https://github.com/qbraid/qbraid-lab-demo

Notebooks demonstrating how to use qBraid Lab to streamline quantum workflows, connect to quantum hardware, and leverage GPU-enabled scalable compute for hybrid algorithms.
https://github.com/qbraid/qbraid-lab-demo

ipython quantum quantum-algorithms quantum-circuit quantum-computing

Last synced: 24 days ago
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Notebooks demonstrating how to use qBraid Lab to streamline quantum workflows, connect to quantum hardware, and leverage GPU-enabled scalable compute for hybrid algorithms.

• Host: GitHub
• URL: https://github.com/qbraid/qbraid-lab-demo
• Owner: qBraid
• License: apache-2.0
• Created: 2022-01-28T18:20:24.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2024-07-11T02:47:22.000Z (4 months ago)
• Last Synced: 2024-10-12T11:21:40.957Z (24 days ago)
• Topics: ipython, quantum, quantum-algorithms, quantum-circuit, quantum-computing
• Language: Jupyter Notebook
• Homepage: https://www.qbraid.com
• Size: 2.72 MB
• Stars: 31
• Watchers: 3
• Forks: 13
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# qBraid Lab Demos

[](https://account.qbraid.com?gitHubUrl=https://github.com/qBraid/qbraid-lab-demo.git)

qBraid is a cloud-based platform for quantum computing.

This repository provides demos and tutorials on using the [qBraid SDK](https://github.com/qBraid/qBraid), [qBraid CLI](https://docs.qbraid.com/projects/cli/en/latest/cli/qbraid.html), and qBraid Lab features including [Quantum Jobs](https://docs.qbraid.com/projects/lab/en/latest/lab/quantum_jobs.html), and [GPUs](https://docs.qbraid.com/projects/lab/en/latest/lab/gpu.html).

For more resources and reference material, see [qBraid Docs](https://docs.qbraid.com/en/latest/).