import pennylane as qml
from ttn import ttn_circuit
from gates import two_qubit_gate
from hamiltonians import tfi_chain
num_qubits = 8
# The simulator.
dev = qml.device('default.qubit', wires=num_qubits, analytic=True)
# The TFI model at the critical point.
h = 1.0
periodic = False
H = tfi_chain(num_qubits, h, periodic=periodic)
print(H)
# The TTN circuit.
fix_layers = False
ansatz = ttn_circuit(num_qubits, two_qubit_gate, fix_layers=fix_layers)
# The circuit for computing the expectation value of H.
cost_fn = qml.ExpvalCost(ansatz, H, dev, optimize=True)
num_params_per_gate = 15 # The number of parameters in each two-qubit gate.
depth = int(np.floor(np.log2(num_qubits))) # The depth of the TTN.
num_gates = num_qubits - 1 # The number of two-qubit gates in the TTN.
if fix_layers:
num_params = num_params_per_gate * depth
else:
from pennylane import numpy as np
import matplotlib.pyplot as plt
from mera import mera_circuit, get_num_mera_gates
from hamiltonians import tfi_chain
num_samples = 200
qubits = [2, 4, 8]
variances = []
np.random.seed(1)
h = 1.0
periodic = False
fix_layers = True
for num_qubits in qubits:
H = tfi_chain(num_qubits, h)
grad_vals = []
for i in range(num_samples):
print(f"num_qubits {num_qubits}, step {i}")
dev = qml.device("default.qubit", wires=num_qubits)
ansatz = mera_circuit(num_qubits, periodic, fix_layers)
cost_fn = qml.ExpvalCost(ansatz, H, dev)
grad = qml.grad(cost_fn)
num_params_per_gate = 15
num_gates = get_num_mera_gates(num_qubits, periodic, fix_layers)
num_params = num_params_per_gate * num_gates
params = np.pi * (np.random.rand(num_params) - 1.0)
gradient = np.array(grad(params)[0])
grad_vals.append(gradient)
print(f" +++ {init} +++")
mod_ansatz = ansatz
if init in ["Random |+...+>", "Zero |+...+>"]:
@qml.template
def ansatz_plus(params, wires):
for q in range(num_qubits):
qml.Hadamard(q)
ansatz(params, wires)
mod_ansatz = ansatz_plus
for h in hs:
print(f" ||| h={h} |||")
H = tfi_chain(num_qubits, h, g=g)
grad_vals = []
cost_fn = qml.ExpvalCost(mod_ansatz, H, dev, optimize=True)
grad = qml.grad(cost_fn)
# Use the same random numbers for each set of parameters/ansatz.
np.random.seed(seed)
for i in range(num_samples):
if init in ["Zero |0...0>", "Zero |+...+>"]:
params = np.zeros(num_params)
else:
params = np.pi * (np.random.rand(num_params) - 1.0)
if "HEA" in ansatz_name:
params = np.reshape(params, (len(params) // 3, 3))
import numpy as np
import pennylane as qml
from ttn import ttn_circuit
from mera import mera_circuit, get_num_mera_gates, arb_qubit_gate
from hea import hea_circuit
from gates import two_qubit_gate, simple_two_qubit_gate1, simple_two_qubit_gate2
from hamiltonians import tfi_chain
num_qubits = int(args.N)
# The simulator.
dev = qml.device('default.qubit', wires=num_qubits)
# The TFI model at the critical point.
h = float(args.h)
H = tfi_chain(num_qubits, h, periodic=args.periodic)
print(H)
if args.two_qubit == "two_qubit":
unitary_parameterization = two_qubit_gate
num_params_per_gate = 15
elif args.two_qubit == "simple6":
unitary_parameterization = simple_two_qubit_gate1
num_params_per_gate = 6
elif args.two_qubit == "simple2":
unitary_parameterization = simple_two_qubit_gate2
num_params_per_gate = 2
elif args.two_qubit == "arbitrary":
unitary_parameterization = arb_qubit_gate
num_params_per_gate = 15
else:
import numpy as np
import pennylane as qml
from ttn import ttn_circuit
from mera import mera_circuit, get_num_mera_gates, arb_qubit_gate
from hea import hea_circuit
from gates import two_qubit_gate, simple_two_qubit_gate1, simple_two_qubit_gate2
from hamiltonians import tfi_chain
from observables import sigma_z, sigma_x
num_qubits = int(args.N)
# The simulator.
dev = qml.device('default.qubit', wires=num_qubits, analytic=True)
h = float(args.h)
H = tfi_chain(num_qubits, h, periodic=False)
sz = sigma_z(num_qubits)
sx = sigma_x(num_qubits)
print(H)
print("----")
print(sz)
print("----")
print(sx)
# The TFI model at the critical point.
if args.two_qubit == "two_qubit":
unitary_parameterization = two_qubit_gate
num_params_per_gate = 15
elif args.two_qubit == "simple6":
unitary_parameterization = simple_two_qubit_gate1
