def test_to_matrix(self):
"""to matrix text """
np.testing.assert_array_equal(X.to_matrix(),
Operator.from_label('X').data)
np.testing.assert_array_equal(Y.to_matrix(),
Operator.from_label('Y').data)
np.testing.assert_array_equal(Z.to_matrix(),
Operator.from_label('Z').data)
op1 = Y + H
np.testing.assert_array_almost_equal(op1.to_matrix(),
Y.to_matrix() + H.to_matrix())
op2 = op1 * .5
np.testing.assert_array_almost_equal(op2.to_matrix(),
op1.to_matrix() * .5)
op3 = (4 - .6j) * op2
np.testing.assert_array_almost_equal(op3.to_matrix(),
op2.to_matrix() * (4 - .6j))
op4 = op3.tensor(X)
np.testing.assert_array_almost_equal(
op4.to_matrix(), np.kron(op3.to_matrix(), X.to_matrix()))
op5 = op4.compose(H ^ I)
np.testing.assert_array_almost_equal(
op5.to_matrix(), np.dot(op4.to_matrix(), (H ^ I).to_matrix()))
op6 = op5 + PrimitiveOp(Operator.from_label('+r').data)
np.testing.assert_array_almost_equal(
op6.to_matrix(),
op5.to_matrix() + Operator.from_label('+r').data)
def test_io_consistency(self):
""" consistency test """
new_op = X ^ Y ^ I
label = 'XYI'
# label = new_op.primitive.to_label()
self.assertEqual(str(new_op.primitive), label)
np.testing.assert_array_almost_equal(new_op.primitive.to_matrix(),
Operator.from_label(label).data)
self.assertEqual(new_op.primitive, Pauli(label=label))
x_mat = X.primitive.to_matrix()
y_mat = Y.primitive.to_matrix()
i_mat = np.eye(2, 2)
np.testing.assert_array_almost_equal(new_op.primitive.to_matrix(),
np.kron(np.kron(x_mat, y_mat), i_mat))
hi = np.kron(H.to_matrix(), I.to_matrix())
hi2 = Operator.from_label('HI').data
hi3 = (H ^ I).to_matrix()
np.testing.assert_array_almost_equal(hi, hi2)
np.testing.assert_array_almost_equal(hi2, hi3)
xy = np.kron(X.to_matrix(), Y.to_matrix())
xy2 = Operator.from_label('XY').data
xy3 = (X ^ Y).to_matrix()
np.testing.assert_array_almost_equal(xy, xy2)
np.testing.assert_array_almost_equal(xy2, xy3)
# Check if numpy array instantiation is the same as from Operator
matrix_op = Operator.from_label('+r')
np.testing.assert_array_almost_equal(PrimitiveOp(matrix_op).to_matrix(),
PrimitiveOp(matrix_op.data).to_matrix())
# Ditto list of lists
np.testing.assert_array_almost_equal(PrimitiveOp(matrix_op.data.tolist()).to_matrix(),
PrimitiveOp(matrix_op.data).to_matrix())
def test_to_matrix(self):
"""to matrix text """
np.testing.assert_array_equal(X.to_matrix(),
Operator.from_label('X').data)
np.testing.assert_array_equal(Y.to_matrix(),
Operator.from_label('Y').data)
np.testing.assert_array_equal(Z.to_matrix(),
Operator.from_label('Z').data)
op1 = Y + H
np.testing.assert_array_almost_equal(op1.to_matrix(),
Y.to_matrix() + H.to_matrix())
op2 = op1 * .5
np.testing.assert_array_almost_equal(op2.to_matrix(),
op1.to_matrix() * .5)
op3 = (4 - .6j) * op2
np.testing.assert_array_almost_equal(op3.to_matrix(),
op2.to_matrix() * (4 - .6j))
op4 = op3.tensor(X)
np.testing.assert_array_almost_equal(
op4.to_matrix(), np.kron(op3.to_matrix(), X.to_matrix()))
op5 = op4.compose(H ^ I)
np.testing.assert_array_almost_equal(
op5.to_matrix(), np.dot(op4.to_matrix(), (H ^ I).to_matrix()))
op6 = op5 + PrimitiveOp(Operator.from_label('+r').data)
np.testing.assert_array_almost_equal(
op6.to_matrix(),
op5.to_matrix() + Operator.from_label('+r').data)
param = Parameter("α")
m = np.array([[0, -1j], [1j, 0]])
op7 = MatrixOp(m, param)
np.testing.assert_array_equal(op7.to_matrix(), m * param)
param = Parameter("β")
op8 = PauliOp(primitive=Pauli(label="Y"), coeff=param)
np.testing.assert_array_equal(op8.to_matrix(), m * param)
param = Parameter("γ")
qc = QuantumCircuit(1)
qc.h(0)
op9 = CircuitOp(qc, coeff=param)
m = np.array([[1, 1], [1, -1]]) / np.sqrt(2)
np.testing.assert_array_equal(op9.to_matrix(), m * param)
from docplex.mp.model import Model from qiskit.optimization.problems import QuadraticProgram from qiskit.optimization.converters import QuadraticProgramToIsing from qiskit import QuantumCircuit from qiskit.aqua.operators import StateFn from qiskit.aqua.operators import Z, X, Y, I, H, S import random count = 0 w = 0 P_0 = I.to_matrix() P_1 = X.to_matrix() P_2 = Y.to_matrix() P_3 = Z.to_matrix() HH = H.to_matrix() S = S.to_matrix() OPE = [P_0, HH, S] pauli = [P_0, P_1, P_2, P_3] Pauli = [I, X, Y, Z] R = 2 #number of iteration == R n = 5 #number of qubits x_matrix = np.zeros((R, n)) z_matrix = np.zeros((R, n)) matrix = np.zeros((R, 2*n)) x_vector = [] z_vector = [] vector = []