def city(statevector):
dark_style(False)
figure = plot_state_city(statevector)
figure.savefig(temppath('density_matrix_cityscape_light.png'))
dark_style(True)
figure = plot_state_city(statevector)
figure.savefig(temppath('density_matrix_cityscape_dark.png'))
def process_results(qc, result):
if result.backend_name in 'statevector_simulator':
statevector = result.get_statevector(qc)
logger.info("State vector is\n{0}".format(statevector))
logger.debug("Plotting")
from qiskit.tools.visualization import plot_state_city
plot_state_city(statevector)
elif result.backend_name in 'unitary_simulator':
unitary = result.get_unitary(qc)
logger.info("Circuit unitary is:\n{0}".format(unitary))
else: # For qasm and real devices
counts = result.get_counts(qc)
logger.info("{0} results: \n {1}".format(len(counts), counts))
logger.info("Time taken {}".format(result.time_taken))
max_val = max(counts.values())
max_val_status = max(counts, key=lambda key: counts[key])
logger.info(
"Max value is {0} ({2:4.2f} accuracy) for status {1}".format(
max_val, max_val_status, max_val / 8192))
logger.debug("Plotting")
from qiskit.tools.visualization import plot_histogram
plot_histogram(counts)
circ.draw(output='mpl')
# Import Aer
from qiskit import BasicAer
# Run the quantum circuit on a statevector simulator backend
backend = BasicAer.get_backend('statevector_simulator')
# Create a Quantum Program for execution
job = execute(circ, backend)
result = job.result()
outputstate = result.get_statevector(circ, decimals=3)
print(outputstate)
from qiskit.tools.visualization import plot_state_city
plot_state_city(outputstate)
# Run the quantum circuit on a unitary simulator backend
backend = BasicAer.get_backend('unitary_simulator')
job = execute(circ, backend)
result = job.result()
# Show the results
print(result.get_unitary(circ, decimals=3))
# Add a CX (CNOT) gate on control qubit 0 and target qubit 1
circuit.cx(0, 1)
circuit.t(0)
#circuit.measure_all()
# Execute the circuit on the statevector simulator
job = execute(circuit, simulator)
# Grab results from the job
result = job.result()
statevector = result.get_statevector(circuit)
plot_bloch_multivector(statevector, title='Bloch sphere')
plot_state_city(statevector, title='State vector')
print(statevector)
# Returns counts
counts = result.get_counts(circuit)
print("\nCounts:",counts)
# Draw the circuit
circ_plt = circuit.draw(output='mpl')
plt.show(block=False)
print(circuit.draw(output='text'))
# Plot a histogram
fig = plot_histogram(counts)
plt.show(block=True)
circuit.cx(3, 5)
circuit.barrier()
# Perform Bell state measurement
circuit.cx(1, 3)
circuit.cx(0, 2)
circuit.h(1)
circuit.h(0)
circuit.measure([0, 1, 2, 3], [0, 1, 2, 3])
# Operate on Bob's qubit given result
circuit.cx(3, 4)
circuit.cz(0, 4)
circuit.cx(2, 5)
circuit.cz(1, 5)
circuit.barrier()
# Do the reverse things on Bob's qubit
apply_secret_unitary(secret_0, 4, circuit, True)
apply_secret_unitary(secret_1, 5, circuit, True)
# Measure Bob's qubit
circuit.measure([4, 5], [4, 5])
print(circuit)
# Simulate circuit
simulator = Aer.get_backend('statevector_simulator')
result = execute(circuit, backend=simulator).result()
statevector = result.get_statevector(circuit)
plot_state_city(statevector)
q = QuantumRegister(3, 'q')
circ = QuantumCircuit(q)
#Add a H gate (Hammard gate) in qbit 0,
#putting this qbit in superposition
circ.h(q[0])
#Add CX (CNOT) gate on control of qbit 0 and target qbit 1, putting
#the qbits in a Bell state
circ.cx(q[0], q[1])
#Add CX (CNOT) gate on control of qbit 0 and target qbit 1, putting
#the qbits in a GHZ state
circ.cx(q[0], q[2])
circ.draw(output='mpl')
backend = BasicAer.get_backend('statevector_simulator')
job = execute(circ, backend)
result = job.result()
outputstate = result.get_statevector(circ, decimals=3)
print(plot_state_city(outputstate))