def basic_variational_circuit(params, rotations, masked_circuit: MaskedCircuit):
full_parameters = masked_circuit.expanded_parameters(params)
wires = masked_circuit.wires
dropout_mask = masked_circuit.full_mask(DropoutMask)
for wire, _is_masked in enumerate(masked_circuit.mask(Axis.WIRES)):
qml.RY(np.pi / 4, wires=wire)
r = -1
for layer, _is_layer_masked in enumerate(masked_circuit.mask(Axis.LAYERS)):
for wire, _is_wire_masked in enumerate(masked_circuit.mask(Axis.WIRES)):
r += 1
if dropout_mask[layer][wire]:
continue
if rotations[r] == 0:
rotation = qml.RX
elif rotations[r] == 1:
rotation = qml.RY
else:
rotation = qml.RZ
rotation(full_parameters[layer][wire], wires=wire)
for wire in range(0, wires - 1, 2):
if (
Axis.ENTANGLING in masked_circuit.masks
and masked_circuit.mask(Axis.ENTANGLING)[layer, wire]
):
continue
qml.CZ(wires=[wire, wire + 1])
for wire in range(1, wires - 1, 2):
if (
Axis.ENTANGLING in masked_circuit.masks
and masked_circuit.mask(Axis.ENTANGLING)[layer, wire]
):
continue
qml.CZ(wires=[wire, wire + 1])
def variational_ansatz_zero(params, wires):
n_qubits = len(wires)
D1 = [0,1]
D2 = [i for i in range(len(D1) ,params.shape[0]-1)]
depth = params.shape[0]
#n_rotations = len(D1)
qml.BasisState(np.array([0 for i in range(n_qubits)]), wires=[i for i in range(n_qubits)])
for d in D1:
for i in range(n_qubits//2, n_qubits):
qml.RY(params[d,i],wires=[i])
qml.RZ(params[d,i],wires=[i])
for d2 in D2:
for i in range(n_qubits):
qml.RY(params[d2,i],wires=[i])
qml.RZ(params[d2,i],wires=[i])
for i in range(n_qubits//2):
qml.CZ(wires=[2*i, 2*i + 1]) #circuit.add_gate(CZ(2*i, 2*i+1))
for i in range(n_qubits//2 - 1):
qml.CZ(wires=[2*i+1, 2*i + 2]) #circuit.add_gate(CZ(2*i+1, 2*i+2))
for i in range(n_qubits):
qml.RY(params[depth-1,i],wires=[i])
qml.RZ(params[depth-1,i],wires=[i])
def expand(self):
with qml.tape.QuantumTape() as tape:
# initial rotations
for i in range(len(self.wires)):
qml.RY(self.parameters[0][i], wires=self.wires[i])
for layer in range(self.n_layers):
# even layer of entanglers
even_wires = [
self.wires[i:i + 2] for i in range(0,
len(self.wires) - 1, 2)
]
for i, wire_pair in enumerate(even_wires):
qml.CZ(wires=wire_pair)
qml.RY(self.parameters[1][layer, i, 0], wires=wire_pair[0])
qml.RY(self.parameters[1][layer, i, 1], wires=wire_pair[1])
# odd layer of entanglers
odd_wires = [
self.wires[i:i + 2] for i in range(1,
len(self.wires) - 1, 2)
]
for i, wire_pair in enumerate(odd_wires):
qml.CZ(wires=wire_pair)
qml.RY(self.parameters[1][layer,
len(self.wires) // 2 + i, 0],
wires=wire_pair[0])
qml.RY(self.parameters[1][layer,
len(self.wires) // 2 + i, 1],
wires=wire_pair[1])
return tape
def qfunc(a, b, c, angles):
qml.RX(a, wires=0)
qml.RX(b, wires=1)
qml.PauliZ(1)
qml.CNOT(wires=[0, 1]).inv()
qml.CRY(b, wires=[3, 1])
qml.RX(angles[0], wires=0)
qml.RX(4 * angles[1], wires=1)
qml.PhaseShift(17 / 9 * c, wires=2)
qml.RZ(b, wires=3)
qml.RX(angles[2], wires=2).inv()
qml.CRY(0.3589, wires=[3, 1]).inv()
qml.CSWAP(wires=[4, 2, 1]).inv()
qml.QubitUnitary(np.eye(2), wires=[2])
qml.Toffoli(wires=[0, 2, 1])
qml.CNOT(wires=[0, 2])
qml.PauliZ(wires=[1])
qml.PauliZ(wires=[1]).inv()
qml.CZ(wires=[0, 1])
qml.CZ(wires=[0, 2]).inv()
qml.CNOT(wires=[2, 1])
qml.CNOT(wires=[0, 2])
qml.SWAP(wires=[0, 2]).inv()
qml.CNOT(wires=[1, 3])
qml.RZ(b, wires=3)
qml.CSWAP(wires=[4, 0, 1])
return [
qml.expval(qml.PauliY(0)),
qml.var(qml.Hadamard(wires=1)),
qml.sample(qml.PauliX(2)),
qml.expval(qml.Hermitian(np.eye(4), wires=[3, 4])),
]
def entangler(self, layer):
if layer%2==0:
for wire in range(0, self.width//2, 1):
qml.CZ(wires=[2*wire, 2*wire + 1])
if layer%2==1:
for wire in range(1, self.width+1, 2):
qml.CZ(wires=[wire, (wire + 1)%self.width])
def entangle_layer(width=4, layer=4):
"""adds entangling gates to even / odd wires"""
even = [[i, i+1] for i in range(0, width, 2)]
odd = [[i+1, (i+2)%width] for i in range(0, width, 2)]
for i in range(int(width/2)):
if layer%2 == 0:
qml.CZ(wires=even[i])
if layer%2 == 1:
qml.CZ(wires=odd[i])
def circuit1(params, x=None):
for i in range(n_wires):
qml.RX(x[i % n_features], wires=i)
qml.Rot(*params[0, 0, i], wires=i)
qml.CZ(wires=[0, 1])
qml.CZ(wires=[1, 2])
qml.CZ(wires=[1, 3])
for i in range(n_wires):
qml.Rot(*params[0, 1, i], wires=i)
return qml.expval(qml.PauliZ(0)), qml.expval(qml.PauliZ(1)), qml.expval(qml.PauliZ(2))
def plain_variational_circuit(params):
layers = params.shape[0]
wires = params.shape[1]
for layer in range(layers):
for wire in range(wires):
qml.RX(params[layer][wire][0], wires=wire)
qml.RY(params[layer][wire][1], wires=wire)
for wire in range(0, layers - 1, 2):
qml.CZ(wires=[wire, wire + 1])
for wire in range(1, layers - 1, 2):
qml.CZ(wires=[wire, wire + 1])
return qml.probs(wires=range(wires))
def rand_circuit(self, cparams, num_qparams):
# Numbers of classical and "quantum" parameters
gate_idx = 0
num_cparams = self.num_params - num_qparams
# Wires:
# First `num_qubits` wires form the main register.
# After that, every `precision_qparams` wires coresponds to one qparam.
num_wires = self.num_qubits + num_qparams * self.precision_qparams
# Iterate over layers
for k in range(self.num_params):
# Algorithm description: the number of layers in this circuit is
# equal to num_params, with each layer receiving a single parameter.
# The first layers will be filled with classical parameters, after
# which the remainder of layers receive quantum parameters.
# sqrt(H) mixing layer
for i in range(self.num_qubits):
qml.RY(np.pi / 4, wires=i)
# Fill out classical parameter first
if k < num_cparams:
# First wire gets the param
self.gate_set[self.random_gateidx_sequence[k]](cparams[k],
wires=0)
# Fill out quantum parameters
else:
ctrl_gate = self.ctrl_gate_set[self.random_gateidx_sequence[k]]
# Add controls to every wire in the ancilla register according
# to the bit of theta that we're capturing.
for j in range(self.precision_qparams):
ctrl_wire = self.num_qubits + (
k - num_cparams) * self.precision_qparams + j
#j = 0 is the least significant
ctrl_angle = self.max_qparams * 2**(
self.precision_qparams - j - 1) / self.num_bins
ctrl_gate(ctrl_angle, wires=[ctrl_wire, 0])
# Pad the remainder of each parameterized layer with random paulis
for i in range(1, self.num_qubits):
rand_angle = np.random.random() * np.pi
rand_gate = self.gate_set[self.singleq_gate_sequence[gate_idx]]
gate_idx += 1
rand_gate(rand_angle, wires=i)
# Interleaved entangling gates
for i in range(0, self.num_qubits - 1, 2):
qml.CZ(wires=[i, i + 1])
for i in range(1, self.num_qubits - 1, 2):
qml.CZ(wires=[i, i + 1])
def qfunc(theta):
qml.Hadamard(wires=0)
qml.PauliX(wires=1)
qml.S(wires=1)
qml.adjoint(qml.S)(wires=1)
qml.Hadamard(wires=0)
qml.CNOT(wires=[0, 1])
qml.RZ(theta[0], wires=2)
qml.PauliX(wires=1)
qml.CZ(wires=[1, 0])
qml.RY(theta[1], wires=2)
qml.CZ(wires=[0, 1])
return qml.expval(qml.PauliX(0) @ qml.PauliX(2))
def circuit_decomposed(initial_weights, weights):
qml.RY(initial_weights[0], wires=0)
qml.RY(initial_weights[1], wires=1)
qml.RY(initial_weights[2], wires=2)
qml.CZ(wires=[0, 1])
qml.RY(weights[0, 0, 0], wires=0)
qml.RY(weights[0, 0, 1], wires=1)
qml.CZ(wires=[1, 2])
qml.RY(weights[0, 1, 0], wires=1)
qml.RY(weights[0, 1, 1], wires=2)
return qml.expval(qml.PauliZ(0))
def variational_circuit(params, masked_circuit: MaskedCircuit = None):
full_parameters = masked_circuit.expanded_parameters(params)
for layer, layer_hidden in enumerate(masked_circuit.mask(Axis.LAYERS)):
if not layer_hidden:
for wire, wire_hidden in enumerate(masked_circuit.mask(Axis.WIRES)):
if not wire_hidden:
if not masked_circuit.mask(Axis.PARAMETERS)[layer][wire][0]:
qml.RX(full_parameters[layer][wire][0], wires=wire)
if not masked_circuit.mask(Axis.PARAMETERS)[layer][wire][1]:
qml.RY(full_parameters[layer][wire][1], wires=wire)
for wire in range(0, masked_circuit.mask(Axis.LAYERS).size - 1, 2):
qml.CZ(wires=[wire, wire + 1])
for wire in range(1, masked_circuit.mask(Axis.LAYERS).size - 1, 2):
qml.CZ(wires=[wire, wire + 1])
return qml.probs(wires=range(len(masked_circuit.mask(Axis.WIRES))))
def circuit(params, x):
xEmbeded = [i * np.pi for i in x]
for i in range(NUM_WIRES):
qml.RX(xEmbeded[i], wires=i)
qml.Rot(*params[0, i], wires=i)
qml.CZ(wires=[1, 0])
qml.CZ(wires=[1, 2])
qml.CZ(wires=[0, 2])
for i in range(NUM_WIRES):
qml.Rot(*params[1, i], wires=i)
return qml.expval(qml.PauliZ(0)), qml.expval(
qml.PauliZ(1)), qml.expval(qml.PauliZ(2))
def decomposition(wires):
return [
qml.SWAP(wires=wires),
qml.S(wires=[wires[0]]),
qml.S(wires=[wires[1]]),
qml.CZ(wires=wires),
]
def variational_ansatz(params, wires):
"""The variational ansatz circuit.
Fill in the details of your ansatz between the # QHACK # comment markers. Your
ansatz should produce an n-qubit state of the form
a_0 |10...0> + a_1 |01..0> + ... + a_{n-2} |00...10> + a_{n-1} |00...01>
where {a_i} are real-valued coefficients.
Args:
params (np.array): The variational parameters.
wires (qml.Wires): The device wires that this circuit will run on.
"""
# QHACK #
N = len(wires)
qml.PauliX(wires=0)
for i, param in enumerate(params):
qml.RY(-param, wires=i + 1)
qml.CZ(wires=[i + 1, i])
qml.RY(param, wires=i + 1)
# Reversed CNOTs
for i in range(len(params)):
qml.Hadamard(wires=i)
qml.Hadamard(wires=i + 1)
qml.CNOT(wires=[i, i + 1])
qml.Hadamard(wires=i)
qml.Hadamard(wires=i + 1)
def rand_circuit(self, cparams, num_qparams):
# Numbers of classical and "quantum" parameters
num_cparams = self.num_params - num_qparams
# Wires:
# First `num_qubits` wires form the main register.
# After that, every `precision_qparams` wires coresponds to one qparam.
num_wires = self.num_qubits + num_qparams * self.precision_qparams
for i in range(self.num_qubits):
qml.RY(np.pi / 4, wires=i)
for i in range(num_cparams):
self.gate_set[self.random_gateidx_sequence[i]](cparams[i], wires=i)
for i in range(num_cparams, self.num_params):
ctrl_gate = self.ctrl_gate_set[self.random_gateidx_sequence[i]]
for j in range(self.precision_qparams):
ctrl_wire = self.num_qubits + (
i - num_cparams) * self.precision_qparams + j
#j = 0 is the least significant
ctrl_angle = self.max_qparams * 2**(self.precision_qparams -
j - 1) / self.num_bins
ctrl_gate(ctrl_angle, wires=[ctrl_wire, i])
for i in range(self.num_qubits - 1):
qml.CZ(wires=[i, i + 1])
def circuit():
"""A combination of two and three qubit gates with the one_qubit_block and a simple
PauliZ measurement, all acting on a four qubit input basis state"""
qml.BasisState(np.array(basis_state), wires=[0, 1, 2, 3])
qml.RX(0.5, wires=0)
qml.Hadamard(wires=1)
qml.RY(0.9, wires=2)
qml.Rot(0.1, -0.2, -0.3, wires=3)
qml.CNOT(wires=[0, 1])
qml.CNOT(wires=[3, 1])
one_qubit_block(wires=3)
qml.CNOT(wires=[2, 0])
qml.CZ(wires=[1, 0])
one_qubit_block(wires=0)
qml.Toffoli(wires=[1, 0, 2])
one_qubit_block(wires=2)
qml.SWAP(wires=[0, 1])
qml.SWAP(wires=[0, 2])
qml.Toffoli(wires=[1, 3, 2])
qml.CRX(0.5, wires=[1, 0])
qml.CSWAP(wires=[2, 1, 0])
qml.CRY(0.9, wires=[2, 1])
one_qubit_block(wires=1)
qml.CRZ(0.02, wires=[0, 1])
qml.CRY(0.9, wires=[2, 3])
qml.CRot(0.2, 0.3, 0.7, wires=[2, 1])
qml.RZ(0.4, wires=0)
qml.Toffoli(wires=[2, 1, 0])
return qml.expval(qml.PauliZ(0))
def test_statevector_complex_circuit(self, dev, tol):
dy = np.array([[1.0, 0.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0],
[0.0, 1.0, 0.0, 0.0], [0.0, 0.0, 0.0, 1.0]])
fn0 = dev.vjp([qml.state()], dy[0, :])
fn1 = dev.vjp([qml.state()], dy[1, :])
fn2 = dev.vjp([qml.state()], dy[2, :])
fn3 = dev.vjp([qml.state()], dy[3, :])
params = [math.pi / 7, 6 * math.pi / 7]
with qml.tape.QuantumTape() as tape:
qml.QubitStateVector(np.array([1.0] * 4) / 2, wires=range(2))
qml.RY(params[0], wires=0)
qml.RZ(params[1], wires=1)
qml.CZ(wires=[0, 1])
tape.trainable_params = {2} # RZ
psi_00_diff = (
(math.cos(params[0] / 2) - math.sin(params[0] / 2)) *
(-math.sin(params[1] / 2) - 1j * math.cos(params[1] / 2)) / 4)
psi_01_diff = (
(math.cos(params[0] / 2) + math.sin(params[0] / 2)) *
(-math.sin(params[1] / 2) - 1j * math.cos(params[1] / 2)) / 4)
psi_10_diff = (
(math.cos(params[0] / 2) - math.sin(params[0] / 2)) *
(-math.sin(params[1] / 2) + 1j * math.cos(params[1] / 2)) / 4)
psi_11_diff = (
-(math.cos(params[0] / 2) + math.sin(params[0] / 2)) *
(-math.sin(params[1] / 2) + 1j * math.cos(params[1] / 2)) / 4)
assert np.allclose(fn0(tape), psi_00_diff, atol=tol)
assert np.allclose(fn1(tape), psi_01_diff, atol=tol)
assert np.allclose(fn2(tape), psi_10_diff, atol=tol)
assert np.allclose(fn3(tape), psi_11_diff, atol=tol)
def local_hadamard_test(weights, l=None, lp=None, j=None, part=None):
# First Hadamard gate applied to the ancillary qubit.
qml.Hadamard(wires=ancilla_idx)
# For estimating the imaginary part of the coefficient "mu", we must add a "-i" phase gate.
if part == "Im" or part == "im":
qml.PhaseShift(-np.pi / 2, wires=ancilla_idx)
# Variational circuit generating a guess for the solution vector |x>
variational_block(weights)
# Controlled application of the unitary component A_l of the problem matrix A.
CA(l)
# Adjoint of the unitary U_b associated to the problem vector |b>.
# In this specific example Adjoint(U_b) = U_b.
U_b()
# Controlled Z operator at position j. If j = -1, apply the identity.
if j != -1:
qml.CZ(wires=[ancilla_idx, j])
# Unitary U_b associated to the problem vector |b>.
U_b()
# Controlled application of Adjoint(A_lp).
# In this specific example Adjoint(A_lp) = A_lp.
CA(lp)
# Second Hadamard gate applied to the ancillary qubit.
qml.Hadamard(wires=ancilla_idx)
# Expectation value of Z for the ancillary qubit.
return qml.expval(qml.PauliZ(wires=ancilla_idx))
def test_control_sanity_check():
"""Test that control works on a very standard usecase."""
def make_ops():
qml.RX(0.123, wires=0)
qml.RY(0.456, wires=2)
qml.RX(0.789, wires=0)
qml.Rot(0.111, 0.222, 0.333, wires=2),
qml.PauliX(wires=2)
qml.PauliY(wires=4)
qml.PauliZ(wires=0)
with QuantumTape() as tape:
cmake_ops = ctrl(make_ops, control=1)
#Execute controlled version.
cmake_ops()
expected = [
qml.CRX(0.123, wires=[1, 0]),
qml.CRY(0.456, wires=[1, 2]),
qml.CRX(0.789, wires=[1, 0]),
qml.CRot(0.111, 0.222, 0.333, wires=[1, 2]),
qml.CNOT(wires=[1, 2]),
qml.CY(wires=[1, 4]),
qml.CZ(wires=[1, 0]),
]
assert len(tape.operations) == 1
ctrl_op = tape.operations[0]
assert isinstance(ctrl_op, ControlledOperation)
expanded = ctrl_op.expand()
assert_equal_operations(expanded.operations, expected)
def decompose_ua(phi, wires=None):
r"""Implements the circuit decomposing the controlled application of the unitary
:math:`U_A(\phi)`
.. math::
U_A(\phi) = \left(\begin{array}{cc} 0 & e^{-i\phi} \\ e^{-i\phi} & 0 \\ \end{array}\right)
in terms of the quantum operations supported by PennyLane.
:math:`U_A(\phi)` is used in `arXiv:1805.04340 <https://arxiv.org/abs/1805.04340>`_,
to define two-qubit exchange gates required to build particle-conserving
VQE ansatze for quantum chemistry simulations. See :func:`~.ParticleConservingU1`.
:math:`U_A(\phi)` is expressed in terms of ``PhaseShift``, ``Rot`` and ``PauliZ`` operations
:math:`U_A(\phi) = R_\phi(-2\phi) R(-\phi, \pi, \phi) \sigma_z`.
Args:
phi (float): angle :math:`\phi` defining the unitary :math:`U_A(\phi)`
wires (Iterable): the wires ``n`` and ``m`` the circuit acts on
"""
n, m = wires
qml.CZ(wires=wires)
qml.CRot(-phi, np.pi, phi, wires=wires)
# decomposition of C-PhaseShift(2*phi) gate
qml.PhaseShift(-phi, wires=m)
qml.CNOT(wires=wires)
qml.PhaseShift(phi, wires=m)
qml.CNOT(wires=wires)
qml.PhaseShift(-phi, wires=n)
def CA_all():
"""Controlled application of all the unitary components A_l of the problem matrix A."""
# Controlled-A_1
qml.CNOT(wires=[ancilla_idx, 0])
qml.CZ(wires=[ancilla_idx, 1])
# Controlled-A2
qml.CNOT(wires=[ancilla_idx + 1, 0])
def random_circuit_stat(params, G=0, sequence=0, p=0, **kwargs):
for i in range(len(G.nodes)):
qml.RY(np.pi / 4, wires=i)
for j in range(p):
Random_unitary(params, G, sequence)
for i in range(len(G.nodes) - 1):
qml.CZ(wires=[i, i + 1])
return [qml.sample(qml.PauliZ(i)) for i in range(len(G.nodes))]
def random_circuit(params, G=0, sequence=0, p=0, **kwargs):
for i in range(len(G.nodes)):
qml.RY(np.pi / 4, wires=i)
for j in range(p):
Random_unitary(params, G, sequence)
for i in range(len(G.nodes) - 1):
qml.CZ(wires=[i, i + 1])
return qml.probs(wires=list(range(len(G.nodes))))
def Odd(thetaOdd):
""" Applies a set of RZ(theta) followed by CZ entanglement between every pair of qubits
"""
for wire in range(n_wires):
qml.RZ(thetaOdd[wire], wires=wire)
for i in range(n_wires):
for j in range(i + 1, n_wires):
qml.CZ(wires=[i, j])
def convert_cnots(tape):
for op in tape.operations + tape.measurements:
if op.name == "CNOT":
wires = op.wires
qml.Hadamard(wires=wires[0])
qml.CZ(wires=[wires[0], wires[1]])
else:
op.queue()
def Turing():
# distinct fun names in functional placeholders=
# []
qml.Hadamard(0)
qml.PauliX(1)
qml.PauliY(1)
qml.PauliZ(1)
qml.CNOT(wires=[0, 1])
qml.CZ(wires=[0, 1])
qml.SWAP(wires=[1, 0])
qml.RX(-6.283185307179586, wires=2)
qml.RY(-6.283185307179586, wires=2)
qml.RZ(-6.283185307179586, wires=2)
qml.PhaseShift(3.141592653589793, wires=1)
def rot(rad_ang_x, rad_ang_y, rad_ang_z):
"""
Returns
exp(1j*(rad_ang_x*sig_x + rad_ang_y*sig_y + rad_ang_z*sig_z))
where rad_ang_x is an angle in radians and sig_x is the x Pauli
matrix, etc.
Parameters
----------
rad_ang_x : float
rad_ang_y : float
rad_ang_z : float
Returns
-------
np.ndarray
"""
ty = np.complex128
mat = np.zeros([2, 2], dtype=ty)
vec = np.array([rad_ang_x, rad_ang_y, rad_ang_z])
n = np.linalg.norm(vec) # sqrt(dot(vec, vec.conj))
if abs(n) < 1e-8:
mat[0, 0] = 1
mat[1, 1] = 1
else:
nx = rad_ang_x / n
ny = rad_ang_y / n
nz = rad_ang_z / n
c = np.cos(n)
s = np.sin(n)
mat[0, 0] = c + 1j * s * nz
mat[0, 1] = s * ny + 1j * s * nx
mat[1, 0] = -s * ny + 1j * s * nx
mat[1, 1] = c - 1j * s * nz
return mat
qml.QubitUnitary(rot(-6.283185307179586, -6.283185307179586,
-6.283185307179586),
wires=0)
return qml.expval.Hermitian(hamil)
def my_transform(tape):
for op in tape.operations + tape.measurements:
if op.name == "CRX":
wires = op.wires
param = op.parameters[0]
qml.RX(param, wires=wires[1])
qml.RY(param / 2, wires=wires[1])
qml.CZ(wires=[wires[1], wires[0]])
else:
op.queue()
def parameterized_qubit_tape():
"""A parametrized qubit ciruit."""
a, b, c = 0.1, 0.2, 0.3
angles = np.array([0.4, 0.5, 0.6])
with qml.tape.QuantumTape() as tape:
qml.RX(a, wires=0)
qml.RX(b, wires=1)
qml.PauliZ(1)
qml.CNOT(wires=[0, 1]).inv()
qml.CRY(b, wires=[3, 1])
qml.RX(angles[0], wires=0)
qml.RX(4 * angles[1], wires=1)
qml.PhaseShift(17 / 9 * c, wires=2)
qml.RZ(b, wires=3)
qml.RX(angles[2], wires=2).inv()
qml.CRY(0.3589, wires=[3, 1]).inv()
qml.CSWAP(wires=[4, 2, 1]).inv()
qml.QubitUnitary(np.eye(2), wires=[2])
qml.ControlledQubitUnitary(np.eye(2), control_wires=[0, 1], wires=[2])
qml.MultiControlledX(control_wires=[0, 1, 2], wires=[3])
qml.Toffoli(wires=[0, 2, 1])
qml.CNOT(wires=[0, 2])
qml.PauliZ(wires=[1])
qml.PauliZ(wires=[1]).inv()
qml.CZ(wires=[0, 1])
qml.CZ(wires=[0, 2]).inv()
qml.CY(wires=[1, 2])
qml.CY(wires=[2, 0]).inv()
qml.CNOT(wires=[2, 1])
qml.CNOT(wires=[0, 2])
qml.SWAP(wires=[0, 2]).inv()
qml.CNOT(wires=[1, 3])
qml.RZ(b, wires=3)
qml.CSWAP(wires=[4, 0, 1])
qml.expval(qml.PauliY(0)),
qml.var(qml.Hadamard(wires=1)),
qml.sample(qml.PauliX(2)),
qml.expval(qml.Hermitian(np.eye(4), wires=[3, 4])),
return tape
def qfunc():
qml.CZ(wires=[0, 2])
qml.PauliZ(wires=2)
qml.S(wires=0)
qml.CNOT(wires=[0, 1])
qml.CRZ(0.5, wires=[0, 1])
qml.RZ(0.2, wires=2)
qml.T(wires=0)
qml.PauliZ(wires=0)