qrisp.qaoa.QAOAProblem.run#

QAOAProblem.run(qarg, depth, mes_kwargs={}, max_iter=50, init_type='random', optimizer='COBYLA')[source]#

Run the specific QAOA problem instance with given quantum arguments, depth of QAOA circuit, measurement keyword arguments (mes_kwargs) and maximum iterations for optimization (max_iter).

Parameters:

qargQuantumVariable or QuantumArray: The quantum argument to which the QAOA circuit is applied.
depthint: The amount of QAOA layers.
mes_kwargsdict, optional: The keyword arguments for the measurement function. Default is an empty dictionary.
max_iterint, optional: The maximum number of iterations for the optimization method. Default is 50.
init_typestring, optional: Specifies the way the initial optimization parameters are chosen. Available are random and tqa. The default is random: The parameters are initialized uniformly at random in the interval \([0,\pi/2]\). For tqa, the parameters are chosen based on the Trotterized Quantum Annealing protocol. If tqa is chosen, and no init_function for the QAOAProblem is specified, the \(\ket{-}^n\) state is prepared (the ground state for the X mixer).
optimizerstr, optional: Specifies the optimization routine. Available are, e.g., COBYLA, COBYQA, Nelder-Mead. The Default is COBYLA.

Returns:

opt_resdict: The optimal result after running QAOA problem for a specific problem instance. It contains the measurement results after applying the optimal QAOA circuit to the quantum argument.