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Data Analysis and Graphs

The input to the analyzer tool is a quantum program in OpenQasm or Cirq format. The analysis data and graphs can be accessed using Classiq's Python SDK. After synthesizing a quantum program, initialize the Analyzer class using the quantum program returned from the synthesis process.

from classiq import (
from classiq.qmod.quantum_function import QFunc

def main(res: Output[QBit]) -> None:
    allocate(1, res)

model = create_model(main)
qprog = synthesize(model)
analyzer = Analyzer(circuit=QuantumProgram.from_qprog(qprog))

Graphs and Data

Quantum programs are more than just a beautiful image; they are meant to run on real quantum hardware to solve and supply interesting and new answers. The hardware analysis supplies two main insights.

Available Devices

To perform hardware-aware analysis, you may want to know which devices are available using the Classiq Platform. You can get a list of the devices that are both available and suit the quantum program (i.e., have a sufficient number of qubits).


This command returns the available devices of all the providers, in dictionary format, where providers are the keys, and lists of available devices are the values:

    "IBM Quantum": [
    "Azure Quantum": ["ionq", "quantinuum"],

You can also request the devices of a specific provider:

analyzer.get_available_devices(["IBM Quantum"])

Hardware-Circuit Connection

The Hardware-Circuit Connection graph is a representation of a quantum program as implemented on a specific (physical) quantum device. You can interactively select hardware from hardware providers such as IBM Quantum, Amazon Braket, and Microsoft Azure. The analyzer compiles the quantum program for the selected hardware, allowing easy inspection of which physical qubits will be used for execution on the device and, in turn, modifying the quantum program if needed. This information is important if you want to execute the quantum program on real quantum hardware, so you can make modifications to the quantum program.

This graph is accessible from the SDK only if you install the analyzer_sdk extension with the pip install classiq[analyzer_sdk] command and use Jupyter as your coding platform. Once the extension is installed, run this command:

# Run inside jupyter


Alternatively, you can open the graph directly with a specific provider and device:

analyzer.plot_hardware_connectivity(provider="IBM Quantum", device="washington")

Hardware Comparison Table

The hardware comparison table compares the transpiled quantum program on different hardware backends. The table includes information about the quantum program's depth, number of multi-qubit gates, and total number of gates.

providers = ["IBM Quantum", "Azure Quantum", "Amazon Braket"]
analyzer = Analyzer(circuit=GeneratedCircuit.from_qprog(qprog))

The providers variable is a list of providers ("IBM Quantum", "Azure Quantum", and "Amazon Braket"), where the table includes only the backends of providers that appear in the list, and the default is to use all the providers. The table has the following form:


Sort the table according to the table properties using the dropdown button on the upper left of the table. ```


Using the default device/providers option (all) or comparing a large number of devices might take a long time, especially when analyzing large quantum programs. It is advised to compare a small number of devices when you are interested in analyzing large quantum programs.


The difference between the transpilation in the synthesis process and the comparison table data originates from the fact that the comparison table data is aware of the specific hardware and considers information such as the basis gates and connectivity.

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[2] S. Oum, "Rank-width: Algorithmic and structural results", Lect. Notes Comput. Sci. 3787, 49 (2005).

[3] S. Oum, "Rank-width is less than or equal to branch-width", J. Graph Theory, 57 (3), 239-244 (2008).

[4] Hans L. Bodlaender, "Discovering treewidth". Institute of Information and Computing Sciences, Utrecht University, Technical Report. UU-CS-2005-018.