Q-Lab
Q-Lab is a quantum experiment tracking platform designed for research teams. It automatically captures every circuit run across quantum providers such as IBM Quantum, IonQ, Rigetti, and others, with a zero-boilerplate SDK setup. Researchers can track qubits, depth, gates, results, calibration data, and timestamps, ensuring no experiment data is ever lost. The platform provides a central dashboard for circuit analytics, including gate depth trends, entanglement ratios, and health scores. AI Insights, powered by Q-Lab Copilot, allows users to ask questions about their experiments in plain English and surface patterns that might otherwise be overlooked. Real-time collaboration features let teams share projects, annotate runs, and see live updates as teammates push results. Q-Lab also includes a Cost Oracle that shows the exact cost of a circuit run before submission, helping enterprises avoid runaway QPU bills. It supports multiple providers through one SDK and dashboard, with the ability to route workloads to the cheapest provider that meets a specified fidelity target. Publication tools enable researchers to export figures, auto-generate methods sections, and publish reproducible experiment packages to arXiv.
- Category
- Code
- Pricing
- Free
Problem solved
Quantum research teams often struggle with scattered experiment data, hidden provider costs, and difficulty reproducing results. Q-Lab provides automatic experiment tracking, multi-provider comparison, cost estimation, and collaborative reproducibility tools to ensure no result is lost and budgets are predictable.
Use cases
- Track every quantum circuit run automatically from IBM Quantum, IonQ, Rigetti, and more
- Estimate QPU costs before submitting a circuit
- Compare provider pricing and fidelity targets side by side
- Collaborate in real time with research teammates on shared projects
- Analyze gate depth trends and calibration health across experiments
- Ask natural-language questions about historical circuit runs
- Generate publication-ready figures, methods sections, or reproducible packages
Audience
- Researchers
- Developers
- Data Scientists
- Startups
Pros
- One-line SDK auto-tracking works with existing Qiskit or PennyLane workflows
- Integrated cost oracle shows live pricing across multiple quantum providers
- Supports IBM Quantum, IonQ, Rigetti, Azure Quantum, and AWS Braket
- AI Copilot provides natural-language insights on experiment data
- Real-time collaboration and publication tools for research teams
Cons
- Currently in public beta and may not be fully stable
- Requires cloud account and API key for SDK telemetry
- Platform is specialized for quantum experiments, not general ML tracking
- No self-hosted or on-premise option mentioned
- Provider list, while growing, may not include every quantum backend
Official website: https://www.soqlab.com/
Canonical LambdaBase page: https://www.lambdabase.com/tools/q-lab