def build_super_layers(self):
super_layers_all = tq.QuantumModuleList()
super_layers_all.append(
tq.Super1QLayer(op=tq.SHadamard, n_wires=self.n_wires))
for k in range(self.arch['n_blocks']):
super_layers_all.append(
tq.Super1QLayer(op=tq.RX,
n_wires=self.n_wires,
has_params=True,
trainable=True))
super_layers_all.append(
tq.Super1QLayer(op=tq.RY,
n_wires=self.n_wires,
has_params=True,
trainable=True))
super_layers_all.append(
tq.Super1QLayer(op=tq.RZ,
n_wires=self.n_wires,
has_params=True,
trainable=True))
super_layers_all.append(
tq.Super2QAlterLayer(op=tq.CZ,
n_wires=self.n_wires,
jump=1))
return super_layers_all
def __init__(self, n_wires, arch):
super().__init__()
self.n_wires = n_wires
self.arch = arch
self.super_layers_all = tq.QuantumModuleList()
self.n_blocks = arch['n_blocks']
self.n_layers_per_block = arch['n_layers_per_block']
self.n_front_share_blocks = arch['n_front_share_blocks']
for k in range(self.n_blocks):
self.super_layers_all.append(
tq.Super1QLayer(op=tq.RX,
n_wires=self.n_wires,
has_params=True,
trainable=True))
self.super_layers_all.append(
tq.Super1QLayer(op=tq.RY,
n_wires=self.n_wires,
has_params=True,
trainable=True))
self.super_layers_all.append(
tq.Super1QLayer(op=tq.RZ,
n_wires=self.n_wires,
has_params=True,
trainable=True))
self.super_layers_all.append(
tq.Super2QAllLayer(op=tq.CRX,
n_wires=self.n_wires,
has_params=True,
trainable=True,
jump=1,
circular=True))
self.super_layers_all.append(
tq.Super2QAllLayer(op=tq.CRY,
n_wires=self.n_wires,
has_params=True,
trainable=True,
jump=1,
circular=True))
self.super_layers_all.append(
tq.Super2QAllLayer(op=tq.CRZ,
n_wires=self.n_wires,
has_params=True,
trainable=True,
jump=1,
circular=True))
self.sample_n_blocks = None
def build_super_layers(self):
super_layers_all = tq.QuantumModuleList()
for k in range(self.arch['n_blocks']):
super_layers_all.append(
tq.Super1QLayer(op=tq.RX,
n_wires=self.n_wires,
has_params=True,
trainable=True))
super_layers_all.append(
tq.Super1QLayer(op=tq.S, n_wires=self.n_wires))
super_layers_all.append(
tq.Super2QAllLayer(op=tq.CNOT,
n_wires=self.n_wires,
jump=1,
circular=True))
super_layers_all.append(
tq.Super1QLayer(op=tq.RY,
n_wires=self.n_wires,
has_params=True,
trainable=True))
super_layers_all.append(
tq.Super1QLayer(op=tq.T, n_wires=self.n_wires))
super_layers_all.append(
tq.Super2QAllLayer(op=tq.SWAP,
n_wires=self.n_wires,
jump=1,
circular=True))
super_layers_all.append(
tq.Super1QLayer(op=tq.RZ,
n_wires=self.n_wires,
has_params=True,
trainable=True))
super_layers_all.append(
tq.Super1QLayer(op=tq.T, n_wires=self.n_wires))
super_layers_all.append(
tq.Super2QAllLayer(op=tq.SSWAP,
n_wires=self.n_wires,
jump=1,
circular=True))
super_layers_all.append(
tq.Super1QLayer(op=tq.U1,
n_wires=self.n_wires,
has_params=True,
trainable=True))
super_layers_all.append(
tq.Super2QAllLayer(op=tq.CU3,
n_wires=self.n_wires,
has_params=True,
trainable=True,
jump=1,
circular=True))
return super_layers_all