def test_with_model(self):
model = SpinChainModel(3, setup="linear")
processor = OptPulseProcessor(3, model=model)
qc = QubitCircuit(3)
qc.add_gate("CNOT", 1, 0)
qc.add_gate("X", 2)
processor.load_circuit(qc,
merge_gates=True,
num_tslots=10,
evo_time=2.0)
init_state = qutip.rand_ket(8, dims=[[2, 2, 2], [1, 1, 1]])
num_result = processor.run_state(init_state=init_state).states[-1]
ideal_result = qc.run(init_state)
assert (pytest.approx(qutip.fidelity(num_result, ideal_result),
1.0e-5) == 1.0)
def test_simple_hadamard(self):
"""
Test for optimizing a simple hadamard gate
"""
N = 1
H_d = sigmaz()
H_c = sigmax()
qc = QubitCircuit(N)
qc.add_gate("SNOT", 0)
# test load_circuit, with verbose info
num_tslots = 10
evo_time = 10
test = OptPulseProcessor(N, drift=H_d)
test.add_control(H_c, targets=0)
tlist, coeffs = test.load_circuit(qc,
num_tslots=num_tslots,
evo_time=evo_time,
verbose=True)
# test run_state
rho0 = qubit_states(1, [0])
plus = (qubit_states(1, [0]) + qubit_states(1, [1])).unit()
result = test.run_state(rho0)
assert_allclose(fidelity(result.states[-1], plus), 1, rtol=1.0e-6)
# Optimal control model
setting_args = {
"SNOT": {
"num_tslots": 6,
"evo_time": 2
},
"X": {
"num_tslots": 1,
"evo_time": 0.5
},
"CNOT": {
"num_tslots": 12,
"evo_time": 5
}
}
opt_processor = OptPulseProcessor(num_qubits=num_qubits,
model=SpinChainModel(3, setup="linear"))
opt_processor.load_circuit( # Provide parameters for the algorithm
dj_circuit,
setting_args=setting_args,
merge_gates=False,
verbose=True,
amp_ubound=5,
amp_lbound=0)
initial_state = basis([2, 2, 2], [0, 0, 0])
result3 = opt_processor.run_state(initial_state)
# For plotting
width = TEXTWIDTH / 3
fig, ax = opt_processor.plot_pulses(figsize=(width, width * 3 / 2.9), dpi=200)
ax[0].set_ylabel(r"$\Omega^x_{0}$")
def test_multi_gates(self):
N = 2
H_d = tensor([sigmaz()] * 2)
H_c = []
test = OptPulseProcessor(N)
test.add_drift(H_d, [0, 1])
test.add_control(sigmax(), cyclic_permutation=True)
test.add_control(sigmay(), cyclic_permutation=True)
test.add_control(tensor([sigmay(), sigmay()]))
# qubits circuit with 3 gates
setting_args = {
"SNOT": {
"num_tslots": 10,
"evo_time": 1
},
"SWAP": {
"num_tslots": 30,
"evo_time": 3
},
"CNOT": {
"num_tslots": 30,
"evo_time": 3
}
}
qc = QubitCircuit(N)
qc.add_gate("SNOT", 0)
qc.add_gate("SWAP", targets=[0, 1])
qc.add_gate('CNOT', controls=1, targets=[0])
test.load_circuit(qc, setting_args=setting_args, merge_gates=False)
rho0 = rand_ket(4) # use random generated ket state
rho0.dims = [[2, 2], [1, 1]]
U = gate_sequence_product(qc.propagators())
rho1 = U * rho0
result = test.run_state(rho0)
assert_(fidelity(result.states[-1], rho1) > 1 - 1.0e-6)
def test_multi_qubits(self):
"""
Test for multi-qubits system.
"""
N = 3
H_d = tensor([sigmaz()] * 3)
H_c = []
# test empty ctrls
num_tslots = 30
evo_time = 10
test = OptPulseProcessor(N)
test.add_drift(H_d, [0, 1, 2])
test.add_control(tensor([sigmax(), sigmax()]), cyclic_permutation=True)
# test periodically adding ctrls
sx = sigmax()
iden = identity(2)
assert (len(test.get_control_labels()) == 3)
test.add_control(sigmax(), cyclic_permutation=True)
test.add_control(sigmay(), cyclic_permutation=True)
# test pulse genration for cnot gate, with kwargs
qc = [tensor([identity(2), cnot()])]
test.load_circuit(qc,
num_tslots=num_tslots,
evo_time=evo_time,
min_fid_err=1.0e-6)
rho0 = qubit_states(3, [1, 1, 1])
rho1 = qubit_states(3, [1, 1, 0])
result = test.run_state(rho0, options=SolverOptions(store_states=True))
assert_(fidelity(result.states[-1], rho1) > 1 - 1.0e-6)