Quantum Control Plane

Quantum Control Plane (QCP)

The Quantum Control Plane (QCP) is an open-source developer platform tailored for quantum computing. It enables users to submit QASM circuits, orchestrate multi-step experiments, benchmark different quantum providers, and visualize results efficiently. This platform is akin to tools like MLflow and Airflow, but specifically designed for the nuances of quantum technology.

Platform Overview

The architecture of the platform is organized into distinct layers:

┌──────────────────────────────────────────────────────┐
│  Developer Platform: SDK · CLI · REST API (/v1/)     │
├──────────────────────────────────────────────────────┤
│  Control Plane: Experiments · Workflows · Cost Gov   │
├──────────────────────────────────────────────────────┤
│  Execution Plane: Workers · Providers · Simulators   │
├──────────────────────────────────────────────────────┤
│  Dashboard: Experiments · Leaderboard · Demo · Runs  │
└──────────────────────────────────────────────────────┘

Key Features

• API Integration: Establish seamless integrations using the FastAPI framework, facilitating the management of experiments and workflows while ensuring cost governance.
• Execution Flexibility: Utilize asynchronous workers, provider adapters, and simulators to execute quantum jobs efficiently.
• Developer Tools: Leverage the Python SDK and CLI tools for straightforward interaction with the platform.
• Interactive Dashboard: Access a Next.js-based web console for monitoring experiments, viewing leaderboards, and running demos.

Example Use Cases and Experiments

The platform supports various quantum experiments, including:

• Bell State: Achieves maximal entanglement between two qubits using Hadamard and CNOT gates.
• GHZ State: Extends entanglement concepts to three qubits, showcasing genuine multipartite entanglement.
• Grover's Algorithm: Demonstrates quantum search capabilities on a small dataset, highlighting quadratic speedup compared to classical approaches.

Developer and API Access

The platform provides comprehensive capabilities for developers:

Python SDK Example:

from quantum_sdk import QCPClient

client = QCPClient(api_key="qcp_...")
job = client.run_experiment(
    name="bell",
    qasm=open("bell.qasm").read(),
    shots=1024,
)
result = client.wait_for_result(job["job"]["id"])
print(result["result"]["counts"])

CLI Commands:

qcp login
qcp experiment run bell.qasm --provider local_simulator
qcp experiment list

REST API Endpoints include:

• POST /v1/api-keys: For creating new API keys.
• POST /v1/experiments: To submit a new experiment.
• GET /v1/results/{id}: To retrieve results for a specific job.

Development Tools

QCP offers robust development support through Makefile targets, including:

• make lint: Runs code linters to maintain code quality.
• make test: Executes unit tests to ensure functionality.

Documentation and Community Support

For further guidance, detailed documentation covering different aspects such as getting started, architecture, and specific guides are readily available, ensuring a smooth onboarding process for all users.

• Getting Started
• Contributing

The Quantum Control Plane is set to empower developers and researchers in the burgeoning field of quantum computing by providing the tools required to innovate and explore the quantum landscape.