marlinspike/azure-quantum-gov

Exploring Azure Quantum

This repository contains sample code that allows you to run quantum programs on Azure Quantum.

Creating the Environment file (.env)

The following environment variables are required to run the sample, which should be placed in a file named .env in the root directory of the sample.

resource_id="/subscriptions/xxxx-xxx-xx-xx-xxx/resourceGroups/AzureQuantum/providers/Microsoft.Quantum/Workspaces/rcQuantum"
location="East US"
account_url="https://xxxx.blob.core.windows.net"
storage_account_key="xxxx"
file_dir="output"
quantum_target="ionq.simulator"

Here is a description of each variable:

resource_id: The resource id of the Azure Quantum workspace
location: The location of the Azure Quantum workspace
account_url: The url of the Azure Storage account
storage_account_key: A valid key for the Azure Storage account
file_dir: The container in the Azure Storage account where the output files will be stored
quantum_target: The target to run the quantum program on
azure_login_cmd : The command to login to Azure Commercial. This is used to authenticate to Azure Quantum. This is only required ifyou're running the sample in a container.

Creating the JSON properties file

There are some issues with passing an env file via Docker's --env-file flag, so we'll use a JSON properties file instead. The following environment variables are required to run the sample, which should be placed in a file named env.json in the root directory of the sample.

Use the output of the Create Service Pricipal Step below to populate the azure_login_cmd property.

{
    "resource_id": "/subscriptions/xxxx-xxx-xx-xx-xxx/resourceGroups/AzureQuantum/providers/Microsoft.Quantum/Workspaces/rcQuantum",
    "location": "East US",
    "account_url": "https://xxxx.blob.core.windows.net",
    "storage_account_key": "xxxx",
    "file_dir": "output",
    "quantum_target": "ionq.simulator",
     "azure_login_cmd" : "az login --service-principal -u xx -p xx --tenant xx"
}

The app reads from this file. A future version will allow you to pass certain properties via env variables as well.

Create a Service Principal in Azure Commercial, which will be used to authenticate to Azure Quantum

 az ad sp create-for-rbac --name "rc-az-quantum" --sdk-auth --role contributor --scopes /subscriptions/xxx/resourceGroups/AzureQuantum

Your output should look like this:

{
  "clientId": "xxx",
  "clientSecret": "xxx",
  "subscriptionId": "xxx",
  "tenantId": "xxx",
  "activeDirectoryEndpointUrl": "https://login.microsoftonline.com",
  "resourceManagerEndpointUrl": "https://management.azure.com/",
  "activeDirectoryGraphResourceId": "https://graph.windows.net/",
  "sqlManagementEndpointUrl": "https://management.core.windows.net:8443/",
  "galleryEndpointUrl": "https://gallery.azure.com/",
  "managementEndpointUrl": "https://management.core.windows.net/"
}

Copy the output of the command, as you'll need it when you create the env.json file, specifically, the azure_login_cmd property.

Running the sample from the command line

python3 main.py

Build the container to run the sample

docker build -t quant-sim:1 .

If you're running on a Mac with an M1 chip, you'll may need to build the container for the ARM64 architecture if you want to run it on a Linux host:

docker build --platform linux/amd64 -t quant-sim:1 .

Running the container

docker run --rm  quant-sim:1

The --rm flag will remove the container after it exits.

You should see the following output:

This workspace's targets:
- ionq.qpu
- ionq.qpu.aria-1
- ionq.simulator
- quantinuum.hqs-lt-s1
- quantinuum.hqs-lt-s1-apival
- quantinuum.hqs-lt-s2
- quantinuum.hqs-lt-s2-apival
- quantinuum.hqs-lt-s1-sim
- quantinuum.hqs-lt-s2-sim
- quantinuum.qpu.h1-1
- quantinuum.sim.h1-1sc
- quantinuum.qpu.h1-2
- quantinuum.sim.h1-2sc
- quantinuum.sim.h1-1e
- quantinuum.sim.h1-2e
Job id: 47cee0ea-073b-11ee-a6b6-56bf2ceda040
Awaiting job results...
Job finished. State probabilities:
0: 0.5
1: 0.5
{'etag': '"0x8DB695F3176E6E3"', 'last_modified': datetime.datetime(2023, 6, 10, 3, 2, 57, tzinfo=datetime.timezone.utc), 'content_md5': bytearray(b',\x80\xba\x1e\x1b)8X\xda\xee\xf5\x1f\x07^\x87H'), 'client_request_id': '4c1f2d58-073b-11ee-a6b6-56bf2ceda040', 'request_id': '859f2ba8-e01e-0014-0948-9be452000000', 'version': '2022-11-02', 'version_id': None, 'date': datetime.datetime(2023, 6, 10, 3, 2, 56, tzinfo=datetime.timezone.utc), 'request_server_encrypted': True, 'encryption_key_sha256': None, 'encryption_scope': None}
Axes(0.125,0.11;0.775x0.77)

You'll also notice that a file with the same name as the Job ID was created in the output container in the Azure Storage account. That's the output of the quantum program.

marlinspike / azure-quantum-gov