iqm.benchmarks.entanglement.graph_states.shadow_tomography_analysis

iqm.benchmarks.entanglement.graph_states.shadow_tomography_analysis#

iqm.benchmarks.entanglement.graph_states.shadow_tomography_analysis(dataset: Dataset, all_qubit_pairs_per_group: dict[int, list[tuple[int, int]]], all_qubit_neighbors_per_group: dict[int, list[list[int]]], all_unprojected_qubits: dict[int, list[int]], backend_name: str, execution_timestamp: str) → tuple[dict[str, Any], list[BenchmarkObservation], dict[str, dict[str, str | float]], Dataset]#

Performs shadow tomography analysis on the given dataset.

Parameters:

  • dataset (Dataset) – The dataset containing the experimental data.

  • all_qubit_pairs_per_group (dict[int, list[tuple[int, int]]]) – mDictionary mapping group indices to lists of qubit pairs.

  • all_qubit_neighbors_per_group (dict[int, list[list[int]]]) – Dictionary mapping group indices to lists of neighbor qubit groups.

  • all_unprojected_qubits (dict[int, list[int]]) – Dictionary mapping group indices to lists of unprojected qubits.

  • backend_name (str) – The name of the backend used for the experiment.

  • execution_timestamp (str) – The timestamp of the experiment execution.

Returns:

  • A dictionary of plots.

  • A list of benchmark observations.

  • A dictionary of maximum negativities.

  • The updated dataset.

Return type:

A tuple containing

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