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Modified README.md to reflect EL contribution + changed Azure backend…
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KilianPoirier committed Oct 25, 2023
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11 changes: 6 additions & 5 deletions samples/azure-quantum/qaoa/README.md
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---
page_type: sample
author:
description: Introduction to RQAOA using the OpenQAOA library.
author: KilianPoirier
description: Introduction to QAOA using the OpenQAOA library.
ms.author:
ms.date:
languages:
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# 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 for a specific problem instance (TO SPECIFY) as well as a general QUBO problem that can be taylored to more specific cases like graph coloring or minimum vertex cover.
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.ipynb) Python notebook demonstrating how to run RQAOA 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/
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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6 changes: 3 additions & 3 deletions samples/azure-quantum/qaoa/openqaoa.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 5: Running on Azure devices\n",
"### Step 5: Running on Azure Quantum backend\n",
"\n",
"Now that we have demonstrated how to create a problem, configure the QAOA model, compile and access the opimization results, we will show how to execute the circuit using Azure Quantum backend."
]
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"cell_type": "markdown",
"metadata": {},
"source": [
"Job submission to the Azure backend is made internally in the optimization loop in OpenQAOA. You can submit Jobs one at a time using the optimization loop or group them with the help of the Azure Session feature.\n",
"Job submission to the Azure Quantum backend is made internally in the optimization loop in OpenQAOA. You can submit Jobs one at a time using the optimization loop or group them with the help of the Azure Quantum Session feature.\n",
"\n",
"This cell can take a few minutes to execute (note that executing on real QPUs can take longer run time)."
]
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}
],
"source": [
"# Job submission to Azure Quantum is done internally\n",
"# Job submission to Azure Quantum backend is done internally\n",
"# q_qpu.optimize()\n",
"\n",
"# Jobs can also be grouped using Azure sessions\n",
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