API Reference: qbraid.runtime.native

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Installation & Setup

To interface with the qBraid QIR simulator or any of the 10+ quantum devices supported by qBraid’s managed access, install the relevant qbraid runtime extra(s) based on your device(s) of choice: 
pip install 'qbraid[qir]'     # qBraid QIR Simulator
pip install 'qbraid[pyqubo]'  # NEC Vector Annealer
pip install 'qbraid[quera]'   # QuEra QASM Simulator
pip install 'qbraid[ionq]'    # IonQ Simulator and QPUs
pip install 'qbraid[braket]'  # AWS SV1, DM1, TN1, and QuEra Aquila
pip install 'qbraid[azure]'   # Pasqal Emulator, Fresnal, and Quantinuum H1-1 Emulator, Syntax checker, and QPU
pip install qbraid            # Default installation for all other devices
Next, obtain your qBraid API key:
  1. Login or create an account at account.qbraid.com.
  2. Copy your API Key from the Plan info card on the left side of your account page.
See also: Account - API Keys

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Save account to disk

Once you have your API key, you can save it locally in a configuration file ~/.qbraid/qbraidrc, where ~ corresponds to your home ($HOME) directory:
Account credentials are saved in plain text, so only do so if you are using a trusted device.
from qbraid.runtime import QbraidProvider

provider = QbraidProvider(api_key='API_KEY')
provider.save_config()
Once the account is saved on disk, you can instantiate the provider without any arguments: 
provider = QbraidProvider()

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Load account from environment variables

Alternatively, the qBraid-SDK can discover credentials from environment variables: 
export QBRAID_API_KEY='QBRAID_API_KEY'

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Basic Usage

Given a qbraid_id, a QbraidDevice object can be created as follows: 
from qbraid import QbraidProvider

provider = QbraidProvider()
provider.get_devices()
# [<qbraid.runtime.native.device.QbraidDevice('qbraid_qir_simulator')>]

device = provider.get_device('qbraid_qir_simulator')

type(device)
# <class 'qbraid.runtime.native.device.QbraidDevice'>
From here, class methods are available to get information about the device, execute quantum programs, access the wrapped device object directly, and more. 
device.metadata()
# {'device_id': 'qbraid_qir_simulator',
#  'device_type': 'SIMULATOR',
#  'num_qubits': 64,
#  'status': 'ONLINE',
#  'queue_depth': 0}
Then you can submit quantum jobs to the device. 
run_input = [qiskit_circuit, braket_circuit, cirq_circuit, qasm3_str]

jobs = device.run(run_input, shots=100)

results = [job.result() for job in jobs]

print(results[0].data.get_counts())
# {'00': 50, '01': 2, '10': 47, '11': 1}
See how to visualize these results in the Visualization section.