ResonaGraph

Next-Generation Distributed Graph Database
Phase-Modulated Superpositions over Prime-Based Hilbert Spaces

Quick Start • Documentation • Examples • Papers

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Overview

ResonaGraph is a distributed graph database that replaces traditional data replication with resonance beacons - achieving 80-90% bandwidth savings while maintaining eventual consistency through thermodynamic principles.

Core Innovation

Instead of replicating entire data structures, ResonaGraph encodes graph elements as phase-modulated superpositions in prime-indexed Hilbert spaces. Data is reconstructed non-locally through:

• Resonance Locking: Iterative convergence to recover original data
• Chinese Remainder Theorem: Mathematical guarantee of reconstruction
• REC (Resonant Eventual Consistency): Thermodynamic conflict resolution
• Phase-Key Cryptography: Built-in access control without central auth

Key Features

🚀 Performance

• Sub-second queries at 1M+ nodes
• 80-90% bandwidth reduction vs traditional replication
• GPU acceleration for resonance locking (50-200x speedup)
• LZ4 compression with delta encoding for beacons

🔒 Security

• Phase-key access control with HMAC-based cryptographic binding
• Hardware Security Module (HSM) integration
• Real-time threat detection with behavioral analytics
• Compliance reporting (GDPR, SOX, HIPAA, SOC2, ISO 27001)
• Advanced audit logging with anonymization

🌐 Distributed

• Partition tolerance through REC conflict resolution
• Gossip protocol with Kademlia DHT discovery
• Compact beacons (128-512 bytes) for coordination
• Multi-epoch storage with automatic conflict resolution

📊 Developer Experience

• Cypher-inspired query language with resonance extensions
• Familiar APIs (put, get, query, traverse)
• Python SDK with type hints
• Comprehensive examples and documentation

Quick Start

from resonagraph import Client, PhaseKey, Query

# Initialize client and create phase key
client = Client("https://api.resonagraph.com/v1")
phase_key = PhaseKey.from_secret(b"your-32-byte-secret-key-here!")

# Store a vertex with GPU acceleration
beacon = client.put(
    key="vertex:user_alice",
    payload={"name": "Alice", "email": "[email protected]", "age": 30},
    phase_key=phase_key,
    options={
        "k_primes": 48,           # 32-64 primes for security/performance balance
        "taper_alpha": 0.05,      # Convergence speed
        "use_gpu": True,          # Enable GPU acceleration
        "enable_compression": True # Enable LZ4 compression
    }
)

# Query with resonance extensions
query = Query("""
    MATCH (u:User {id: 'alice'})-[:FOLLOWS*1..2]->(f)
    COHERE ON u,f  -- Apply coherence bias for efficient traversal
    RETURN f.name, f.email
""")

results = client.query(query, phase_key=phase_key)
print(f"Found {len(results['nodes'])} connections")

Installation

From PyPI (Coming Soon)

pip install resonagraph

From Source

git clone https://github.com/sschepis/resonagraph.git
cd resonagraph
pip install -r requirements.txt
pip install -e .

With GPU Support

# Install CUDA toolkit first (11.0+)
pip install -r requirements.txt
pip install cupy-cuda11x  # Match your CUDA version
pip install -e .

Run Tests

# All tests
python -m pytest resonagraph/tests/ -v

# With coverage
python -m pytest resonagraph/tests/ --cov=resonagraph

# Specific modules
python -m pytest resonagraph/tests/test_gpu_acceleration.py -v

JavaScript/TypeScript Port

ResonaGraph is also available as a JavaScript/TypeScript library! The JavaScript port includes:

• 🚀 Full core functionality: Phase encoding, resonance locking, CRT reconstruction
• 🖥️ Server process: HTTP/WebSocket RPC node for distributed deployments
• 💻 CLI tool: Command-line interface for easy interaction
• 📦 npm package: Installable via npm (coming soon)
• ✅ 23 passing tests: Full test coverage of core modules

Quick Start (JavaScript)

import { Client, PhaseKey } from 'resonagraph';

const client = new Client('http://localhost:8443');
const phaseKey = PhaseKey.fromPassphrase('my-secret');

// Store data
const beacon = client.put('user:alice', 
  { name: 'Alice', email: '[email protected]' },
  phaseKey
);

// Retrieve data
const result = client.get('user:alice', phaseKey);
console.log(result.payload);

Install JavaScript Port

cd javascript
npm install
npm run build

# Run the server
npm run server

# Use the CLI
node dist/cli.js put user:alice '{"name":"Alice"}'
node dist/cli.js get user:alice

See the JavaScript README for complete documentation.

Architecture

ResonaGraph implements a layered architecture with five main planes:

┌──────────────────────────────────────────────────────────┐
│                   Client SDK Layer                       │
│  • Query execution  • Probe synthesis  • Caching         │
└──────────────────────────────────────────────────────────┘
                            ↕
┌──────────────────────────────────────────────────────────┐
│                    Gossip Plane                          │
│  • QUIC protocol  • Beacon structure  • DHT discovery    │
└──────────────────────────────────────────────────────────┘
                            ↕
┌──────────────────────────────────────────────────────────┐
│                  Resonance Plane                         │
│  • Locking (CPU/GPU)  • Residue extraction  • CRT        │
└──────────────────────────────────────────────────────────┘
                            ↕
┌──────────────────────────────────────────────────────────┐
│                   Storage Layer                          │
│  • RocksDB  • Phase indices  • LZ4 compression           │
└──────────────────────────────────────────────────────────┘
                            ↕
┌──────────────────────────────────────────────────────────┐
│         Security & Monitoring Layer                      │
│  • HSM  • Threat detection  • Compliance  • Analytics    │
└──────────────────────────────────────────────────────────┘

Core Concepts

Phase Encoding

Data is encoded as phase angles in a prime-indexed space:

θ_p = 2π(m_j mod p + α/φ + β/δ + HMAC(p||j, K))

Where:

• m_j: Payload symbol (byte chunk)
• p: Prime from deterministically selected set
• α: Taper parameter (0.05-0.15)
• φ: Golden ratio (1+√5)/2
• K: Phase key for cryptographic binding

Resonance Locking

Iterative convergence process to recover data:

|Q⟩ = ∑ w_p e^{iφ_p} |p⟩     # Probe superposition
R = |⟨Q|A⟩|                  # Overlap with address
S(t) = S_0 e^{-λt}           # Entropy decay
RS(t) = RS_★(1 - e^{-γt})    # Resonance growth

Convergence criteria: R > 0.95 AND S < 0.01

Resonant Eventual Consistency (REC)

Conflict resolution via thermodynamic selection:

1. Detect multiple epochs for same key
2. Simulate dynamics to steady state for each candidate
3. Select winner: min(S_stable) AND max(RS_stable)

Security Features

Threat Detection

from resonagraph.security import ThreatDetector, SecurityMonitor

detector = ThreatDetector(
    alert_callback=handle_alert,
    baseline_window=24 * 3600  # 24-hour behavioral baseline
)

# Automatic detection of:
# - Brute force attacks
# - Key enumeration
# - Replay attacks
# - Mass data exfiltration
# - Privilege escalation

Compliance Reporting

from resonagraph.security import ComplianceReporter, ComplianceFramework

reporter = ComplianceReporter(audit_logger)
report = reporter.generate_compliance_report(
    framework=ComplianceFramework.GDPR,
    start_time=start_of_quarter,
    end_time=end_of_quarter
)

print(f"Compliance Score: {report['executive_summary']['compliance_score']:.1f}%")

HSM Integration

from resonagraph.security import HSMManager, YubiHSMProvider

hsm = HSMManager(provider=YubiHSMProvider(connector_url="http://localhost:12345"))
signature = hsm.sign(message, key_id="signing-key-01")

Query Language

ResonaGraph supports a Cypher-inspired query language with resonance extensions:

-- Find mutual connections
MATCH (a:User {id: "alice"})-[:FOLLOWS]->(mutual)<-[:FOLLOWS]-(b:User {id: "bob"})
COHERE ON a,b,mutual
RETURN mutual.name, mutual.email

-- Recent posts with epoch filtering
MATCH (u:User {id: "alice"})-[:FOLLOWS]->(f)-[:POSTED]->(p:Post)
WHERE p.created_at > date('2024-01-01')
EPOCH WINDOW +2
RETURN f.name, p.title, p.created_at
ORDER BY p.created_at DESC
LIMIT 10

-- Variable-length paths with coherence
MATCH (u:User {id: "alice"})-[:FOLLOWS*1..3]->(f)
COHERE ON u,f
RETURN f.name, f.connections

Resonance Extensions

• COHERE ON variables: Apply coherence bias for efficient subgraph traversal
• EPOCH WINDOW ±n: Filter beacons by epoch drift tolerance

Performance Tuning

GPU Acceleration

# Enable GPU for large-scale operations
options = {
    "use_gpu": True,
    "gpu_device_id": 0,  # CUDA device ID
    "gpu_batch_size": 1000  # Batch multiple operations
}

result = client.get("vertex:alice", phase_key, options=options)

Benchmarks (RTX 3090):

• Single lock: 50-200x speedup
• Batch operations: 100-500x speedup
• Memory overhead: ~2GB for 10k concurrent locks

Compression

# Enable LZ4 compression for beacons
options = {
    "enable_compression": True,
    "compression_level": 6,  # 1-9, higher = better compression
    "use_delta_encoding": True  # For prime indices
}

beacon = client.put("vertex:alice", payload, phase_key, options=options)

Compression Ratios:

• Beacon size: 60-80% reduction
• Prime indices: 75-85% reduction (delta encoding)
• Overall bandwidth: 65-75% reduction

Parameter Tuning

# High performance (lower security)
options = {"k_primes": 32, "taper_alpha": 0.05, "r_min": 0.90}

# Balanced (recommended)
options = {"k_primes": 48, "taper_alpha": 0.10, "r_min": 0.95}

# High security (slower)
options = {"k_primes": 64, "taper_alpha": 0.15, "r_min": 0.98}

Documentation

Core Documentation

• User's Guide - Complete user documentation
• System Reference - Technical architecture and implementation
• Security Guidelines - Security best practices
• Threat Model - Security analysis and mitigations

Research Papers

See papers/ directory for:

• Prime-Resonant Graph Databases
• Quantum Prime Resonance
• Resonant Model & Sentience
• Triadic Resonance Theory
• And more...

Examples

# Run basic demo
PYTHONPATH=. python examples/basic_demo.py

# Run GPU acceleration demo
PYTHONPATH=. python examples/gpu_demo.py

# Run security demo
PYTHONPATH=. python examples/security_demo.py

# Run compression demo
PYTHONPATH=. python examples/compression_demo.py

See examples/ directory for more demonstrations.

Deployment

Docker

# Single node
docker run -p 8443:8443 resonagraph/node:latest

# Cluster
docker-compose up -d

Kubernetes

kubectl apply -f k8s/deployment.yaml
kubectl apply -f k8s/service.yaml

See Deployment Guide for details.

Testing

# All tests
python -m pytest resonagraph/tests/ -v

# With coverage
python -m pytest resonagraph/tests/ --cov=resonagraph --cov-report=html

# Specific modules
python -m pytest resonagraph/tests/test_gpu_acceleration.py -v
python -m pytest resonagraph/tests/test_compression.py -v
python -m pytest resonagraph/tests/security/ -v

# Benchmarks
python -m pytest resonagraph/tests/test_gpu_acceleration.py -v -k benchmark

Current Status: 220 tests passing, 3 skipped

Test Categories

• Unit Tests: Core algorithms and data structures
• Integration Tests: Multi-component workflows
• Security Tests: Access control, audit logging, threat detection
• Performance Tests: GPU acceleration, compression ratios
• Fuzz Tests: Robustness and edge cases

Contributing

We welcome contributions! Please see:

• Copilot Instructions - Development guidelines
• Code style: Black formatter, type hints required
• Tests: All new features must include tests
• Documentation: Update relevant docs with changes

License

MIT License - see LICENSE file for details.

Citation

If you use ResonaGraph in your research, please cite:

@techreport{schepis2025resonagraph,
  title={Prime-Resonant Graph Databases},
  author={Schepis, Sebastian},
  institution={xAI},
  year={2025},
  type={Technical Report}
}

Acknowledgments

ResonaGraph implements the Prime-Resonant Graph Database formalism developed by Sebastian Schepis (2025). The project builds on foundational work in:

• Prime number theory and Chinese Remainder Theorem
• Quantum-inspired computing and superposition principles
• Thermodynamic principles in distributed systems
• Modern graph database design

Support

• Documentation: https://resonagraph.readthedocs.io
• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [email protected]

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