genpark-quantum-gate-hadamard-pauli-cnot-engine-skill

⚡ Overview & Architectural Significance

genpark-quantum-gate-hadamard-pauli-cnot-engine-skill delivers zero-dependency quantum circuit simulation, qubit state vector evolution, Born-rule measurement, and Grover amplitude amplification engineered strictly using Python 3.9+ standard library.

🌟 Key Architectural Capabilities

• Zero External Dependencies: Operates exclusively via pure Python (math, cmath, random, json). Zero Qiskit/Cirq C++ compilation overhead.

• Enterprise Quantum Invariants: Implements formal complex state vectors, unitary Hadamard and CNOT entanglement gates, Born rule projective measurement sampling, EPR Bell state generation, and Grover diffusion operators.

• Native Anthropic MCP Protocol: Compliant with standard JSON-RPC 2.0 stdio MCP specifications for Claude Desktop, Cursor, and Windsurf.

Related MCP server: genpark-quantum-gate-hadamard-pauli-cnot-engine-skill

🏗️ Architectural Topology & State Machine

flowchart TD
    InitialRegister["Qubit Register |0...0>"] --> GateLayer["Unitary Gate Operations (H, Pauli, Phase)"]
    GateLayer --> EntanglementGate["Two-Qubit Entangling CNOT Gate"]
    EntanglementGate --> GroverOracle["Phase Inversion & Grover Diffusion"]
    GroverOracle --> ProjectiveMeasurement["Born's Rule Collapse & Shot Sampler"]
    ProjectiveMeasurement --> QuantumTelemetry["Classical Quantum Bitstring Telemetry"]

🚀 Quickstart & Standalone Execution

Local Python Client Usage

from client import QuantumGateEngine

# Initialize engine
engine = QuantumGateEngine()

# Execute self-testing benchmark suite
result = engine.benchmark_quantum_gates()
print("Execution Result:", result)

🔌 One-Click MCP Integration (Claude Desktop / Cursor)

Add to your claude_desktop_config.json or cursor.json:

{
  "mcpServers": {
    "genpark-quantum-gate-hadamard-pauli-cnot-engine-skill": {
      "command": "python",
      "args": ["-u", "/path/to/genpark-quantum-gate-hadamard-pauli-cnot-engine-skill/mcp_server.py"]
    }
  }
}

📦 Smithery.ai & PyPI Deployment

This skill contains pre-configured smithery.yaml and pyproject.toml manifests. Install directly via pip:

pip install git+https://github.com/alphaparkinc/genpark-quantum-gate-hadamard-pauli-cnot-engine-skill.git