qrisp.vqe.VQEProblem.run#
- VQEProblem.run(qarg, depth, mes_kwargs={}, max_iter=50, init_type='random', init_point=None, optimizer='COBYLA')[source]#
Run the specific VQE problem instance with given quantum arguments, depth of VQE circuit, measurement keyword arguments (mes_kwargs) and maximum iterations for optimization (max_iter).
- Parameters:
- qargQuantumVariable or QuantumArray
The argument to which the VQE circuit is applied.
- depthint
The amount of VQE layers.
- mes_kwargsdict, optional
The keyword arguments for the measurement function. Default is an empty dictionary. By default, the target
precision
is set to 0.01, and the maximum amount ofshots
is 100000.- 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 is
random
. The default israndom
: Parameters are initialized uniformly at random in the interval \([0,\pi/2)]\).- init_pointlist[float], optional
Specifies the initial optimization parameters.
- optimizerstr, optional
Specifies the optimization routine. Available are, e.g.,
COBYLA
,COBYQA
,Nelder-Mead
. The Default isCOBYLA
.
- Returns:
- energyfloat
The expected value of the Hamiltonian after applying the optimal VQE circuit to the quantum argument.