def test_pauliz_tensor_hadamard(self, theta, phi, varphi, tol_stochastic):
        """Test that a tensor product involving PauliZ and hadamard works correctly"""
        dev = qml.device("default.qubit", wires=3, shots=int(1e6))

        @qml.qnode(dev, diff_method="parameter-shift")
        def circuit(a, b, c):
            ansatz(a, b, c)
            return sample(qml.PauliZ(0) @ qml.Hadamard(1) @ qml.PauliY(2))

        s1 = circuit(theta, phi, varphi)

        zero_state = np.zeros(2**3)
        zero_state[0] = 1
        psi = zero_state
        psi = tensor_product([Rotx(theta), I, I]) @ zero_state
        psi = tensor_product([I, Rotx(phi), I]) @ psi
        psi = tensor_product([I, I, Rotx(varphi)]) @ psi
        psi = tensor_product([CNOT, I]) @ psi
        psi = tensor_product([I, CNOT]) @ psi

        # Diagonalize according to the observable
        psi = tensor_product([I, Roty(-np.pi / 4), I]) @ psi
        psi = tensor_product([I, I, Z]) @ psi
        psi = tensor_product([I, I, S]) @ psi
        psi = tensor_product([I, I, H]) @ psi

        expected_probabilities = np.abs(psi)**2

        assert np.allclose(dev.probability(),
                           expected_probabilities,
                           atol=tol_stochastic,
                           rtol=0)

        # s1 should only contain 1 and -1
        assert np.allclose(s1**2, 1, atol=tol_stochastic, rtol=0)
    def test_paulix_tensor_pauliy(self, theta, phi, varphi, tol):
        """Test that a tensor product involving PauliX and PauliY works correctly"""
        dev = qml.device("default.qubit", wires=3)

        @qml.qnode(dev)
        def circuit(a, b, c):
            ansatz(a, b, c)
            return sample(qml.PauliX(0) @ qml.PauliY(2))

        s1 = circuit(theta, phi, varphi)

        # s1 should only contain 1 and -1
        assert np.allclose(s1**2, 1, atol=tol, rtol=0)

        zero_state = np.zeros(2**3)
        zero_state[0] = 1
        psi = zero_state
        psi = tensor_product([Rotx(theta), I, I]) @ zero_state
        psi = tensor_product([I, Rotx(phi), I]) @ psi
        psi = tensor_product([I, I, Rotx(varphi)]) @ psi
        psi = tensor_product([CNOT, I]) @ psi
        psi = tensor_product([I, CNOT]) @ psi

        # Diagonalize according to the observable
        psi = tensor_product([H, I, I]) @ psi
        psi = tensor_product([I, I, Z]) @ psi
        psi = tensor_product([I, I, S]) @ psi
        psi = tensor_product([I, I, H]) @ psi

        expected_probabilities = np.abs(psi)**2

        assert np.allclose(dev.probability(),
                           expected_probabilities,
                           atol=tol,
                           rtol=0)
    def test_tensor_hermitian(self, theta, phi, varphi, tol):
        """Test that a tensor product involving qml.Hermitian works correctly"""
        dev = qml.device("default.qubit", wires=3)

        A = np.array([
            [-6, 2 + 1j, -3, -5 + 2j],
            [2 - 1j, 0, 2 - 1j, -5 + 4j],
            [-3, 2 + 1j, 0, -4 + 3j],
            [-5 - 2j, -5 - 4j, -4 - 3j, -6],
        ])

        @qml.qnode(dev)
        def circuit(a, b, c):
            ansatz(a, b, c)
            return sample(qml.PauliZ(0) @ qml.Hermitian(A, [1, 2]))

        s1 = circuit(theta, phi, varphi)

        # s1 should only contain the eigenvalues of
        # the hermitian matrix tensor product Z
        Z = np.diag([1, -1])
        eigvals = np.linalg.eigvalsh(np.kron(Z, A))
        assert set(np.round(s1, 8)).issubset(set(np.round(eigvals, 8)))

        zero_state = np.zeros(2**3)
        zero_state[0] = 1
        psi = zero_state
        psi = tensor_product([Rotx(theta), I, I]) @ zero_state
        psi = tensor_product([I, Rotx(phi), I]) @ psi
        psi = tensor_product([I, I, Rotx(varphi)]) @ psi
        psi = tensor_product([CNOT, I]) @ psi
        psi = tensor_product([I, CNOT]) @ psi

        # Diagonalize according to the observable
        eigvals, eigvecs = np.linalg.eigh(A)
        psi = tensor_product([I, eigvecs.conj().T]) @ psi

        expected_probabilities = np.abs(psi)**2

        assert np.allclose(dev.probability(),
                           expected_probabilities,
                           atol=tol,
                           rtol=0)
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    def test_multiple_expectation_different_wires(self, qubit_device_2_wires,
                                                  tol):
        """Tests that qnodes return multiple expectation values."""
        a, b, c = torch.tensor(0.5), torch.tensor(0.54), torch.tensor(0.3)

        @qml.qnode(qubit_device_2_wires, interface='torch')
        def circuit(x, y, z):
            qml.RX(x, wires=[0])
            qml.RZ(y, wires=[0])
            qml.CNOT(wires=[0, 1])
            qml.RY(y, wires=[0])
            qml.RX(z, wires=[0])
            return qml.expval(qml.PauliY(0)), qml.expval(qml.PauliZ(1))

        res = circuit(a, b, c)

        out_state = np.kron(Rotx(c.numpy()), I) @ np.kron(Roty(b.numpy()), I) @ CNOT \
            @ np.kron(Rotz(b.numpy()), I) @ np.kron(Rotx(a.numpy()), I) @ np.array([1, 0, 0, 0])

        ex0 = np.vdot(out_state, np.kron(Y, I) @ out_state)
        ex1 = np.vdot(out_state, np.kron(I, Z) @ out_state)
        ex = np.array([ex0, ex1])

        assert np.allclose(ex, res.numpy(), atol=tol, rtol=0)
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    def test_qnode_fanout(self, qubit_device_1_wire, tol):
        """Tests that qnodes can compute the correct function when the same parameter is used in multiple gates."""
        @qml.qnode(qubit_device_1_wire, interface='torch')
        def circuit(reused_param, other_param):
            qml.RX(reused_param, wires=[0])
            qml.RZ(other_param, wires=[0])
            qml.RX(reused_param, wires=[0])
            return qml.expval(qml.PauliZ(0))

        thetas = torch.linspace(-2 * np.pi, 2 * np.pi, 7)

        for reused_param in thetas:
            for theta in thetas:
                other_param = theta**2 / 11
                y_eval = circuit(reused_param, other_param)
                Rx = Rotx(reused_param.numpy())
                Rz = Rotz(other_param.numpy())
                zero_state = np.array([1., 0.])
                final_state = (Rx @ Rz @ Rx @ zero_state)
                y_true = expZ(final_state)

                assert np.allclose(y_eval, y_true, atol=tol, rtol=0)