Enterprise-grade Quantum Computing Framework with 13-dimensional Metatron Geometry

Q⊗DASH (MetatronQSO - Quantum State Operator) is a state-of-the-art quantum computing framework in pure Rust, based on the Sacred Geometry of Metatron's Cube. The system implements a complete stack of quantum algorithms, variational methods, dynamic tripolar logic, and automatic calibration through the Seraphic Calibration Shell.

• 13-dimensional Metatron Cube - Complete geometric quantum structure with 78 edges
• Variational Quantum Algorithms - VQE, QAOA, VQC with 3 ansatz types
• Dynamic Tripolar Logic (DTL) - 58.5% information advantage over binary systems
• Seraphic Calibration Shell (SCS) - Automatic hyperparameter optimization
• DioniceOS Integration - 4D-funnel system for 4D-5D coupling
• Python SDK - High-performance bindings via PyO3
• Backend Abstraction - Unified interface for Local/IBM/Cloud backends
• Telemetry & Dashboard - Real-time monitoring with REST API
• 24 Rust Crates - Modular workspace architecture

The project is organized as a Cargo workspace with 24 crates:

• apollyon_5d/ (3 Crates) - 5D dynamic system framework

  • core - Dynamics, coupling, ensemble, stability
  • bridge - Integration layer
  • metatron - Geometric cognition engine

• infinity-ledger/ (13 Crates) - MEF Pipeline System

  • mef-core - Core MEF pipeline
  • mef-ledger - Hash-chained ledger
  • mef-memory - Vector memory with adaptive routing
  • mef-router - S7 routing system
  • mef-spiral, mef-storage, mef-hdag, mef-topology, mef-coupling, mef-schemas
  • mef-solvecoagula - Double-kick operators
  • Additional: acquisition, domains, knowledge, api, audit, cli, benchmarks, tic, vector-db

• apollyon-mef-bridge/ - APOLLYON-5D ⟷ Infinity-Ledger Bridge

  • 4D-funnel system (8 modules)
  • 4 bidirectional adapters
  • Unified cognitive engine

• overlay/ - Unified 5D Cube Overlay

For Windows users: Before building, you need to install additional tools:

• CMake (required for cryptographic dependencies)
• NASM (recommended for performance)
• Visual Studio Build Tools 2022 with C++ workload

📖 See docs/WINDOWS_SETUP.md for detailed Windows installation instructions

For Linux/macOS users:

• Rust 1.85.0+
• Standard build tools (gcc/clang)
• CMake (usually available via package manager: apt install cmake / brew install cmake)

# Clone repository
git clone https://github.com/LashSesh/qso.git
cd qso

# Build core library
cargo build --release -p metatron-qso-rs

# Run all tests
cargo test --workspace

# Run benchmarks
cargo run --release --bin quantum_walk_bench

use metatron_qso_rs::prelude::*;

fn main() -> Result<()> {
    // Initialize Metatron QSO
    let qso = QSO::new(QSOParameters::default())?;

    // Quantum walk from center node
    let initial = QuantumState::basis_state(0); // Node 0 = center
    let evolved = qso.evolve_state(&initial, 1.0)?;

    // Probability distribution
    for (node, prob) in evolved.probabilities().iter().enumerate() {
        println!("Node {}: {:.4}", node, prob);
    }

    Ok(())
}

# Install Python SDK
cd metatron_qso_py
pip install maturin
maturin develop --release

import metatron_qso

# Create Metatron graph
graph = metatron_qso.MetatronGraph()

# Run quantum walk
result = metatron_qso.run_quantum_walk(
    graph=graph,
    source_nodes=[0],
    t_max=5.0,
    dt=0.1
)

# QAOA for MaxCut
qaoa_result = metatron_qso.solve_maxcut_qaoa(
    graph=graph,
    depth=3,
    max_iters=100
)

# VQE ground state
vqe_result = metatron_qso.run_vqe(
    graph=graph,
    depth=2,
    ansatz_type="hardware_efficient"
)

13-dimensional Cube based on Sacred Geometry:

• 1 center node (Node 0)
• 6 hexagon nodes (Nodes 1-6)
• 6 cube nodes (Nodes 7-12)
• 78 edges with complete connectivity
• Embedding of all 5 Platonic solids
• Symmetry group G_M for error-resistant operations

Graph Properties:

• Average degree: 12
• Algebraic connectivity: λ₁ > 0 (high)
• Code distance: d ≥ 6 (topological error correction)

VQE (Variational Quantum Eigensolver):

use metatron_qso_rs::vqa::{VQE, AnsatzType};

let vqe = VQE::builder()
    .hamiltonian(qso.hamiltonian().clone())
    .ansatz_type(AnsatzType::HardwareEfficient)
    .depth(2)
    .optimizer_name("ADAM")
    .max_iterations(1000)
    .build()?;

let result = vqe.run()?;
println!("Ground Energy: {:.10}", result.ground_energy);

3 Ansatz Types:

• HardwareEfficient - Optimized for hardware implementation
• EfficientSU2 - SU(2)-based
• MetatronAnsatz - Specialized for Metatron geometry

QAOA (Quantum Approximate Optimization Algorithm):

use metatron_qso_rs::vqa::{QAOA, MaxCutProblem};

let graph = MetatronGraph::new();
let problem = MaxCutProblem::from_graph(&graph);
let qaoa = QAOA::new(problem.hamiltonian(), 3);
let result = qaoa.run()?;

println!("Approximation ratio: {:.4}", result.approximation_ratio);

VQC (Variational Quantum Classifier):

• Binary and multi-class classification
• Parameter shift rule for gradients
• Training/test split support

Optimizers: COBYLA, ADAM, L-BFGS-B

4 Implementations:

• CTQW (Continuous-Time Quantum Walk) - Spectral propagator method
• Krylov Methods - Lanczos algorithm for large systems
• Scattering Analysis - Density of states, scattering channels
• Benchmark Suite - Hitting time, mixing time, fidelity

use metatron_qso_rs::quantum_walk::*;

let walk = ContinuousQuantumWalk::new(graph.adjacency_matrix());
let result = walk.evolve(initial_state, time)?;

• Grover Search - Metatron-specific variant
• Boson Sampling - Platonic-solid interference
• Quantum Machine Learning - Graph-structured ML

58.5% information advantage over binary systems:

3 States:

• L+ (active) - High activation
• L- (inactive) - Low activation
• Ld (dynamic/undetermined) - Superposition

Features:

• Kuramoto synchronization networks
• Resonator dynamics
• Tripolar gate operations
• Network coupling

Information Capacity (13 nodes):

• Binary: 13.0 bit
• Tripolar: 20.6 bit (+58.5%)
• With phase: 46.6 bit (+258%)

• G_M Symmetry Group - Metatron-specific symmetries
• Topological Codes - Code distance d ≥ 6
• Error-resistant Operations - Symmetry-protected gates

High-Performance Python Bindings via PyO3

cd metatron_qso_py
pip install maturin
maturin develop --release

• ✅ Python-idiomatic API - dict returns, list parameters
• ✅ Rust performance - Zero-cost bindings
• ✅ Jupyter-ready - Interactive notebooks
• ✅ Type safety - Clear error handling

# Run examples
python metatron_qso_py/examples/01_quantum_walk_basic.py
python metatron_qso_py/examples/02_qaoa_maxcut_basic.py
python metatron_qso_py/examples/03_vqe_ground_state.py

# Jupyter notebook
jupyter notebook metatron_qso_py/notebooks/QuantumWalk_Intro.ipynb

import metatron_qso

# QAOA with automatic calibration
result, proposal = metatron_qso.solve_maxcut_qaoa_with_tuning(
    graph=graph,
    depth=3,
    max_iters=100,
    auto_calibrate=True
)

if proposal.por_accepted:
    print(f"SCS suggests: depth={proposal.config.ansatz_depth}")

Automatic Hyperparameter Optimization for Quantum Algorithms

The SCS is a meta-algorithm for automatic calibration of quantum algorithms. It uses field-theoretic feedback and fixpoint dynamics.

Performance Triplet Φ(c) = (ψ, ρ, ω):

• ψ (Quality) - Algorithm-specific quality
• ρ (Stability) - Robustness across multiple runs
• ω (Efficiency) - Computational efficiency

Mandorla Field M(t):

• 16-dimensional resonance field
• Historical performance patterns
• Guides configuration changes

Double-Kick Operator T = Φ_V ∘ Φ_U:

• Update-Kick Φ_U: Improves quality
• Stabilization-Kick Φ_V: Optimizes stability
• Converges to fixpoint attractors

Proof-of-Resonance (PoR):

• Acceptance criterion for new configurations
• Guarantees monotonic quality improvement
• Validates field resonance

CRI (Calibration Regime Initialization):

• Detects stagnation in local optimum
• Automatically switches to new regime
• Enables global exploration

# Initialize SCS
python -m scs.cli init

# Execute 5 calibration steps
python -m scs.cli step -n 5

# Show status
python -m scs.cli status

# Export best configuration
python -m scs.cli export -o best_config.json

from scs import AutoTuner

tuner = AutoTuner(benchmark_dir="benchmarks", enabled=True)
tuner.initialize()

for iteration in range(10):
    result = run_algorithm()
    metrics = {"psi": 0.85, "rho": 0.80, "omega": 0.72}

    tuner.ingest_benchmark("qaoa", config, metrics, result)
    proposal = tuner.propose_new_config()

    if proposal.por_accepted:
        config = proposal.config

4D-5D Coupling System for Cognitive Quantum Processing

4D-Funnel (Gabriel) ←→ APOLLYON-5D ←→ Infinity-Ledger (MEF)
                               ↓
                     Metatron QSO (via Bridge)

Components:

• Funnel Graph - Directed graph with Hebbian learning
• Hyperbion Layer - Morphodynamic 4D-5D coupling
• HDAG Field - 5D resonance lattice (hyperdimensional acyclic)
• Policies - Explore, exploit, homeostasis

Properties:

• Deterministic: Same inputs → identical outputs
• Proof-carrying: Cryptographic verification
• Coordinate mapping: SCS metrics → 4D state space

Unified 5D Space (x, y, z, ψ, ω):

• x, y, z - Spatial coordinates
• ψ (psi) - Semantic weight / resonance
• ω (omega) - Temporal phase / oscillation

4 Adapters for seamless integration:

• State Adapter - 5D ⟷ Spiral
• Spectral Adapter - Features ⟷ Signature
• Metatron Adapter - Cube-13 ⟷ S7
• Resonance Adapter - Field ⟷ PoR

1. SCS State (ψ, ρ, ω, algorithm) → QDashCalibrationState
2. Bridge Mapping → 4D state space
3. 4D-Funnel Coupling Tick:
   • Lift 4D → 5D
   • Hyperbion absorption
   • HDAG relaxation & gradient
   • Project 5D → 4D
   • Funnel advection
4. Calibration Suggestion generation

• APOLLYON-5D: 109 tests
• Infinity-Ledger: Complete MEF tests
• Bridge: 84 tests (41 for 4D-funnel)

Unified Interface for Multiple Quantum Backends

• Local Simulator (default) - Pure Rust simulation
• IBM Quantum (feature-gated) - IBM Cloud integration
• Extensible for AWS Braket, IonQ, Rigetti

use metatron_backend::*;

// Backend registry
let registry = BackendRegistry::new();

// Local backend
let local = registry.get_backend("local")?;

// Execute circuit
let circuit = Circuit::new(num_qubits);
circuit.add_gate(Gate::H(0));
circuit.add_gate(Gate::CNOT(0, 1));

let result = local.execute(&circuit)?;
println!("Measurements: {:?}", result.measurements);

• Provider Abstraction - Unified API for all backends
• Circuit Representation - Backend-agnostic format
• Registry Pattern - Factory for backend instances
• Feature Gates - Optional IBM/Cloud integration

Real-time Monitoring with HTTP REST API

• REST API - Complete HTTP endpoints
• Real-time Metrics - Live performance tracking
• Historical Data - Persistent storage
• Web Dashboard - Browser-based UI
• Demo Mode - Sample data for testing

cargo run --release --bin metatron_telemetry

🚀 Telemetry server running on http://localhost:3000

Endpoints:
  GET  /health              - Health check
  GET  /api/metrics         - Current metrics
  POST /api/metrics         - Add metric
  GET  /api/metrics/history - Historical data
  GET  /dashboard           - Web dashboard

# Health check
curl http://localhost:3000/health

# Get metrics
curl http://localhost:3000/api/metrics

# Send metric
curl -X POST http://localhost:3000/api/metrics \
  -H "Content-Type: application/json" \
  -d '{"algorithm": "vqe", "energy": -12.9997, "iterations": 150}'

# Open dashboard in browser
open http://localhost:3000/dashboard

Features:

• Live metric visualization
• Algorithm performance charts
• Historical trend analysis
• Export to JSON/CSV

Evolutionary Spiral-Search for SCS Calibration

TRITON uses golden-angle spirals for efficient hyperparameter exploration:

SpectralSignature (ψ, ρ, ω):

• 3D quality metric
• Momentum-based search
• Adaptive step size

use metatron_triton::*;

let search = TritonSearch::new(config_space);
let signature = SpectralSignature::new(0.85, 0.80, 0.72);

let proposal = search.evolve(current_config, signature)?;

if proposal.quality_improved() {
    apply_config(proposal.config);
}

• Golden-angle spirals (φ = 137.5°)
• Momentum-driven evolution
• Calibration proposals
• Integration with SCS

# All unit tests in workspace
cargo test --workspace

# Test specific crate
cargo test -p metatron-qso-rs
cargo test -p metatron_dionice_bridge

# DioniceOS tests
cargo test -p apollyon_5d            # 109 tests
cargo test -p apollyon-mef-bridge    # 84 tests (41 for 4D-funnel)

8 Benchmark Binaries:

# Core benchmarks
cargo run --release --bin quantum_walk_bench
cargo run --release --bin vqe_bench
cargo run --release --bin qaoa_bench
cargo run --release --bin vqc_bench

# Comparison benchmarks
cargo run --release --bin integration_bench
cargo run --release --bin cross_system_bench
cargo run --release --bin advanced_algorithms_bench
cargo run --release --bin benchmark_compare

GitHub Actions with automatic baseline comparison:

• Parallel test execution
• Performance regression detection
• Baseline tracking in metatron-qso-rs/ci/
• Daily performance metrics

• PRODUCT_OVERVIEW.md - Architecture overview
• DIONICEOS_INTEGRATION.md - DioniceOS integration guide
• VQA_IMPLEMENTATION_GUIDE.md - VQA algorithms guide
• QUANTENINFORMATIONSVERARBEITUNG_DOKUMENTATION.md - Quantum info (DE)
• BENCHMARK_SUITE_DOCUMENTATION.md - Benchmark system
• CHANGELOG.md - Version history
• RELEASE_PLAN.md - Packaging strategy
• DEV_SETUP.md - Development setup

• docs/SCS_CORE_DESIGN.md - Architecture & data flow
• docs/SCS_BENCHMARK_SCHEMA.md - JSON schema specification
• docs/SCS_USAGE_GUIDE.md - Workflows & best practices
• docs/seraphic_calibration_shell.md - Overview

• docs/backend_system.md - Backend architecture
• docs/telemetry_and_dashboard.md - Telemetry system
• docs/pyo3_integration.md - Python bindings
• docs/PYTHON_SDK_GUIDE.md - Python API reference
• docs/CI_PIPELINE_OVERVIEW.md - CI/CD pipeline

• docs/dioniceos/README.md - Complete DioniceOS guide
• docs/dioniceos/QUICK_START.md - Quick start

• metatron-qso-rs/docs/ARCHITECTURE.md - Core architecture
• metatron-qso-rs/docs/RUST_CORE_GUIDE.md - Developer guide
• quantum_walk_mixing.md, cross_system_vqe_scoring.md, vqe_tuning.md, vqc_overview.md

• docs/WINDOWS_SETUP.md - Windows 10/11 setup guide (EN) 🔥
• docs/SCHNELLANLEITUNG.md - Quick guide (DE)

# Generate and open rustdoc
cargo doc --open --workspace

• Rust 1.85.0+ (Edition 2021)
• Cargo with workspace support
• Python 3.8+ (for Python SDK)
• Maturin (for Python bindings)

# Build entire workspace
cargo build --release --workspace

# Build individual crate
cargo build --release -p metatron-qso-rs
cargo build --release -p metatron_backend
cargo build --release -p metatron_telemetry

# Build Python SDK
cd metatron_qso_py
maturin develop --release

# Formatting
cargo fmt --all

# Linting
cargo clippy --workspace -- -D warnings

# Python linting
cd scs
ruff check .
ruff format .

metatron-qso-rs Features:

• walks - Quantum walk algorithms
• vqa - Variational quantum algorithms
• dtl - Dynamic tripolar logic
• codes - Symmetry codes
• advanced - Advanced algorithms

metatron_backend Features:

• local (default) - Local simulator
• ibm - IBM Quantum integration
• all-backends - All backends

# Build with specific features
cargo build --release -p metatron-qso-rs --features "walks,vqa,dtl"
cargo build --release -p metatron_backend --features "ibm"

┌─────────────────────────────────────────────────────────────────────┐
│                           Q⊗DASH Workspace                          │
├─────────────────────────────────────────────────────────────────────┤
│                                                                     │
│  ┌──────────────────┐      ┌──────────────────┐                   │
│  │ metatron-qso-rs  │◄────►│ metatron_backend │                   │
│  │  • Quantum Core  │      │  • Local/IBM     │                   │
│  │  • VQA/QAOA/VQC  │      │  • Circuit API   │                   │
│  │  • Quantum Walks │      └──────────────────┘                   │
│  │  • DTL System    │                                             │
│  └────────┬─────────┘                                             │
│           │                                                        │
│           ▼                                                        │
│  ┌──────────────────┐      ┌──────────────────────────┐          │
│  │ metatron_qso_py  │      │ metatron_dionice_bridge  │          │
│  │  • PyO3 Bindings │      │  • 4D-Trichter System    │          │
│  │  • Python API    │◄────►│  • 4D-5D Coupling        │          │
│  │  • Auto-Tuning   │      │  • 4 Adapters            │          │
│  └──────────────────┘      └───────────┬──────────────┘          │
│                                        │                          │
│  ┌──────────────────┐                 ▼                          │
│  │ metatron_triton  │      ┌──────────────────────────┐          │
│  │  • Spiral Search │      │   DioniceOS (18 Crates)  │          │
│  │  • TRITON        │      ├──────────────────────────┤          │
│  └──────────────────┘      │ • apollyon_5d (3)        │          │
│                            │ • infinity-ledger (13)   │          │
│  ┌──────────────────┐      │ • apollyon-mef-bridge    │          │
│  │ metatron_telemetry│      │ • unified_5d_cube        │          │
│  │  • HTTP Server   │      └──────────────────────────┘          │
│  │  • REST API      │                                             │
│  │  • Dashboard     │                                             │
│  └──────────────────┘                                             │
│                                                                     │
│  ┌──────────────────────────────────────────┐                     │
│  │         SCS (Python 12 Modules)          │                     │
│  │  • Calibrator • Field • Operators • PoR  │                     │
│  │  • CRI • CLI • AutoTuner • Benchmark     │                     │
│  └──────────────────────────────────────────┘                     │
└─────────────────────────────────────────────────────────────────────┘

Metatron System (13 nodes):

Binary:             13.0 bit (classical)
Tripolar:           20.6 bit (+58.5%)
Tripolar with phase: 46.6 bit (+258%)

5D State Space: (x, y, z, ψ, ω)

• Semantic dimension: ψ (resonance/weight)
• Temporal dimension: ω (phase/oscillation)

Coupling Operator:

Lift:    4D → 5D  (Hyperbion absorption)
Relax:   5D → 5D  (HDAG gradient descent)
Project: 5D → 4D  (Funnel advection)

Contributions are welcome! Please note:

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Add tests (cargo test --workspace)
4. Check formatting (cargo fmt --all && cargo clippy --workspace)
5. Commit (git commit -m 'Add amazing feature')
6. Push to branch (git push origin feature/amazing-feature)
7. Open pull request

• All new features need tests
• Documentation with rustdoc
• Update benchmark baselines when performance changes
• Add Python examples for new APIs

This project is licensed under the MIT License. See LICENSE for details.

• Sacred Geometry - Metatron's Cube as fundamental structure
• Quantum Computing - VQE/QAOA/VQC research
• Rust Community - nalgebra, petgraph, rayon, pyo3
• DioniceOS - 4D-5D integration framework

• GitHub Issues: https://github.com/LashSesh/qso/issues
• Documentation: See docs/ directory
• Examples: metatron_qso_py/examples/

• Lines of Code: ~8,222 Rust (Core) + ~17,200 Rust (Python bindings) + ~3,204 Python (SCS)
• Test Coverage: 109 tests (APOLLYON-5D) + 84 tests (Bridge) + inline tests
• Workspace Crates: 24 (6 main + 18 DioniceOS)
• Benchmark Suites: 8 executables with CI/CD integration
• Documentation Files: 30+ Markdown files

Made with ❤️ in Rust | Powered by Quantum Geometry | © 2025 Sebastian Klemm (Aion-Chronos; "Sol invictus Mithra")