iqm.benchmarks.optimization.qscore.run_qaoa

iqm.benchmarks.optimization.qscore.run_qaoa(counts: dict[str, int], graph_physical: Graph, qubit_node: dict[int, int], use_classical_angles: bool, qaoa_layers: int, virtual_nodes: list[tuple[int, int]]) → float

Solves the cut size of MaxCut for a graph using QAOA. The result is sampled from the optimized ansatz.

Parameters:

• counts (dict[str, int]) – Key as bitstring, value as counts

• graph_physical (Graph) – The graph to be optimized

• qubit_node (dict[int, int]) – The qubit to be optimized

• use_classical_angles (bool) – Whether to use classical angles

• qaoa_layers (int) – The number of QAOA layers

• virtual_nodes (list[tuple[int, int]]) – The presence of virtual nodes or not

Returns:

The expectation value of the maximum cut size.

Return type:

float