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8 changes: 8 additions & 0 deletions binder-index.md
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<td><strong><a href="./samples/azure-quantum/openqaoa/README.md">Quantum Approximate Optimization Algorithm</a></strong></td>
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<td><a href="./samples/azure-quantum/openqaoa/openqaoa.ipynb">Python</a></td>
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page_type: sample
author: KilianPoirier
description: Introduction to QAOA using the OpenQAOA library.
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languages:
- python
products:
- azure-quantum
---

# Solving Quadratic Unconstrained Binary Optimization (QUBO) problems using QAOA on Azure Quantum

This sample shows how to solve quadratic unconstrained binary optimization problems using the Quantum Approximate Optimization Algorithm (QAOA) on the Azure Quantum service. It demonstrates how to operate the QAOA workflow with a readily available problem instance (Maximum Cut) as well as a general QUBO problem that can be taylored to other combinatorial problems like graph coloring or minimum vertex cover.

## Manifest

- [openqaoa.ipynb](./openqaoa.ipynb) Python notebook demonstrating how to run QAOA locally and on the Azure Quantum platform using the OpenQAOA package.
- [openqaoa-recursive.ipynb](./openqaoa-recursive.ipynb) Python notebook demonstrating how to run RQAOA locally and on the Azure Quantum platform using the OpenQAOA package.

## See Also

To learn more about QAOA and how to solve QUBO problems using OpenQAOA, visit https://openqaoa.entropicalabs.com/
This sample code and notebooks were written by members of Entropica Labs team.
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