def __init__(self,
protocol='Bell_teleport',
device='qasm_simulator',
live=False,
qasm_sim=False,
noise_model=None,
shots=1024,
save_results=False,
directory=None): # QIP_Task initialisation function
# Stores protocol information
self.protocol = protocol
self.live = live
self.shots = shots
self.save_results = save_results
self.directory = directory
if device == 'qasm_simulator': # Defines settings for qasm_simulator use only
self.qasm_sim = False
self.backend = Aer.get_backend('qasm_simulator')
self.device = self.backend
self.coupling_map = None
if noise_model:
self.noise_model = noise_model
self.basis_gates = self.noise_model.basis_gates
else:
self.noise_model = None
self.basis_gates = None
else: # Defines settings for processor use
self.qasm_sim = qasm_sim
provider = IBMQ.get_provider(group='open')
self.device = provider.get_backend(device)
if save_results:
plot_error_map(self.device).savefig('{}/error_map.svg'.format(
self.directory),
format='svg')
if self.live: # Defines settings for live simulations
self.backend = self.device
self.coupling_map = None
self.noise_model = None
self.basis_gates = None
else: # Defines settings for artificial simulations
from qiskit.providers.aer.noise import NoiseModel
self.backend = Aer.get_backend('qasm_simulator')
self.properties = self.device.properties()
self.coupling_map = self.device.configuration().coupling_map
self.noise_model = NoiseModel.from_backend(self.properties)
self.basis_gates = self.noise_model.basis_gates
def get_gate_info(backend):
# Pull out the gates information.
gates=backend.properties().gates
#Cycle through the CX gate couplings to find the best and worst
cx_best_worst = [[[0,0],1],[[0,0],0]]
for n in range (0, len(gates)):
if gates[n].gate == "cx":
print(gates[n].name, ":", gates[n].parameters[0].name,"=", gates[n].parameters[0].value)
if cx_best_worst[0][1]>gates[n].parameters[0].value:
cx_best_worst[0][1]=gates[n].parameters[0].value
cx_best_worst[0][0]=gates[n].qubits
if cx_best_worst[1][1]<gates[n].parameters[0].value:
cx_best_worst[1][1]=gates[n].parameters[0].value
cx_best_worst[1][0]=gates[n].qubits
print("Best cx gate:", cx_best_worst[0][0], ",", round(cx_best_worst[0][1]*100,3),"%")
print("Worst cx gate:", cx_best_worst[1][0], ",", round(cx_best_worst[1][1]*100,3),"%")
display(plot_error_map(backend, show_title=True))
return(cx_best_worst)
for n in range(0, len(available_backends)):
backend = provider.get_backend(str(available_backends[n]))
print("{0:20} {1:<10}".format(backend.name(),
backend.configuration().n_qubits))
# Select a backend or go for the least busy backend with more than 1 qubits
backend_input = input("Enter the name of a backend, or X for the least busy:")
if backend_input not in ["X", "x"]:
backend = provider.get_backend(backend_input)
else:
backend = least_busy(
provider.backends(filters=lambda b: b.configuration().n_qubits > 1 and
b.status().operational))
# Display the gate and error map for the backend.
print("\nQubit data for backend:", backend.status().backend_name)
display(plot_gate_map(backend, plot_directed=True))
display(plot_error_map(backend))
# Create and transpile a 2 qubit Bell circuit
qc = QuantumCircuit(2)
qc.h(0)
qc.cx(0, 1)
display(qc.draw('mpl'))
qc_transpiled = transpile(qc, backend=backend, optimization_level=3)
display(qc_transpiled.draw('mpl'))
# Display the circuit layout for the backend.
display(plot_circuit_layout(qc_transpiled, backend, view='physical'))
def collisional_model(self,
backend='qasm_simulator',
live=False,
noise_model=None,
channel='amplitude_damping',
shots=1024,
measured_qubits=(),
max_collisions=5,
theta=np.pi / 2,
concurrence=False,
tangle=False,
witness=False,
tangle_witness=True,
markov=True,
print_results=True,
save_results=False,
directory=None,
full=True,
initial_statevector=np.array([0.5, 0.5])):
self.channel = channel
self.markov = markov
if self.state == 'h':
self.qc.h(0)
elif self.state == 'GHZ_teleport':
initial_state = initial_statevector
initial_state /= np.linalg.norm(initial_state)
self.qc.initialize(initial_state, [0])
self.theoretical_rho = np.outer(initial_state, initial_state)
self.GHZ([1, 2, 3])
elif self.state == 'D':
self.D()
if full:
self.theoretical_rho = self.full_theoretical_D(self.n, self.k)
else:
self.theoretical_rho = self.theoretical_D(self.n, self.k)
elif self.state == 'W':
self.W()
if full:
self.theoretical_rho = self.full_theoretical_D(self.n, self.k)
else:
self.theoretical_rho = self.theoretical_D(self.n, self.k)
elif self.state == 'GHZ':
self.GHZ(range(self.n))
if full:
self.theoretical_rho = self.full_theoretical_GHZ(self.n)
else:
self.theoretical_rho = self.theoretical_GHZ(self.n)
self.histogram_data = []
self.directory = directory
if backend == 'qasm_simulator':
self.backend = Aer.get_backend('qasm_simulator')
self.coupling_map = None
if noise_model:
self.noise_model = noise_model
self.basis_gates = self.noise_model.basis_gates
else:
self.noise_model = None
self.basis_gates = None
else:
provider = IBMQ.get_provider(group='open')
self.device = provider.get_backend(backend)
self.properties = self.device.properties()
self.coupling_map = self.device.configuration().coupling_map
self.noise_model = noise.device.basic_device_noise_model(
self.properties)
self.basis_gates = self.noise_model.basis_gates
if save_results:
visual.plot_error_map(self.device).savefig(
'{}/error_map.png'.format(self.directory))
if live:
check = input(
"Are you sure you want to run the circuit live? [y/n]: ")
if check == 'y' or check == 'yes':
self.backend = self.device
else:
self.backend = Aer.get_backend('qasm_simulator')
else:
self.backend = Aer.get_backend('qasm_simulator')
self.unitary_backend = Aer.get_backend('unitary_simulator')
self.shots = shots
if self.state == 'GHZ_teleport':
self.a = 3
self.b = 3
elif measured_qubits == ():
self.a = 0
self.b = self.n - 1
else:
self.a = measured_qubits[0]
self.b = measured_qubits[1]
self.max_collisions = max_collisions
self.theta = theta
if self.max_collisions > 0:
if self.channel == 'phase_damping_one_qubit':
self.ancilla = QuantumRegister(1, 'a')
self.qc.add_register(self.ancilla)
elif not markov:
self.ancilla = QuantumRegister(3, 'a')
self.qc.add_register(self.ancilla)
self.qc.h(self.ancilla[2])
self.qc.cx(self.ancilla[2], self.ancilla[1])
self.qc.cx(self.ancilla[1], self.ancilla[0])
else:
self.ancilla = QuantumRegister(self.max_collisions, 'a')
self.qc.add_register(self.ancilla)
if self.channel == 'amplitude_damping':
self.U = self.amplitude_damping_operator(full)
elif self.channel == 'phase_damping' or 'phase_damping_one_qubit':
self.U = self.phase_damping_operator(full)
elif self.channel == 'heisenberg':
print('Not yet programmed')
quit()
self.U = self.heisenberg_operator()
if tangle_witness:
self.tangle_witness_GHZ = 3 / 4 * np.kron(np.kron(
I, I), I) - self.full_theoretical_GHZ(3)
self.tangle_witness_tri = 1 / 2 * np.kron(np.kron(
I, I), I) - self.full_theoretical_GHZ(3)
counts_list = []
rho_list = []
theoretical_rho_list = []
concurrence_list = []
theoretical_concurrence_list = []
tangle_ub_list = []
tangle_lb_list = []
theoretical_tangle_list = []
fidelity_list = []
witness_list = []
tangle_witness_GHZ_list = []
tangle_witness_tri_list = []
trace_squared_list = []
for k in range(self.max_collisions + 1):
if k > 0:
self.collision(k)
if witness:
counts = self.measure(witness)
else:
rho = self.tomography(full)
self.evolve_theoretical_rho(full)
else:
if witness:
counts = 1 / 2
else:
rho = self.tomography(full)
if save_results:
visual.plot_state_city(rho).savefig(
'{}/state_city_{}.png'.format(self.directory, k))
visual.plot_state_paulivec(rho).savefig(
'{}/paulivec_{}.png'.format(self.directory, k))
if witness:
counts_list.append(counts)
else:
rho_list.append(rho)
theoretical_rho_list.append(self.theoretical_rho)
if not full and self.state != 'GHZ_teleport':
C = self.concurrence(rho)
concurrence_list.append(C)
TC = self.concurrence(self.theoretical_rho)
theoretical_concurrence_list.append(TC)
if tangle:
T_ub = self.tangle_ub(rho)
tangle_ub_list.append(T_ub)
#T_lb = self.tangle_lb(rho)
#tangle_lb_list.append(T_lb)
if self.state == 'GHZ':
TT = np.exp(np.log(np.cos(self.theta)) * k)
theoretical_tangle_list.append(TT)
F = state_fidelity(theoretical_rho_list[0], rho)
fidelity_list.append(F)
if witness:
W = np.real(
np.trace(
np.matmul(self.full_theoretical_GHZ(self.n), rho)))
witness_list.append(W)
if tangle_witness and full:
TWGHZ = np.real(
np.trace(np.matmul(self.tangle_witness_GHZ, rho)))
tangle_witness_GHZ_list.append(TWGHZ)
TWtri = np.real(
np.trace(np.matmul(self.tangle_witness_tri, rho)))
tangle_witness_tri_list.append(TWtri)
Tr2 = np.real(np.trace(np.matmul(rho, rho)))
trace_squared_list.append(Tr2)
if print_results:
print("Collision Number:", k)
print("Original Density Matrix:")
print(theoretical_rho_list[0])
print("Theoretical Density Matrix:")
print(self.theoretical_rho)
print("Measured Density Matrix:")
print(rho)
print("Trace:", np.real(np.trace(rho)))
print("Trace Squared:", Tr2)
if concurrence:
print("Concurrence:", C)
print("Theoretical Concurrence:", TC)
if tangle:
print("Tangle Upper Bound:", T_ub)
#print("Tangle Lower Bound:", T_lb)
print("Theoretical Tangle:", TT)
print("Fidelity:", F)
if witness:
print("Witness:", W)
if tangle_witness and full:
print("GHZ Tangle Witness:", TWGHZ)
print("Tripartite Tangle Witness:", TWtri)
print("Eigenvalues:",
np.sort(np.real(np.linalg.eigvals(rho)))[::-1])
print(
"\n-----------------------------------------------------------------------------------\n"
)
if print_results:
if save_results:
visual.circuit_drawer(
self.qc,
filename='{}/constructed_circuit.png'.format(
self.directory),
output='mpl')
else:
print(self.qc)
print("Constructed Circuit Depth: ", self.qc.depth())
try:
transpiled_qc = transpile(self.qc,
self.device,
optimization_level=3)
if save_results:
visual.circuit_drawer(
transpiled_qc,
filename='{}/transpiled_circuit.png'.format(
self.directory),
output='mpl')
print("Transpiled Circuit Depth: ", self.qc.depth())
except:
pass
print()
if save_results:
visual.plot_histogram(
self.histogram_data, title=self.state).savefig(
'{}/histogram.png'.format(self.directory))
return counts_list, theoretical_rho_list, rho_list, theoretical_concurrence_list, concurrence_list, \
theoretical_tangle_list, tangle_ub_list, tangle_lb_list, fidelity_list, witness_list, \
tangle_witness_GHZ_list, tangle_witness_tri_list, trace_squared_list
" ",
link[10], " ", link[9], "\n"
" | |\n"
" ",
value_q[9], " -- ", link[8], " -- ", value_q[8], " -- ", link[7],
" -- ", value_q[7])
return 0
calculus_differencial(value_q)
print("Value qubits : ", value_q)
if backend_sim == quantum_computer:
plot_error_map(quantum_computer)
qubit_decoherence = nb_qubits
value_decoherence = [0, 0, 0, 0, 0]
for i in range(0, nb_qubits):
if i % 2 == 0:
value_decoherence[qubit_decoherence - 10] = (
(value_q[qubit_decoherence] - value_q[i]) +
(value_q[qubit_decoherence] - value_q[i + 1])) / 512
print("q", i, "[", value_q[qubit_decoherence], "-", value_q[i],
"] + q", i + 1, "[", value_q[qubit_decoherence], "-",
value_q[i + 1], "] => ",
(value_q[qubit_decoherence] - value_q[i]) +
(value_q[qubit_decoherence] - value_q[i + 1]), "/ 512 = ",
value_decoherence[qubit_decoherence - 10])
qubit_decoherence += 1
