我们然后在VQE运行时设置它,就有QuantumInstance可以使用了。 algorithm_globals.random_seed=seedqi=QuantumInstance(Aer.get_backend('aer_simulator_statevector'),seed_transpiler=seed,seed_simulator=seed)ansatz=TwoLocal(rotation_blocks='ry',entanglement_blocks='cz')slsqp=SLSQP(maxiter=1000)vqe=VQE(ansatz,o...
本文展示了使用Qiskit中VQE算法,绘制了选择优化器组的收敛到基态能量的图像。 importnumpyasnpimportpylabfromqiskitimportAerfromqiskit.opflowimportX,Z,Ifromqiskit.utilsimportQuantumInstance,algorithm_globalsfromqiskit.algorithmsimportVQE,NumPyMinimumEigensolverfromqiskit.algorithms.optimizersimportCOBYLA,L_BFGS_B,SLSQP...
I have addressed the previous comment and also updated all occurrences of algorithm_globals. See df0137c for more details on the latter. Member woodsp-ibm commented Sep 14, 2023 • edited One other thing - this also uses qiskit.utils validation eg like this in places from qiskit.utils....
总体而言，机器学习是让计算机在大量数据中寻找数据规律，并根据数据规律对未知或主要数据趋势进行最终预测。
Deprecation of algorithm utils (algorithm_globals and validation) (#10905) Deprecate bind_parameters in favor of assign_parameters (#10792) Move OpenQASM 2 exporter to qiskit.qasm2 (#10533) Deprecate qiskit.extensions (#10725) Deprecate duplicate circuit gate method (#10797) Added Merging UnrollCu...
seed=50algorithm_globals.random_seed=seedqi=QuantumInstance(Aer.get_backend('statevector_simulator'),seed_transpiler=seed,seed_simulator=seed)ansatz=TwoLocal(rotation_blocks='ry',entanglement_blocks='cz')slsqp=SLSQP(maxiter=1000)vqe=VQE(ansatz,optimizer=slsqp,quantum_instance=qi)result=vqe.compute_mi...
binary string as numpy array.w (numpy.ndarray): adjacency matrix.Returns:float: value of the cut."""X=np.outer(x,(1-x))w_01=np.where(w!=0,1,0)returnnp.sum(w_01*X)algorithm_globals.random_seed=10598optimizer=COBYLA()qaoa=QAOA(optimizer,quantum_instance=Aer.get_backend('statevector...
from qiskit.utils import algorithm_globals from qiskit_aer.noise import NoiseModel from qiskit_ibm_runtime import QiskitRuntimeService, Options, Session, Sampler from qiskit_machine_learning.kernels import TrainableFidelityQuantumKernel from qiskit_machine_learning.kernels.algorithms import QuantumKernelTrainer...
utils import algorithm_globals from qiskit_machine_learning.algorithms import VQC from qiskit_machine_learning.datasets import ad_hoc_data seed = 1376 algorithm_globals.random_seed = seed # Use ad hoc data set for training and test data feature_dim = 2 # dimension of each data point training_...
[j]fori,j,winedges))# Fix node 0 to be 1 to break the symmetry of the max-cut solutionmodel.add(x[0]==1)# Convert the Docplex model into a `QuadraticProgram` objectproblem=from_docplex_mp(model)# Run quantum algorithm QAOA on qasm simulatorseed=1234algorithm_globals.random_seed=...