How to use the pennylane.RZ function in PennyLane

To help you get started, we’ve selected a few PennyLane examples, based on popular ways it is used in public projects.

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github XanaduAI / pennylane / tests / qnodes / test_qnode_qubit.py View on Github external
def circuit(a, b, c):
            qml.RX(a, wires=0)
            qml.RY(b, wires=1)
            qml.CNOT(wires=[1, 2])
            qml.RX(c, wires=2)
            qml.CNOT(wires=[0, 1])
            qml.RZ(c, wires=2)
            return qml.var(qml.PauliZ(0)), qml.expval(qml.PauliZ(1)), qml.var(qml.PauliZ(2))
github XanaduAI / pennylane / tests / test_utils.py View on Github external
def template(x):
            for i in range(5):
                qml.RZ(i * x, wires=0)

            return qml.var(qml.PauliZ(0)), qml.sample(qml.PauliX(1))
github XanaduAI / pennylane / tests / beta / test_tensornet_tf.py View on Github external
rz = lambda theta: np.cos(theta / 2) * I + 1j * np.sin(-theta / 2) * Z
rot = lambda a, b, c: rz(c) @ (ry(b) @ rz(a))
crz = lambda theta: np.array(
    [
        [1, 0, 0, 0],
        [0, 1, 0, 0],
        [0, 0, np.exp(-1j * theta / 2), 0],
        [0, 0, 0, np.exp(1j * theta / 2)],
    ]
)


single_qubit = [(qml.PauliX, X), (qml.PauliY, Y), (qml.PauliZ, Z), (qml.Hadamard, H)]


single_qubit_param = [(qml.PhaseShift, phase_shift), (qml.RX, rx), (qml.RY, ry), (qml.RZ, rz)]
two_qubit = [(qml.CNOT, CNOT), (qml.SWAP, SWAP)]
two_qubit_param = [(qml.CRZ, crz)]
three_qubit = [(qml.Toffoli, Toffoli), (qml.CSWAP, CSWAP)]


#####################################################
# Fixtures
#####################################################


@pytest.fixture
def init_state(scope="session"):
    """Generates a random initial state"""

    def _init_state(n):
        """random initial state"""
github XanaduAI / pennylane / tests / test_qnode.py View on Github external
def layer3_off_diag_first_order(x, y, z, h, g, f):
            non_parametrized_layer(a, b, c)
            qml.RX(x, wires=0)
            qml.RY(y, wires=1)
            qml.RZ(z, wires=2)
            non_parametrized_layer(a, b, c)
            return qml.expval(qml.PauliZ(2)), qml.expval(qml.PauliY(1))
github XanaduAI / pennylane / tests / qnodes / test_qnode_metric_tensor.py View on Github external
def non_parametrized_layer(a, b, c):
            qml.RX(a, wires=0)
            qml.RX(b, wires=1)
            qml.RX(c, wires=1)
            qml.CNOT(wires=[0, 1])
            qml.CNOT(wires=[1, 2])
            qml.RZ(a, wires=0)
            qml.Hadamard(wires=1)
            qml.CNOT(wires=[0, 1])
            qml.RZ(b, wires=1)
            qml.Hadamard(wires=0)
github XanaduAI / pennylane / tests / test_qnode.py View on Github external
def non_parametrized_layer(a, b, c):
            qml.RX(a, wires=0)
            qml.RX(b, wires=1)
            qml.RX(c, wires=1)
            qml.CNOT(wires=[0, 1])
            qml.CNOT(wires=[1, 2])
            qml.RZ(a, wires=0)
            qml.Hadamard(wires=1)
            qml.CNOT(wires=[0, 1])
            qml.RZ(b, wires=1)
            qml.Hadamard(wires=0)
github XanaduAI / pennylane / examples / pennylane_pytorch_noise.py View on Github external
def circuit(phi, theta):
    qml.RX(theta, wires=0)
    qml.RZ(phi, wires=0)
    return qml.expval(qml.PauliZ(0))
github XanaduAI / qml / demonstrations / tutorial_quantum_metrology.py View on Github external
def encoding(phi, gamma):
    for i in range(3):
        qml.RZ(phi[i], wires=[i])
        cirq_ops.PhaseDamp(gamma, wires=[i])
github XanaduAI / pennylane / examples / Q4_quantum-GAN.py View on Github external
def generator(w):
    """Circuit that serves as a generator.

    Args:
        w (array[float]): variables of the circuit
    """
    qml.RX(w[0], wires=0)
    qml.RX(w[1], wires=1)
    qml.RY(w[2], wires=0)
    qml.RY(w[3], wires=1)
    qml.RZ(w[4], wires=0)
    qml.RZ(w[5], wires=1)
    qml.CNOT(wires=[0,1])
    qml.RX(w[6], wires=0)
    qml.RY(w[7], wires=0)
    qml.RZ(w[8], wires=0)
github XanaduAI / pennylane / examples / Q4_quantum-GAN.py View on Github external
def discriminator(w):
    """Circuit that serves as a discriminator. Same structure as generator.

    Args:
        w (array[float]): variables of the circuit
    """
    qml.RX(w[0], wires=0)
    qml.RX(w[1], wires=2)
    qml.RY(w[2], wires=0)
    qml.RY(w[3], wires=2)
    qml.RZ(w[4], wires=0)
    qml.RZ(w[5], wires=2)
    qml.CNOT(wires=[1,2])
    qml.RX(w[6], wires=2)
    qml.RY(w[7], wires=2)
    qml.RZ(w[8], wires=2)

PennyLane

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.

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