plot_now(experiment, theory, parameter_space, do_fit=False)
# Close hardware
dac.zero()
# Normalize, save and return data
#data=data/np.amax(data)
experiment_filename, theory_filename, param_filename = get_filenames(heater_index)
np.save(experiment_filename, experiment)
np.save(theory_filename, theory)
np.save(param_filename, parameter_space)
return experiment_filename, theory_filename, param_filename
start_time=timestamp()
device=lo.beamsplitter_network(json='cnot_mz.json')
simulator=lo.simulator(device, nphotons=2)
simulator.set_input_state([1,3])
simulator.set_visibility(0.95)
dac=dac.dac()
fpga=fpga()
fpga.read()
fpga.read()
fpga.read()
fpga.read()
table=calibration_table()
heater_index = 5
#hold_table=[[0,pi/2],[2,0], [6,pi/2]]
hold_table=list(enumerate([0,pi/2,0,0,0,0,0,pi/2]))
# Normalize, save and return data
#data=data/np.amax(data)
experiment_filename, theory_filename, param_filename, hold_table_filename = get_filenames(
heater_index)
file = open(hold_table_filename, "w")
file.write(str(hold_table))
file.close()
np.save(experiment_filename, experiment)
np.save(theory_filename, theory)
np.save(param_filename, parameter_space)
return experiment_filename, theory_filename, param_filename
start_time = timestamp()
device = lo.beamsplitter_network(json='cnot_mz.json')
simulator = lo.simulator(device, nphotons=2)
simulator.set_input_state([1, 3])
simulator.set_visibility(0.99)
dac = dac.dac()
fpga = fpga()
fpga.read()
fpga.read()
fpga.read()
fpga.read()
table = calibration_table()
heater_index = 6
#hold_table=[[0,pi/2],[2,0], [6,pi/2]]
hold_table = list(enumerate([pi, 0, 0, 0, 0, 0, 0, 0]))
import numpy as np
from qy.simulation import linear_optics as lo
'''
Test our code with some HOM dips
'''
# Build a BS and a two-photon basis
basis=lo.basis(2,2)
device=lo.beamsplitter_network(json='devices/beamsplitter.json')
# Draw it
device.draw('devices/beamsplitter.pdf')
# Start a simulator
simulator=lo.simulator(device, basis)
# Set the input state and get some probabilities
input_state=basis.get_state([0,1])
print 'INPUT:', input_state
simulator.set_input_state(input_state)
print simulator.get_probability_quantum([0,0])
print simulator.get_probability_quantum([0,1])
print simulator.get_probability_classical([0,1])
# Let's try a few different input states
for input_modes in [[0,1], [0,0], [1,1]]:
input_state=basis.get_state(input_modes)
simulator.set_input_state(input_state)
print '\nINPUT:', str(input_state).strip()