def test_statefn_overlaps(self):
"""state functions overlaps test"""
wf = (4 * StateFn({"101010": 0.5, "111111": 0.3})) + ((3 + 0.1j) * (Zero ^ 6))
wf_vec = StateFn(wf.to_matrix())
self.assertAlmostEqual(wf.adjoint().eval(wf), 14.45)
self.assertAlmostEqual(wf_vec.adjoint().eval(wf_vec), 14.45)
self.assertAlmostEqual(wf_vec.adjoint().eval(wf), 14.45)
self.assertAlmostEqual(wf.adjoint().eval(wf_vec), 14.45)
def test_wf_evals_x(self):
""" wf evals x test """
qbits = 4
wf = ((Zero ^ qbits) + (One ^ qbits)) * (1 / 2**.5)
# Note: wf = Plus^qbits fails because TensoredOp can't handle it.
wf_vec = StateFn(wf.to_matrix())
op = X ^ qbits
# op = I^6
self.assertAlmostEqual(wf.adjoint().eval(op.eval(wf)), 1)
self.assertAlmostEqual(wf_vec.adjoint().eval(op.eval(wf)), 1)
self.assertAlmostEqual(wf.adjoint().eval(op.eval(wf_vec)), 1)
self.assertAlmostEqual(wf_vec.adjoint().eval(op.eval(wf_vec)), 1)
# op = (H^X^Y)^2
op = H ^ 6
wf = ((Zero ^ 6) + (One ^ 6)) * (1 / 2**.5)
wf_vec = StateFn(wf.to_matrix())
# print(wf.adjoint().to_matrix() @ op.to_matrix() @ wf.to_matrix())
self.assertAlmostEqual(wf.adjoint().eval(op.eval(wf)), .25)
self.assertAlmostEqual(wf_vec.adjoint().eval(op.eval(wf)), .25)
self.assertAlmostEqual(wf.adjoint().eval(op.eval(wf_vec)), .25)
self.assertAlmostEqual(wf_vec.adjoint().eval(op.eval(wf_vec)), .25)
