def random_tiling(n_qubits, depth=3, gateset=None, seed=None):
""" Returns a random Euler decomposition if n_qubits == 1,
otherwise returns a random tiling with the given depth and gateset.
>>> from discopy.quantum.gates import CX, H, T, Rx, Rz
>>> c = random_tiling(1, seed=420)
>>> print(c)
Rx(0.0263) >> Rz(0.781) >> Rx(0.273)
>>> print(random_tiling(2, 2, gateset=[CX, H, T], seed=420))
CX >> T @ Id(1) >> Id(1) @ T
>>> print(random_tiling(3, 2, gateset=[CX, H, T], seed=420))
CX @ Id(1) >> Id(2) @ T >> H @ Id(2) >> Id(1) @ H @ Id(1) >> Id(2) @ H
>>> print(random_tiling(2, 1, gateset=[Rz, Rx], seed=420))
Rz(0.673) @ Id(1) >> Id(1) @ Rx(0.273)
"""
from discopy.quantum.gates import H, CX, Rx, Rz, Parametrized
gateset = gateset or [H, Rx, CX]
if seed is not None:
random.seed(seed)
if n_qubits == 1:
phases = [random.random() for _ in range(3)]
return Rx(phases[0]) >> Rz(phases[1]) >> Rx(phases[2])
result = Id(n_qubits)
for _ in range(depth):
line, n_affected = Id(0), 0
while n_affected < n_qubits:
gate = random.choice(
gateset if n_qubits - n_affected > 1 else
[g for g in gateset if g is Rx or g is Rz or len(g.dom) == 1])
if isinstance(gate, type) and issubclass(gate, Parametrized):
gate = gate(random.random())
line = line @ gate
n_affected += len(gate.dom)
result = result >> line
return result
def box_from_tk(tk_gate):
name = tk_gate.op.type.name
if name == 'Rx':
return Rx(tk_gate.op.params[0] / 2)
if name == 'Rz':
return Rz(tk_gate.op.params[0] / 2)
if name == 'CRz':
return CRz(tk_gate.op.params[0] / 2)
for gate in GATES:
if name == gate.name:
return gate
raise NotImplementedError
def __init__(self, n_qubits, params):
from discopy.quantum.gates import H, Rx, Rz, CRz
def layer(thetas):
hadamards = Id(0).tensor(*(n_qubits * [H]))
rotations = Id(n_qubits).then(*(
Id(i) @ CRz(thetas[i]) @ Id(n_qubits - 2 - i)
for i in range(n_qubits - 1)))
return hadamards >> rotations
if n_qubits == 1:
circuit = Rx(params[0]) >> Rz(params[1]) >> Rx(params[2])
elif len(Tensor.np.shape(params)) != 2\
or Tensor.np.shape(params)[1] != n_qubits - 1:
raise ValueError(
"Expected params of shape (depth, {})".format(n_qubits - 1))
else:
depth = Tensor.np.shape(params)[0]
circuit = Id(n_qubits).then(*(
layer(params[i]) for i in range(depth)))
super().__init__(
circuit.dom, circuit.cod, circuit.boxes, circuit.offsets)