Solve optimization problems by using quantum-inspired optimization
Learn how quantum-inspired algorithms mimic quantum physics to solve difficult optimization problems.
Learning objectives
In this module, you'll:
- Learn about the origins of quantum-inspired algorithms.
- See which kinds of problems are best suited to this method.
- Understand how algorithms inspired by physical processes are used to solve difficult problems.
- Solve a combinatorial optimization problem by using the Azure Quantum optimization service.
Prerequisites
- The latest version of the Python SDK for Azure Quantum
- Jupyter Notebook
- An Azure Quantum workspace
If you don't have these tools yet, we recommend that you begin with the Get started with Azure Quantum module.