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API Reference: qbraid.runtime.origin

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Overview

The qbraid.runtime.OriginProvider provides support for OriginQ’s quantum computing systems through the OriginQ QCloud platform. This means you can write quantum programs using PyQPanda3, and run them on OriginQ’s cloud-based simulators and quantum processors, all from within the qBraid Runtime framework.

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Getting started

Before you begin, make sure you have:
  1. An OriginQ QCloud account and API key.
  2. Python >= 3.10

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Set up the qBraid-SDK

Install qBraid with the origin extra from PyPI using pip: 
pip install 'qbraid[origin]'
This installs the required dependency: pyqpanda3.
Note: The qBraid-SDK requires Python 3.10 or greater. You can check your Python version by running python --version from the command line.

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Authentication

By default, qBraid will look for an environment variable named ORIGIN_API_KEY. Set it from your command line: 
export ORIGIN_API_KEY="your_api_key_here"
Alternatively, you can pass your API key directly when creating the provider: 
from qbraid.runtime.origin import OriginProvider

provider = OriginProvider(api_key="your_api_key_here")
In the examples below, we initialize OriginProvider() with no arguments and assume that qBraid will automatically find your API key from the environment.

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List available devices

Use the OriginProvider to list all devices to which you have access: 
from qbraid.runtime.origin import OriginProvider

provider = OriginProvider()

devices = provider.get_devices()
print(devices)
You can also filter to show only hardware (QPU) devices: 
devices = provider.get_devices(hardware_only=True)
Get a specific device by its ID: 
device = provider.get_device("full_amplitude")

print(device.status())
# <DeviceStatus.ONLINE>

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Available simulators

OriginQ provides several cloud-based quantum simulators:
Simulator IDMax QubitsDescription
full_amplitude35Full amplitude simulation.
partial_amplitude68Partial amplitude simulation.
single_amplitude200Single amplitude simulation.

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Submitting jobs

The OriginProvider accepts quantum programs as PyQPanda3 QProg objects.

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Create a program

from pyqpanda3.core import QProg, H, CNOT, measure

# Bell state circuit
prog = QProg(2)
q = prog.qubits()
prog << H(q[0]) << CNOT(q[0], q[1]) << measure(0, 0) << measure(1, 1)

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Run a job

Use device.run() to submit a program: 
from pyqpanda3.core import QProg, H, CNOT, measure
from qbraid.runtime.origin import OriginProvider

provider = OriginProvider()
device = provider.get_device("full_amplitude")

prog = QProg(2)
q = prog.qubits()
prog << H(q[0]) << CNOT(q[0], q[1]) << measure(0, 0) << measure(1, 1)

job = device.run(prog, shots=1000)
print(f"Job ID: {job.id}")

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Batch submission

Submit multiple programs in a single call: 
from pyqpanda3.core import QProg, H, X, measure
from qbraid.runtime.origin import OriginProvider

provider = OriginProvider()
device = provider.get_device("full_amplitude")

prog1 = QProg(1)
prog1 << H(prog1.qubits()[0]) << measure(0, 0)

prog2 = QProg(1)
prog2 << X(prog2.qubits()[0]) << measure(0, 0)

jobs = device.run([prog1, prog2], shots=500)
for job in jobs:
    print(f"Job ID: {job.id}")
For simulator backends, batch inputs are submitted as individual jobs. For QPU backends, batch inputs are submitted as a single job using the native batch API.

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Retrieving results

result = job.result()

# Measurement probabilities
print(result.data.get_probabilities())
# {'00': 0.5, '11': 0.5}

# Measurement counts (when available)
print(result.data.measurement_counts)

# Job metadata
print(f"Device: {result.device_id}")
print(f"Job ID: {result.job_id}")
print(f"Success: {result.success}")
Depending on the backend, results may be returned as probabilities, measurement counts, or both. Use result.data.get_probabilities() to retrieve probability distributions and result.data.measurement_counts for shot-based counts.

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Check job status

from qbraid.runtime.enums import JobStatus

status = job.status()
print(status)
# <JobStatus.COMPLETED>
Job cancellation is not supported by the OriginQ provider. Calling job.cancel() will raise an error.

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Full example

A complete end-to-end workflow targeting the full amplitude simulator: 
import os
from pyqpanda3.core import QProg, H, CNOT, measure
from qbraid.runtime.origin import OriginProvider

# 1. Set credentials (or export as env var beforehand)
os.environ["ORIGIN_API_KEY"] = "your_api_key_here"

# 2. Initialize provider
provider = OriginProvider()

# 3. Get the target device
device = provider.get_device("full_amplitude")
print(f"Device status: {device.status()}")

# 4. Define a GHZ state circuit
prog = QProg(3)
q = prog.qubits()
prog << H(q[0]) << CNOT(q[0], q[1]) << CNOT(q[1], q[2])
prog << measure(0, 0) << measure(1, 1) << measure(2, 2)

# 5. Submit the job
job = device.run(prog, shots=1000)
print(f"Submitted job: {job.id}")

# 6. Retrieve results
result = job.result()
print(f"Probabilities: {result.data.get_probabilities()}")
# Expected output (approximate): {'000': 0.5, '111': 0.5}