iqm.benchmarks.entanglement.graph_states.plot_max_negativities_graph#
- iqm.benchmarks.entanglement.graph_states.plot_max_negativities_graph(negativities: Dict[str, Dict[str, str | float]], backend_coupling_map: CouplingMap, qubit_names: Dict[int, str], timestamp: str, tomography: Literal['shadow_tomography', 'state_tomography'], station: str | None = None, num_shots: int | None = None, num_bootstraps: int | None = None, num_RM_samples: int | None = None, num_MoMs_samples: int | None = None) Tuple[str, Figure] #
Plots the maximum negativity for each corresponding pair of qubits in a graph layout of the given backend.
- Parameters:
negativities (Dict[str, Dict[str, str | float]]) – A dictionary (str qubit keys) of dictionaries (keys “value”/”uncertainty”) of negativities (float) to plot.
backend_coupling_map (CouplingMap) – The CouplingMap instance.
qubit_names (Dict[int, str]) – A dictionary of qubit names corresponding to qubit indices.
timestamp (str) – The timestamp of the corresponding experiment.
tomography (Literal["shadow_tomography", "state_tomography"]) – The type of tomography that was used.
station (str) – The name of the station to use for the graph layout.
num_shots (Optional[int]) – The number of shots used in the corresponding experiment. * Defaults to None: won’t be displayed in title.
num_bootstraps (Optional[int]) – The number of bootstraps used if tomography corresponds to state tomography. * Defaults to None if the tomography type is “shadow_tomography”.
num_RM_samples (Optional[int]) – The number of randomized measurement samples used if tomography corresponds to shadow tomography. * Defaults to None if the tomography type is “state_tomography”.
num_MoMs_samples (Optional[int]) – The number of Median of Means samples per randomized measurement used if tomography corresponds to shadow tomography. * Defaults to None if the tomography type is “shadow_tomography”.
- Returns:
The figure label and the max negativities plot figure.
- Return type:
Tuple[str, Figure]