Quantum-inspired algorithms and the Azure Quantum optimization service

Delbert Murphy joins Scott Hanselman to show how quantum-inspired algorithms mimic quantum physics to solve difficult optimization problems.

Quantum-Inspired optimization (QIO) takes state-of-the-art algorithmic techniques from quantum physics and makes these capabilities available in Azure on conventional hardware, and callable from a Python client. You can use QIO to solve problems with hundreds of thousands of variables, combined into millions of terms, in a few minutes, with this easy-to-consume Azure service.

Time Stamps

  • 0:00 – Introduction
  • 0:40 – What problems can you solve with quantum-inspired optimization?
  • 5:35 – A concrete example: Secret Santa
  • 8:52 – Demo, Part I: Solving Secret Santa with QIO
  • 17:58 – Demo, Part II: Running the code
  • 21:12 – Quantum-inspired algorithms
  • 24:33 – Wrap-up

3 thoughts on “Quantum-inspired algorithms and the Azure Quantum optimization service”

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