iqm.benchmarks.optimization.qscore

Qscore benchmark

Functions

calculate_optimal_angles_for_QAOA_p1(graph)	Calculates the optimal angles for single layer QAOA MaxCut ansatz.
compute_expectation_value(counts, graph, ...)	Computes expectation value based on measurement results.
create_objective_function(counts, graph, ...)	Creates a function that maps the parameters to the parametrized circuit, runs it and computes the expectation value.
cut_cost_function(x, graph)	Returns the number of cut edges in a graph (with minus sign).
is_successful(approximation_ratio)	Check whether a Q-score benchmark returned approximation ratio above beta*, therefore being successful.
plot_approximation_ratios(nodes, beta_ratio, ...)	Generate the figure of approximation ratios vs number of nodes,
qscore_analysis(run)	Analysis function for a QScore experiment
run_QAOA(counts, graph_physical, qubit_node, ...)	Solves the cut size of MaxCut for a graph using QAOA.

Classes

QScoreBenchmark(backend_arg, configuration)	Q-score estimates the size of combinatorial optimization problems a given number of qubits can execute with meaningful results.
QScoreConfiguration(*, benchmark, shots, ...)	Q-score configuration.

Inheritance