iqm.benchmarks.entanglement.ghz.GHZBenchmark

class iqm.benchmarks.entanglement.ghz.GHZBenchmark(backend: IQMBackendBase, configuration: GHZConfiguration)

Bases: Benchmark

The GHZ Benchmark estimates the quality of generated Greenberger–Horne–Zeilinger states

Attributes

name

Methods

add_configuration_to_dataset(dataset)	Creates a xarray.Dataset and adds the circuits and configuration metadata to it.
analysis_function(run)	Analyze counts and compute the state fidelity
execute(backend)	Executes the benchmark.
generate_coherence_meas_circuits(...)	Takes a given GHZ circuit and outputs circuits needed to measure fidelity via mult.
generate_native_ghz(qubit_layout, ...)	Generate a circuit preparing a GHZ state, according to a given routine and transpiled to the native gate set and topology.
generate_readout_circuit(qubit_layout, ...)	A wrapper for the creation of different circuits to estimate the fidelity

Parameters:

• backend (IQMBackendBase) –

• configuration (GHZConfiguration) –

static analysis_function(run: BenchmarkRunResult) → BenchmarkAnalysisResult

Analyze counts and compute the state fidelity

Parameters:

run (BenchmarkRunResult) – RunResult The RunResult object containing a dataset with counts and benchmark parameters

Returns:

AnalysisResult

An object containing the dataset, plots, and observations

Return type:

BenchmarkAnalysisResult

generate_native_ghz(qubit_layout: List[int], qubit_count: int, routine: str) → CircuitGroup

Generate a circuit preparing a GHZ state, according to a given routine and transpiled to the native gate set and topology.

Parameters:

• qubit_layout (List[int]) – List[int] The subset of system-qubits used in the protocol, indexed from 0

• qubit_count (int) – int The number of qubits for which a GHZ state should be created. This values should be smaller or equal to the number of qubits in qubit_layout

• routine (str) – str The routine to generate the GHZ circuit

Returns:

QuantumCircuit implementing GHZ native state

Return type:

CircuitGroup

generate_coherence_meas_circuits(qubit_layout: List[int], qubit_count: int) → List[IQMCircuit]

Takes a given GHZ circuit and outputs circuits needed to measure fidelity via mult. q. coherences method

Parameters:

• qubit_layout (List[int]) – List[int] The subset of system-qubits used in the protocol, indexed from 0

• qubit_count (int) – int The number of qubits for which a GHZ state should be created. This values should be smaller or equal to the number of qubits in qubit_layout

Returns:

List[QuantumCircuit]

A list of transpiled quantum circuits to be measured

Return type:

qc_list_transpiled

generate_readout_circuit(qubit_layout: List[int], qubit_count: int) → CircuitGroup

A wrapper for the creation of different circuits to estimate the fidelity

Parameters:

• qubit_layout (List[int]) – List[int] The subset of system-qubits used in the protocol, indexed from 0

• qubit_count (int) – int The number of qubits for which a GHZ state should be created. This values should be smaller or equal to the number of qubits in qubit_layout

Returns:

List[QuantumCircuit]

A list of transpiled quantum circuits to be measured

Return type:

all_circuits_list

add_configuration_to_dataset(dataset: Dataset)

Creates a xarray.Dataset and adds the circuits and configuration metadata to it.

Parameters:

dataset (xr.Dataset) –

Returns:

dataset to be used for further data storage

Return type:

xr.Dataset

execute(backend) → Dataset

Executes the benchmark.

Return type:

Dataset