qcloud Module

The pyqpanda3.qcloud module provides quantum cloud computing services for submitting quantum programs to OriginQ cloud backends, including simulators, supercomputing clusters, and real quantum processing units (QPUs).

Overview

The qcloud module is the primary interface for interacting with the OriginQ quantum cloud platform. It provides classes for managing cloud services, submitting quantum jobs, retrieving results, and configuring noise models for realistic simulations.

The typical workflow is:

1. Create a QCloudService instance with your API key.
2. List available backends with backends() and select one with backend().
3. Submit quantum programs via QCloudBackend.run().
4. Monitor job status through QCloudJob.
5. Retrieve measurement results from QCloudResult.

Classes

Class	Description
QCloudService	Main entry point for connecting to the quantum cloud platform and managing backends
QCloudBackend	Represents a specific quantum backend (simulator or real chip) for running programs
QCloudJob	Represents a submitted quantum job with methods for status tracking and result retrieval
QCloudResult	Contains the results of a completed quantum job, including probabilities, counts, and amplitudes
QCloudOptions	Configuration options for cloud job execution such as mapping, optimization, and amendment
QCloudNoiseModel	Noise model configuration for cloud-based noisy simulations
ChipInfo	Information about a quantum chip including qubit properties and topology
ChipBackend	Low-level chip backend configuration including topology edges and gate timing
SingleQubitInfo	Properties of a single qubit on a chip (fidelity, T1, T2, frequency)
DoubleQubitsInfo	Properties of a qubit pair (gate fidelity)

Enumerations

Enum	Description
JobStatus	Status of a cloud job (WAITING, COMPUTING, FINISHED, FAILED, QUEUING)
DataFormat	Data format for circuit export (DEFAULT, BINARY, INSTRUCTION_SET)
DataBase	Base representation for measurement results (Binary, Hex)
NOISE_MODEL	Quantum noise model types (bit-flip, damping, decoherence, etc.)
LogLevel	Logging verbosity levels (CLOUD_INFO, CLOUD_DEBUG, CLOUD_WARNING, CLOUD_ERROR)
LogOutput	Log output destination (CONSOLE, FILE)

Quick Start

from pyqpanda3.qcloud import QCloudService, QCloudNoiseModel
from pyqpanda3.core import QCircuit, H, CNOT, measure

# Connect to the cloud service
service = QCloudService(api_key="your_api_key")

# List available backends
backend_names = service.backends()
print("Available backends:", backend_names)

# Select a backend
backend = service.backend("backend_name")

# Create a quantum program
circuit = QCircuit(2)
circuit << H(0) << CNOT(0, 1)
prog = QProg()
prog << circuit << measure([0, 1], [0, 1])

# Run on the backend
job = backend.run(prog, shots=1000)

# Get the result
result = job.result()
probs = result.get_probs()
print("Probabilities:", probs)

See Also

• pilot_service Module -- Lower-level QPilot OS integration