ # Advanced cognitive substrate
├── refrag-pipeline/ # Document processing pipeline
└── docs/ # Additional documentation
Quick Start by Platform
Rust
cd rust
cargo run --example basic_usage
cargo run --example advanced_features
cargo run --example agenticdb_demo
Node.js
cd nodejs
npm install
node basic_usage.js
node semantic_search.js
WebAssembly (React)
cd wasm-react
npm install
npm run dev
WebAssembly (Vanilla)
cd wasm-vanilla
# Open index.html in browser
Example Categories
| Category | Directory | Description |
|---|---|---|
| Core API | rust/basic_usage.rs |
Vector DB fundamentals |
| Batch Ops | rust/batch_operations.rs |
High-throughput ingestion |
| RAG Pipeline | rust/rag_pipeline.rs |
Retrieval-Augmented Generation |
| Advanced | rust/advanced_features.rs |
Hypergraphs, neural hashing |
| AgenticDB | rust/agenticdb_demo.rs |
AI agent memory system |
| GNN | rust/gnn_example.rs |
Graph Neural Networks |
| Graph | graph/ |
Cypher queries, clustering |
| Node.js | nodejs/ |
JavaScript integration |
| WASM React | wasm-react/ |
Modern React apps |
| WASM Vanilla | wasm-vanilla/ |
Browser without framework |
| Agentic Jujutsu | agentic-jujutsu/ |
Multi-agent version control |
| EXO-AI 2025 | exo-ai-2025/ |
Cognitive substrate research |
| Refrag | refrag-pipeline/ |
Document fragmentation |
Feature Highlights
Vector Database Core
- High-performance similarity search
- Multiple distance metrics (Cosine, Euclidean, Dot Product)
- Metadata filtering
- Batch operations
Advanced Features
- Hypergraph Index: Multi-entity relationships
- Temporal Hypergraph: Time-aware relationships
- Causal Memory: Cause-effect chains
- Learned Index: ML-optimized indexing
- Neural Hash: Locality-sensitive hashing
- Topological Analysis: Persistent homology
AgenticDB
- Reflexion episodes (self-critique)
- Skill library (consolidated patterns)
- Causal memory (hypergraph relationships)
- Learning sessions (RL training data)
- Vector embeddings (core storage)
EXO-AI Cognitive Substrate
- exo-core: IIT consciousness, thermodynamics
- exo-temporal: Causal memory coordination
- exo-hypergraph: Topological structures
- exo-manifold: Continuous deformation
- exo-exotic: 10 cutting-edge experiments
- exo-wasm: Browser deployment
- exo-federation: Distributed consensus
- exo-node: Native bindings
- exo-backend-classical: Classical compute
Running Benchmarks
# Rust benchmarks
cargo bench --example advanced_features
# Refrag pipeline benchmarks
cd refrag-pipeline
cargo bench
# EXO-AI benchmarks
cd exo-ai-2025
cargo bench
Related Documentation
License
MIT OR Apache-2.0