code: def test_Q():
      """Test for the make_Q function using a fixed example"""
  
      A = np.array(
          [
              [0.85358423 - 0.32239299j, -0.12753659 + 0.38883306j],
              [0.39148136 - 0.11915985j, 0.34064316 - 0.84646648j],
          ]
      )
      R = np.array(
          [
              [
                  0.45885289 + 0.03972856j,
                  0.2798685 - 0.05981098j,
                  0.64514642 - 0.51555038j,
                  0.11015177 - 0.10877695j,
              ],
              [
                  0.19407005 - 0.35483005j,
                  0.29756077 + 0.80153453j,
                  -0.19147104 + 0.0507968j,
                  0.15553799 - 0.20493631j,
              ],
              [
                  0.35083011 - 0.20807392j,
                  -0.27602911 - 0.13934692j,
                  0.11874165 + 0.34532609j,
                  -0.45945242 - 0.62734969j,
              ],
              [
                  -0.11379919 - 0.66706921j,
                  -0.21120956 - 0.2165113j,
                  0.30133006 + 0.23367271j,
                  0.54593491 + 0.08446372j,
              ],
          ]
      )
  
      Q_expected = np.array(
          [
              [
                  -0.46513201 - 1.38777878e-17j,
                  -0.13035515 - 2.23341802e-01j,
                  -0.74047856 + 7.08652160e-02j,
                  -0.0990036 - 3.91977176e-01j,
              ],
              [
                  0.13035515 - 2.23341802e-01j,
                  0.46494302 + 0.00000000e00j,
                  0.05507901 - 1.19182067e-01j,
                  -0.80370146 - 2.31904873e-01j,
              ],
              [
                  -0.74047856 - 7.08652160e-02j,
                  -0.05507901 - 1.19182067e-01j,
                  0.62233412 - 2.77555756e-17j,
                  -0.0310774 - 2.02894077e-01j,
              ],
              [
                  0.0990036 - 3.91977176e-01j,
                  -0.80370146 + 2.31904873e-01j,
                  0.0310774 - 2.02894077e-01j,
                  -0.30774091 + 2.77555756e-17j,
              ],
          ]
      )
  
      Q = make_Q(A, R)
  
      assert np.allclose(Q, Q_expected)
  
imports: import numpy
  import pytest
  from scipy.stats import norm
  import pennylane
  from pennylane.templates.subroutines.qmc import QuantumMonteCarlo, _make_V, _make_Z, func_to_unitary, make_Q, probs_to_unitary
  from pennylane.wires import Wires
label_desc: Use image node_id 3 for calling a global function with example usage: test_Q() without return types