def take_data(self):
####
if self.cfg["visdom_plot_livedata"]:
viz = visdom.Visdom()
assert viz.check_connection(), "Visdom server not connected!"
# added two environments "seq_builder.json", and "live_plot.json" in C:\Users\slab\.visdom
eid = "live_plot"
viz.close(win=None, env=eid)
win1 = viz.line( X=np.arange(0, 1), Y=np.arange(0, 1), env=eid,
opts=dict(height=400, width=700, title='expt_avg_data', showlegend=True, xlabel='expt_pts'))
win2 = viz.line( X=np.arange(0, 1), Y=np.arange(0, 1), env=eid,
opts=dict(height=400, width=700, title='expt_avg_data2', showlegend=True, xlabel='expt_pts'))
win3 = viz.line( X=np.arange(0, 1), Y=np.arange(0, 1), env=eid,
opts=dict(height=400, width=700, title='single_record (of only first run)', showlegend=True, xlabel='time ns'))
win4 = viz.scatter(X=array([[1,2,3],[1,2,3]]).transpose(), env=eid,
opts=dict(height=400, width=700, title='g/e/f cal single shot', showlegend=True, xlabel=''))
####
if self.pre_run is not None:
self.pre_run()
TEST_REDPITAYA = False
if TEST_REDPITAYA:
self.awg_run()
if not TEST_REDPITAYA:
if self.adc == None:
print("Prep Card")
adc = Alazar(self.cfg['alazar'])
else:
adc = self.adc
# debug_alazer = False
# if debug_alazer:
#
# # save raw time trace, 100 runs only
# tpts, single_data1, single_data2 = adc.acquire_singleshot_data2()
#
# self.slab_file = self.datafile(data_file=self.data_file)
# with self.slab_file as f:
# f.add('tpts', tpts)
# f.add('single_data1', single_data1)
# f.add('single_data2', single_data2)
# f.close()
#
# # hack for post_run
# expt_avg_data = self.expt_pts
#
# else:
if not self.cfg['readout']['save_single-shot_data']:
expt_data = None
current_data = None
for ii in tqdm(arange(max(1, self.cfg[self.expt_cfg_name]['averages'] / 100))):
tpts, ch1_pts, ch2_pts = adc.acquire_avg_data_by_record(prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'])
if not self.cfg[self.expt_cfg_name]['use_pi_calibration']:
if expt_data is None:
if self.cfg['readout']['channel'] == 1:
expt_data = ch1_pts
elif self.cfg['readout']['channel'] == 2:
expt_data = ch2_pts
else:
if self.cfg['readout']['channel'] == 1:
expt_data = (expt_data * ii + ch1_pts) / (ii + 1.0)
elif self.cfg['readout']['channel'] == 2:
expt_data = (expt_data * ii + ch2_pts) / (ii + 1.0)
if self.cfg['readout']['heterodyne_freq'] == 0:
# homodyne
expt_avg_data = mean(expt_data, 1)
else:
# heterodyne
heterodyne_freq = self.cfg['readout']['heterodyne_freq']
# ifft by numpy default has the correct 1/N normalization
expt_data_fft_amp = np.abs(np.fft.ifft(expt_data))
hetero_f_ind = int(round(heterodyne_freq * tpts.size * 1e-9)) # position in ifft
# todo: do the proper sum here
# expt_avg_data = np.average(expt_data_fft_amp[:, (hetero_f_ind - 1):(hetero_f_ind + 1)], axis=1)
expt_avg_data = expt_data_fft_amp[:, hetero_f_ind]
else:
# average first, then divide by pi_calibration values
if expt_data is None:
if self.cfg['readout']['channel'] == 1:
expt_data = ch1_pts[:-2]
zero_amp_curr = mean(ch1_pts[-2])
pi_amp_curr = mean(ch1_pts[-1])
elif self.cfg['readout']['channel'] == 2:
expt_data = ch2_pts[:-2]
zero_amp_curr = mean(ch2_pts[-2])
pi_amp_curr = mean(ch2_pts[-1])
zero_amp = zero_amp_curr
pi_amp = pi_amp_curr
else:
if self.cfg['readout']['channel'] == 1:
expt_data = (expt_data * ii + ch1_pts[:-2]) / (ii + 1.0)
zero_amp_curr = mean(ch1_pts[-2])
pi_amp_curr = mean(ch1_pts[-1])
elif self.cfg['readout']['channel'] == 2:
expt_data = (expt_data * ii + ch2_pts[:-2]) / (ii + 1.0)
zero_amp_curr = mean(ch2_pts[-2])
pi_amp_curr = mean(ch2_pts[-1])
zero_amp = (zero_amp * ii + zero_amp_curr) / (ii + 1.0)
pi_amp = (pi_amp * ii + pi_amp_curr) / (ii + 1.0)
# todo: add heterodyne with pi_cal
expt_avg_data = mean((expt_data - zero_amp) / (pi_amp - zero_amp), 1)
# self.slab_file = self.datafile(data_file=self.data_file)
with self.slab_file as f:
f.add('expt_2d', expt_data)
f.add('expt_avg_data', expt_avg_data)
f.add('expt_pts', self.expt_pts)
# save pi_cal amps, to be able to monitor fluctuations
if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
f.append_pt('zero_amps', zero_amp_curr)
f.append_pt('pi_amps', pi_amp_curr)
f.close()
else: # here saves all single shot data
if self.prefix == 'Vacuum_Rabi':
print('vacuum_rabi')
het_IFreqList = [self.cfg['readout']['heterodyne_freq']]
het_read_freq_list = [0]
elif self.cfg['readout']['is_multitone_heterodyne']:
het_carrier_freq = self.cfg['readout']['heterodyne_carrier_freq']
het_read_freq_list = array(self.cfg['readout']['heterodyne_freq_list'])
het_IFreqList = het_read_freq_list - het_carrier_freq
else:
het_carrier_freq = self.readout_freq - self.cfg['readout']['heterodyne_freq']
het_read_freq_list = array([self.readout_freq])
het_IFreqList = het_read_freq_list - het_carrier_freq
avgPerAcquisition = int(min(self.cfg[self.expt_cfg_name]['averages'], 100))
numAcquisition = int(np.ceil(self.cfg[self.expt_cfg_name]['averages'] / 100))
# (ch1/2, exp_pts, heterodyne_freq, cos/sin, all averages)
ss_data = zeros((2, len(self.expt_pts), len(het_IFreqList), 2, avgPerAcquisition * numAcquisition))
# (ch1/2, heterodyne_freq, cos/sin, all averages)
ss_cal_g = zeros((2, len(het_IFreqList), 2, avgPerAcquisition * numAcquisition))
ss_cal_e = zeros((2, len(het_IFreqList), 2, avgPerAcquisition * numAcquisition))
ss_cal_f = zeros((2, len(het_IFreqList), 2, avgPerAcquisition * numAcquisition))
if self.cfg['readout']['save_trajectory_data']:
# (ch1/2, exp_pts, heterodyne_freq, cos/sin, all averages, traj)
traj_data = zeros((2, len(self.expt_pts), len(het_IFreqList), 2, avgPerAcquisition * numAcquisition, self.cfg['readout']['pts_per_traj']))
# (ch1/2, heterodyne_freq, cos/sin, all averages, traj)
traj_cal_g = zeros((2, len(het_IFreqList), 2, avgPerAcquisition * numAcquisition, self.cfg['readout']['pts_per_traj']))
traj_cal_e = zeros((2, len(het_IFreqList), 2, avgPerAcquisition * numAcquisition, self.cfg['readout']['pts_per_traj']))
traj_cal_f = zeros((2, len(het_IFreqList), 2, avgPerAcquisition * numAcquisition, self.cfg['readout']['pts_per_traj']))
for ii in tqdm(arange(numAcquisition)):
if not self.cfg['readout']['is_hetero_phase_ref']:
# single_data1/2: index: (hetero_freqs, cos/sin, all_seqs)
single_data1, single_data2, single_record1, single_record2 = \
adc.acquire_singleshot_heterodyne_multitone_data(het_IFreqList, prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'])
# saving the raw time traces
# single_data1, single_data2, single_record1, single_record2 = \
# adc.acquire_singleshot_heterodyne_multitone_data(het_IFreqList, prep_function=self.awg_prep,
# start_function=self.awg_run,
# excise=None, save_raw_data=True)
elif self.cfg['readout']['save_trajectory_data']:
excise = [ 0, self.cfg['readout']['window'][1] ]
single_data1, single_data2, single_record1, single_record2, single_traj1, single_traj2= \
adc.acquire_singleshot_heterodyne_multitone_data_phase_ref_save_traj(het_IFreqList,
self.cfg['readout'][
'hetero_phase_ref_freq'],
prep_function=self.awg_prep,
start_function=self.awg_run,
excise=excise,
isCompensatePhase=True,
save_raw_data=False, pts_per_traj=self.cfg['readout']['pts_per_traj'])
else:
# single_data1/2: index: (hetero_freqs, cos/sin, all_seqs)
single_data1, single_data2, single_record1, single_record2 = \
adc.acquire_singleshot_heterodyne_multitone_data_phase_ref(het_IFreqList,
self.cfg['readout']['hetero_phase_ref_freq'],
prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'],
isCompensatePhase=True,
save_raw_data=False)
single_data = array([single_data1, single_data2])
# index: (ch1/2, hetero_freqs, cos / sin, avgs, seq(exp_pts))
single_data = np.reshape(single_data,
(single_data.shape[0], single_data.shape[1], single_data.shape[2],
int(self.cfg['alazar'][
'recordsPerAcquisition'] / self.pulse_sequence.sequence_length),
self.pulse_sequence.sequence_length))
# index: (ch1/2, exp_pts, hetero_freqs, cos / sin, avgs)
single_data = np.transpose(single_data, (0, 4, 1, 2, 3))
if (self.cfg[self.expt_cfg_name]['use_g-e-f_calibration']):
ss_data[:, :, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:,
0:-3]
ss_cal_g[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:, -3]
ss_cal_e[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:, -2]
ss_cal_f[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:, -1]
elif (self.cfg[self.expt_cfg_name]['use_pi_calibration']):
ss_data[:, :, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:,
0:-2]
ss_cal_g[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:, -2]
ss_cal_e[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:, -1]
else:
ss_data[:, :, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:, :]
####
if self.cfg['readout']['save_trajectory_data']:
# index: (hetero_freqs, cos/sin, all_seqs, traj)
single_traj = array([single_traj1, single_traj2])
# index: (ch1/2, hetero_freqs, cos / sin, avgs, seq(exp_pts), traj)
single_traj = np.reshape(single_traj,
(single_traj.shape[0], single_traj.shape[1], single_traj.shape[2],
self.cfg['alazar']['recordsPerAcquisition'] / self.pulse_sequence.sequence_length,
self.pulse_sequence.sequence_length, single_traj.shape[-1]))
# index: (ch1/2, exp_pts, hetero_freqs, cos / sin, avgs, traj)
single_traj = np.transpose(single_traj, (0, 4, 1, 2, 3, 5))
# print single_traj.shape
if (self.cfg[self.expt_cfg_name]['use_g-e-f_calibration']):
traj_data[:, :, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition), :] = single_traj[
:,
0:-3, :]
traj_cal_g[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition), :] = single_traj[:,
-3, :]
traj_cal_e[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition), :] = single_traj[:,
-2, :]
traj_cal_f[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition), :] = single_traj[:,
-1, :]
elif (self.cfg[self.expt_cfg_name]['use_pi_calibration']):
traj_data[:, :, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition), :] = single_traj[
:,
0:-2, :]
traj_cal_g[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition), :] = single_traj[:,
-2, :]
traj_cal_e[:, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition), :] = single_traj[:,
-1, :]
else:
traj_data[:, :, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition), :] = single_traj[
:, :, :]
####
# old way for easy plotting
# only calculate for 1st het_readout_freq
if het_IFreqList[0] == 0:
# take cos of ch1/ch2
expt_avg_data = mean(ss_data[0, :, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
expt_avg_data2 = mean(ss_data[1, :, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
zero_amp_avg = mean(ss_cal_g[0, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
zero_amp_avg2 = mean(ss_cal_g[1, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
pi_amp_avg = mean(ss_cal_e[0, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
pi_amp_avg2 = mean(ss_cal_e[1, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
zero_amp_curr = mean(
ss_cal_g[0, 0, 0, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)], -1)
zero_amp_curr2 = mean(
ss_cal_g[1, 0, 0, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)], -1)
pi_amp_curr = mean(
ss_cal_e[0, 0, 0, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)], -1)
pi_amp_curr2 = mean(
ss_cal_e[1, 0, 0, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)], -1)
expt_avg_data = (expt_avg_data - zero_amp_avg) / (pi_amp_avg - zero_amp_avg)
expt_avg_data2 = (expt_avg_data2 - zero_amp_avg2) / (pi_amp_avg2 - zero_amp_avg2)
else:
# take cos/sin of ch1
expt_avg_data = mean(ss_data[0, :, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
expt_avg_data2 = mean(ss_data[0, :, 0, 1, 0:((ii + 1) * avgPerAcquisition)], -1)
if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
zero_amp_avg = mean(ss_cal_g[0, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
zero_amp_avg2 = mean(ss_cal_g[0, 0, 1, 0:((ii + 1) * avgPerAcquisition)], -1)
pi_amp_avg = mean(ss_cal_e[0, 0, 0, 0:((ii + 1) * avgPerAcquisition)], -1)
pi_amp_avg2 = mean(ss_cal_e[0, 0, 1, 0:((ii + 1) * avgPerAcquisition)], -1)
zero_amp_curr = mean(
ss_cal_g[0, 0, 0, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)], -1)
zero_amp_curr2 = mean(
ss_cal_g[0, 0, 1, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)],
-1)
pi_amp_curr = mean(
ss_cal_e[0, 0, 0, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)], -1)
pi_amp_curr2 = mean(
ss_cal_e[0, 0, 1, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)], -1)
expt_avg_data = (expt_avg_data - zero_amp_avg) / (pi_amp_avg - zero_amp_avg)
expt_avg_data2 = (expt_avg_data2 - zero_amp_avg2) / (pi_amp_avg2 - zero_amp_avg2)
# this needs to stay here
# if self.data_file != None:
# self.slab_file = SlabFile(self.data_file)
# else:
# self.slab_file = self.datafile()
self.slab_file = self.datafile(data_file=self.data_file)
with self.slab_file as f:
f.add('ss_data', ss_data[:, :, :, :, 0:((ii + 1) * avgPerAcquisition)])
f.add('single_record1', single_record1)
f.add('single_record2', single_record2)
if (self.cfg[self.expt_cfg_name]['use_pi_calibration']):
f.add('ss_cal_g', ss_cal_g[:, :, :, 0:((ii + 1) * avgPerAcquisition)])
f.add('ss_cal_e', ss_cal_e[:, :, :, 0:((ii + 1) * avgPerAcquisition)])
if (self.cfg[self.expt_cfg_name]['use_g-e-f_calibration']):
f.add('ss_cal_g', ss_cal_g[:, :, :, 0:((ii + 1) * avgPerAcquisition)])
f.add('ss_cal_e', ss_cal_e[:, :, :, 0:((ii + 1) * avgPerAcquisition)])
f.add('ss_cal_f', ss_cal_f[:, :, :, 0:((ii + 1) * avgPerAcquisition)])
if self.cfg['readout']['save_trajectory_data']:
f.add('traj_data', traj_data[:, :, :, :, 0:((ii + 1) * avgPerAcquisition), :])
if (self.cfg[self.expt_cfg_name]['use_pi_calibration']):
f.add('traj_cal_g', traj_cal_g[:, :, :, 0:((ii + 1) * avgPerAcquisition), :])
f.add('traj_cal_e', traj_cal_e[:, :, :, 0:((ii + 1) * avgPerAcquisition), :])
if (self.cfg[self.expt_cfg_name]['use_g-e-f_calibration']):
f.add('traj_cal_g', traj_cal_g[:, :, :, 0:((ii + 1) * avgPerAcquisition), :])
f.add('traj_cal_e', traj_cal_e[:, :, :, 0:((ii + 1) * avgPerAcquisition), :])
f.add('traj_cal_f', traj_cal_f[:, :, :, 0:((ii + 1) * avgPerAcquisition), :])
f.add('expt_avg_data', expt_avg_data.flatten())
f.add('expt_avg_data2', expt_avg_data2.flatten())
f.add('expt_pts', self.expt_pts)
f.add('het_read_freq_list', het_read_freq_list)
if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
f.append_pt('zero_amps', zero_amp_curr)
f.append_pt('pi_amps', pi_amp_curr)
f.append_pt('zero_amps2', zero_amp_curr2)
f.append_pt('pi_amps2', pi_amp_curr2)
f.close()
####
if self.cfg["visdom_plot_livedata"]:
viz.updateTrace(X=self.expt_pts, Y=expt_avg_data, env=eid, win=win1, append=False)
viz.updateTrace(X=self.expt_pts, Y=expt_avg_data2, env=eid, win=win2, append=False)
# if (self.cfg[self.expt_cfg_name]['use_pi_calibration']):
#
# f_idx = 0
# viz.scatter(X=array([ss_cal_g[0, f_idx, 0, :],ss_cal_g[0, f_idx, 1, :]]).transpose(),
# Y=None, env=eid, win=win4, name='test')
#
# if (self.cfg[self.expt_cfg_name]['use_g-e-f_calibration']):
# pass
if ii==0:
viz.updateTrace(X=array(range(len(single_record1))), Y=single_record2, env=eid, win=win3, name='2', append=False)
viz.updateTrace(X=array(range(len(single_record1))), Y=single_record1, env=eid, win=win3, name='1', append=False)
####
if self.post_run is not None:
self.post_run(self.expt_pts, expt_avg_data)
if self.cfg['stop_awgs'] == True:
self.awg_prep()
print('stop_awg = True, seqs stopped.')
else:
print('stop_awg = False, seqs left running.')
# closes Alazar card and releases buffer
adc.close()
def take_data(self):
print('take_data() in HistogramHetero')
if self.pre_run is not None:
self.pre_run()
if self.adc == None:
print("Prep Card")
adc = Alazar(self.cfg['alazar'])
else:
adc = self.adc
###
het_IFreqList = array([self.cfg['readout']['heterodyne_freq']])
avgPerAcquisition = int(
min(self.cfg[self.expt_cfg_name]['averages'], 100))
numAcquisition = int(
np.ceil(self.cfg[self.expt_cfg_name]['averages'] / 100))
attenpts = arange(self.cfg[self.expt_cfg_name]['atten_start'],
self.cfg[self.expt_cfg_name]['atten_stop'],
self.cfg[self.expt_cfg_name]['atten_step'])
freqpts = arange(self.cfg[self.expt_cfg_name]['freq_start'],
self.cfg[self.expt_cfg_name]['freq_stop'],
self.cfg[self.expt_cfg_name]['freq_step'])
# (channel, atten, freq, g/e/f, average)
ss_cos_data_all = zeros((2, len(attenpts), len(freqpts), 3,
avgPerAcquisition * numAcquisition))
ss_sin_data_all = zeros((2, len(attenpts), len(freqpts), 3,
avgPerAcquisition * numAcquisition))
for xx, atten in enumerate(attenpts):
try:
self.readout_atten.set_attenuator(atten)
print("Digital atten:", atten)
except:
print("Digital attenuator not loaded.")
# (ch1/2, exp_pts, heterodyne_freq, cos/sin, all averages)
ss_data = zeros((2, len(self.expt_pts), len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition))
for ii in tqdm(arange(numAcquisition)):
if not self.cfg['readout']['is_hetero_phase_ref']:
# single_data1/2: index: (hetero_freqs, cos/sin, all_seqs)
single_data1, single_data2, single_record1, single_record2 = \
adc.acquire_singleshot_heterodyne_multitone_data(het_IFreqList, prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'])
# saving the raw time traces
# single_data1, single_data2, single_record1, single_record2 = \
# adc.acquire_singleshot_heterodyne_multitone_data(het_IFreqList, prep_function=self.awg_prep,
# start_function=self.awg_run,
# excise=None, save_raw_data=True)
else:
# single_data1/2: index: (hetero_freqs, cos/sin, all_seqs)
single_data1, single_data2, single_record1, single_record2 = \
adc.acquire_singleshot_heterodyne_multitone_data_phase_ref(het_IFreqList,
self.cfg['readout']['hetero_phase_ref_freq'],
prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'],
isCompensatePhase=True,
save_raw_data=False)
single_data = array([single_data1, single_data2])
# reshape to fit into histogram data
# index: (ch1/2, hetero_freqs(0), cos / sin, avgs, freqpts(exp seq), g/e/f)
single_data = np.reshape(
single_data, (single_data.shape[0], single_data.shape[1],
single_data.shape[2],
self.cfg['alazar']['recordsPerAcquisition'] /
self.pulse_sequence.sequence_length,
self.pulse_sequence.sequence_length / 3, 3))
# (channel, hetero_freqs(0), cos/sin, freqpts(exp seq), g/e/f, average)
single_data = np.transpose(single_data, (0, 1, 2, 4, 5, 3))
# (channel, atten, freqpts, g/e/f, average)
ss_cos_data_all[:, xx, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:, 0,
0, :, :, :]
ss_sin_data_all[:, xx, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:, 0,
1, :, :, :]
# this needs to stay here
self.slab_file = self.datafile(data_file=self.data_file)
with self.slab_file as f:
f.add('attenpts', attenpts)
f.add('freqpts', freqpts)
f.add('het_IFreqList', het_IFreqList)
f.add('ss_cos_data_ch1', ss_cos_data_all[0])
f.add('ss_cos_data_ch2', ss_cos_data_all[1])
f.add('ss_sin_data_ch1', ss_sin_data_all[0])
f.add('ss_sin_data_ch2', ss_sin_data_all[1])
f.append_line('single_record1', single_record1)
f.append_line('single_record2', single_record2)
f.close()
###
# if self.post_run is not None:
# self.post_run(self.expt_pts, expt_avg_data)
if self.cfg['stop_awgs'] == True:
self.awg_prep()
# close Alazar and release buffer
adc.close()
def run_sequential_experiment(expt_name):
import os
import difflib
expt_list = [
'Frequency_Calibration', 'Rabi_Sweep', 'HalfPiXOptimization_sweep',
'tune_up_experiment'
]
datapath = os.getcwd() + '\data'
config_file = os.path.join(datapath, "..\\config" + ".json")
with open(config_file, 'r') as fid:
cfg_str = fid.read()
cfg = AttrDict(json.loads(cfg_str))
expt = None
experiment_started = False
if expt_name.lower() == 'calibration_experiment':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RabiExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRabiExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRamseyExperiment
# Do Frequency Calibration
expt = RamseyExperiment(path=datapath)
expt.go()
print(expt.offset_freq)
expt = RabiExperiment(path=datapath)
expt.go()
expt = EFRabiExperiment(path=datapath)
expt.go()
expt = EFRamseyExperiment(path=datapath)
expt.go()
del expt
gc.collect()
if expt_name.lower() == 'monitor_frequency_experiment':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRamseyExperiment
# Do Frequency Calibration
for i in arange(20):
expt = RamseyExperiment(path=datapath)
expt.go()
print(expt.offset_freq)
expt = EFRamseyExperiment(path=datapath)
expt.go()
del expt
gc.collect()
if expt_name.lower() == 'sequential_error_amplification':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import SingleQubitErrorAmplificationExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import SingleQubitErrorAmplificationPhaseOffsetExperiment
for i in arange(5):
pulse_calibration(phase_exp=True)
expt = SingleQubitErrorAmplificationPhaseOffsetExperiment(
path=datapath,
trigger_period=0.001,
c0="half_pi",
ci="half_pi")
expt.go()
expt.save_config()
del expt
gc.collect()
for i in arange(5):
pulse_calibration(phase_exp=True)
expt = SingleQubitErrorAmplificationPhaseOffsetExperiment(
path=datapath, trigger_period=0.001, c0="pi", ci="half_pi")
expt.go()
expt.save_config()
del expt
gc.collect()
for i in arange(5):
pulse_calibration(phase_exp=True)
expt = SingleQubitErrorAmplificationPhaseOffsetExperiment(
path=datapath, trigger_period=0.001, c0="pi", ci="pi")
expt.go()
expt.save_config()
del expt
gc.collect()
for i in arange(5):
pulse_calibration(phase_exp=True)
expt = SingleQubitErrorAmplificationPhaseOffsetExperiment(
path=datapath, trigger_period=0.001, c0="half_pi", ci="pi")
expt.go()
expt.save_config()
del expt
gc.collect()
if expt_name.lower() == 'sequential_randomized_benchmarking':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import SingleQubitRandomizedBenchmarkingExperiment
for i in arange(32):
pulse_calibration(phase_exp=False)
expt = SingleQubitRandomizedBenchmarkingExperiment(
path=datapath, trigger_period=0.001)
expt.go()
del expt
gc.collect()
if expt_name.lower() == 'sequential_randomized_benchmarking_phase_offset':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import SingleQubitRandomizedBenchmarkingPhaseOffsetExperiment
for i in arange(32):
pulse_calibration(phase_exp=True)
expt = SingleQubitRandomizedBenchmarkingPhaseOffsetExperiment(
path=datapath, trigger_period=0.001)
expt.go()
del expt
gc.collect()
if expt_name.lower() == 'tomography_tune_up_experiment':
experiment_started = True
print(expt_name + " is running!")
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RabiExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRabiExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRamseyExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import HalfPiYPhaseOptimizationExperiment
# Do Frequency Calibration
expt = RamseyExperiment(path=datapath)
expt.go()
if (abs(expt.offset_freq) < 50e3):
pass
else:
print(expt.flux)
flux_offset = -expt.offset_freq / (expt.freq_flux_slope)
print(flux_offset)
if (abs(flux_offset) < 0.000002):
flux2 = expt.flux + flux_offset
print(flux2)
expt = RamseyExperiment(path=datapath, flux=flux2)
expt.go()
offset_freq2 = expt.offset_freq
flux_offset2 = -expt.offset_freq / (expt.freq_flux_slope)
flux3 = flux2 + flux_offset2
if (abs(offset_freq2) < 50e3):
print("Great success! Frequency calibrated")
expt.save_config()
else:
if (abs(flux_offset2) < 0.000002):
expt = RamseyExperiment(path=datapath, flux=flux3)
expt.go()
if (abs(expt.offset_freq) < 100e3):
print("Frequency calibrated")
expt.save_config()
else:
print("Try again: not converged after 2 tries")
else:
print(
"Large change in flux is required; please do so manually"
)
pass
else:
print(
"Large change in flux is required; please do so manually")
pass
expt = RabiExperiment(path=datapath)
expt.go()
print("ge pi and pi/2 pulses recalibrated")
expt.save_config()
expt = EFRabiExperiment(path=datapath)
expt.go()
print("ef pi and pi/2 pulses recalibrated")
expt.save_config()
expt = EFRamseyExperiment(path=datapath)
expt.go()
expt.save_config()
expt.go()
# #
# expt = HalfPiYPhaseOptimizationExperiment(path=datapath)
# expt.go()
# #
# print flux2
del expt
gc.collect()
if expt_name.lower() == 'offset_phase_calibration_experiment':
qubit_dc_offset_list_pi = array([
0, 0, 0, 1.7e6, 1.7e6, 1.7e6, 1.8e6, 1.8e6, 1.8e6, 1.9e6, 1.9e6,
1.9e6, 2e6, 2e6, 2e6
])
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import HalfPiYPhaseOptimizationExperiment
# Do Frequency Calibration
# frequency_stabilization()
j = 0
for qubit_dc_offset in qubit_dc_offset_list_pi:
if j > 0 and j % 3 == 0:
frequency_stabilization()
expt = HalfPiYPhaseOptimizationExperiment(
path=datapath, qubit_dc_offset=qubit_dc_offset)
expt.go()
expt.save_config()
del expt
gc.collect()
j += 1
if expt_name.lower() == 'frequency_calibration':
frequency_stabilization()
if expt_name.lower() == 'pulse_calibration':
pulse_calibration(phase_exp=True)
if expt_name.lower() == 'rabi_sweep':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RabiSweepExperiment
cfg['alazar']['samplesPerRecord'] = 2**(cfg['readout']['width'] -
1).bit_length()
sequence_length = (
cfg[expt_name.lower()]['stop'] -
cfg[expt_name.lower()]['start']) / cfg[expt_name.lower()]['step']
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
drive_freq_pts = arange(cfg[expt_name.lower()]['freq_start'],
cfg[expt_name.lower()]['freq_stop'],
cfg[expt_name.lower()]['freq_step'])
prefix = 'Rabi_Sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
for ii, drive_freq in enumerate(drive_freq_pts):
print(drive_freq)
expt = RabiSweepExperiment(path=datapath,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'rabi_ramsey_t1_flux_sweep':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RabiRamseyT1FluxSweepExperiment
prefix = 'rabi_ramsey_t1_flux_sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
flux_pts = np.load(
r'S:\_Data\160104 - 2D Multimode Qubit (Chip MM3, 11 modes)\iPython Notebooks\flux_sm.npy'
)
drive_pts = np.load(
r'S:\_Data\160104 - 2D Multimode Qubit (Chip MM3, 11 modes)\iPython Notebooks\qubit_frequencies_sm.npy'
)
readout_pts = np.load(
r'S:\_Data\160104 - 2D Multimode Qubit (Chip MM3, 11 modes)\iPython Notebooks\readout_frequencies_sm.npy'
)
# flux_pts=[-0.012]
# drive_pts=[4.844e9]
# readout_pts=[5257100000.0]
qubit_alpha = cfg['qubit']['alpha']
for ii, flux in enumerate(flux_pts):
drive_freq = drive_pts[ii]
readout_freq = readout_pts[ii]
print("Flux: " + str(flux))
print("Drive frequency: " + str(drive_freq))
print("Readout frequency: " + str(readout_freq))
### 1st Rabi
print("### Running 1st Rabi.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'rabi')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='rabi',
flux=flux,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled)
expt.go()
pi_length = expt.pi_length
half_pi_length = expt.half_pi_length
adc.close()
expt = None
del expt
gc.collect()
### 1st Ramsey
print("### Running 1st Ramsey.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ramsey')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='ramsey',
flux=flux,
half_pi_length=half_pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled)
expt.go()
suggested_qubit_freq = expt.suggested_qubit_freq
drive_freq = suggested_qubit_freq
adc.close()
expt = None
del expt
gc.collect()
### 2nd Rabi
print("### Running 2nd Rabi.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'rabi')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='rabi',
flux=flux,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled)
expt.go()
pi_length = expt.pi_length
half_pi_length = expt.half_pi_length
adc.close()
expt = None
del expt
gc.collect()
### Ramsey long
print("### Running Ramsey Long.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep',
'ramsey_long')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='ramsey_long',
flux=flux,
half_pi_length=half_pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled)
expt.go()
adc.close()
expt = None
del expt
gc.collect()
### Rabi Long
print("### Running Rabi Long.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'rabi_long')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='rabi_long',
flux=flux,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled)
expt.go()
# pi_length = expt.pi_length
# half_pi_length = expt.half_pi_length
adc.close()
expt = None
del expt
gc.collect()
### remove adc
adc = None
del adc
### t1
print("### Running T1.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 't1')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='t1',
flux=flux,
pi_length=pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled)
expt.go()
adc.close()
expt = None
del expt
gc.collect()
### Pi/2 phase sweep
print("### Running pi/2 phase sweep experiment")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep',
'half_pi_phase_sweep')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='half_pi_phase_sweep',
flux=flux,
half_pi_length=half_pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled)
expt.go()
adc.close()
expt = None
del expt
gc.collect()
### EF Rabi
print("### Running EF Rabi.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_rabi')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='ef_rabi',
flux=flux,
pi_length=pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled,
alpha=qubit_alpha)
expt.go()
ef_pi_length = expt.pi_length
ef_half_pi_length = expt.half_pi_length
adc.close()
expt = None
del expt
gc.collect()
### EF Ramsey
print("### Running EF Ramsey.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_ramsey')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='ef_ramsey',
flux=flux,
pi_length=pi_length,
ef_half_pi_length=ef_half_pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled,
alpha=qubit_alpha)
expt.go()
suggested_alpha_freq = expt.suggested_qubit_alpha
print("Suggested alpha frequency: " + str(suggested_alpha_freq))
qubit_alpha = suggested_alpha_freq
adc.close()
expt = None
del expt
gc.collect()
### EF Rabi
print("### Running EF Rabi.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_rabi')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='ef_rabi',
flux=flux,
pi_length=pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled,
alpha=qubit_alpha)
expt.go()
ef_pi_length = expt.pi_length
ef_half_pi_length = expt.half_pi_length
adc.close()
expt = None
del expt
gc.collect()
### EF T1
print("### Running EF T1.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_t1')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='ef_t1',
flux=flux,
pi_length=pi_length,
ef_pi_length=ef_pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled,
alpha=qubit_alpha)
expt.go()
adc.close()
expt = None
del expt
gc.collect()
## EF Ramsey Long
print("### Running EF Ramsey.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep',
'ef_ramsey_long')
expt = RabiRamseyT1FluxSweepExperiment(
path=datapath,
exp='ef_ramsey_long',
flux=flux,
pi_length=pi_length,
ef_half_pi_length=ef_half_pi_length,
data_file=data_file,
adc=adc,
drive_freq=drive_freq,
readout_freq=readout_freq,
liveplot_enabled=liveplot_enabled,
alpha=qubit_alpha)
expt.go()
suggested_alpha_freq = expt.suggested_qubit_alpha
print("Suggested alpha frequency: " + str(suggested_alpha_freq))
qubit_alpha = suggested_alpha_freq
adc.close()
expt = None
del expt
gc.collect()
### remove adc
adc = None
del adc
gc.collect()
if expt_name.lower() == 'halfpixoptimization_sweep':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import HalfPiXOptimizationSweepExperiment
adc = prepare_alazar(cfg, expt_name)
if cfg[expt_name.lower()]['sweep_param'] == "length":
pulse_sweep_pts = arange(cfg[expt_name.lower()]['length_start'],
cfg[expt_name.lower()]['length_stop'],
cfg[expt_name.lower()]['length_step'])
pulse_amp = cfg[expt_name.lower()]['amp']
elif cfg[expt_name.lower()]['sweep_param'] == "amp":
pulse_sweep_pts = arange(cfg[expt_name.lower()]['amp_start'],
cfg[expt_name.lower()]['amp_stop'],
cfg[expt_name.lower()]['amp_step'])
pulse_length = cfg[expt_name.lower()]['length']
prefix = 'HalfPiXOptimization_Sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
if cfg[expt_name.lower()]['sweep_param'] == "length":
for ii, pulse_sweep in enumerate(pulse_sweep_pts):
print("Pulse Sweep: " + str(pulse_sweep))
expt = HalfPiXOptimizationSweepExperiment(
path=datapath,
data_file=data_file,
adc=adc,
pulse_length=pulse_sweep,
pulse_amp=pulse_amp,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
elif cfg[expt_name.lower()]['sweep_param'] == "amp":
for ii, pulse_sweep in enumerate(pulse_sweep_pts):
print("Pulse Sweep: " + str(pulse_sweep))
expt = HalfPiXOptimizationSweepExperiment(
path=datapath,
data_file=data_file,
adc=adc,
pulse_length=pulse_length,
pulse_amp=pulse_sweep,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'pixoptimization_sweep':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import PiXOptimizationSweepExperiment
# cfg['alazar']['samplesPerRecord'] = 2 ** (cfg['readout']['width'] - 1).bit_length()
# sequence_length = (cfg[expt_name.lower()]['stop']-cfg[expt_name.lower()]['start'])/cfg[expt_name.lower()]['step']
# if (cfg[expt_name.lower()]['use_pi_calibration']):
# sequence_length+=2
#
# cfg['alazar']['recordsPerBuffer'] = sequence_length
# cfg['alazar']['recordsPerAcquisition'] = int(
# sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
# print "Prep Card"
# adc = Alazar(cfg['alazar'])
adc = prepare_alazar(cfg, expt_name)
if cfg[expt_name.lower()]['sweep_param'] == "length":
pulse_sweep_pts = arange(cfg[expt_name.lower()]['length_start'],
cfg[expt_name.lower()]['length_stop'],
cfg[expt_name.lower()]['length_step'])
pulse_amp = cfg[expt_name.lower()]['amp']
elif cfg[expt_name.lower()]['sweep_param'] == "amp":
pulse_sweep_pts = arange(cfg[expt_name.lower()]['amp_start'],
cfg[expt_name.lower()]['amp_stop'],
cfg[expt_name.lower()]['amp_step'])
pulse_length = cfg[expt_name.lower()]['length']
prefix = 'PiXOptimization_Sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
# for ii, pulse_sweep in enumerate(pulse_sweep_pts):
# print "Pulse Sweep: " + str(pulse_sweep)
# expt = PiXOptimizationSweepExperiment(path=datapath,data_file=data_file, adc=adc, pulse_length=pulse_sweep, liveplot_enabled = False)
# expt.go()
#
# expt = None
# del expt
#
# gc.collect()
if cfg[expt_name.lower()]['sweep_param'] == "length":
for ii, pulse_sweep in enumerate(pulse_sweep_pts):
print("Pulse Sweep: " + str(pulse_sweep))
expt = PiXOptimizationSweepExperiment(path=datapath,
data_file=data_file,
adc=adc,
pulse_length=pulse_sweep,
pulse_amp=pulse_amp,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
elif cfg[expt_name.lower()]['sweep_param'] == "amp":
for ii, pulse_sweep in enumerate(pulse_sweep_pts):
print("Pulse Sweep: " + str(pulse_sweep))
expt = PiXOptimizationSweepExperiment(
path=datapath,
data_file=data_file,
adc=adc,
pulse_length=pulse_length,
pulse_amp=pulse_sweep,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
if not experiment_started:
close_match = difflib.get_close_matches(expt_name, expt_list)
print("No experiment found for: " + expt_name)
print("Do you mean: " + close_match[0] + "?")
def take_data(self):
####
if self.cfg["visdom_plot_livedata"]:
viz = visdom.Visdom()
assert viz.check_connection(), "Visdom server not connected!"
# added two environments "seq_builder.json", and "live_plot.json" in C:\Users\slab\.visdom
eid = "live_plot"
viz.close(win=None, env=eid)
win1 = viz.line(X=np.arange(0, 1),
Y=np.arange(0, 1),
env=eid,
opts=dict(height=400,
width=700,
title='expt_avg_data',
showlegend=True,
xlabel='expt_pts'))
win2 = viz.line(X=np.arange(0, 1),
Y=np.arange(0, 1),
env=eid,
opts=dict(height=400,
width=700,
title='expt_avg_data2',
showlegend=True,
xlabel='expt_pts'))
win3 = viz.line(X=np.arange(0, 1),
Y=np.arange(0, 1),
env=eid,
opts=dict(
height=400,
width=700,
title='single_record (of only first run)',
showlegend=True,
xlabel='time ns'))
####
if self.pre_run is not None:
self.pre_run()
TEST_REDPITAYA = False
if TEST_REDPITAYA:
self.awg_run()
if not TEST_REDPITAYA:
if self.adc == None:
print("Prep Card")
adc = Alazar(self.cfg['alazar'])
else:
adc = self.adc
# debug_alazer = False
# if debug_alazer:
#
# # save raw time trace, 100 runs only
# tpts, single_data1, single_data2 = adc.acquire_singleshot_data2()
#
# self.slab_file = self.datafile(data_file=self.data_file)
# with self.slab_file as f:
# f.add('tpts', tpts)
# f.add('single_data1', single_data1)
# f.add('single_data2', single_data2)
# f.close()
#
# # hack for post_run
# expt_avg_data = self.expt_pts
#
# else:
if not self.cfg['readout']['save_single-shot_data']:
expt_data = None
current_data = None
for ii in tqdm(
arange(
max(1, self.cfg[self.expt_cfg_name]['averages'] /
100))):
tpts, ch1_pts, ch2_pts = adc.acquire_avg_data_by_record(
prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'])
if not self.cfg[self.expt_cfg_name]['use_pi_calibration']:
if expt_data is None:
if self.cfg['readout']['channel'] == 1:
expt_data = ch1_pts
elif self.cfg['readout']['channel'] == 2:
expt_data = ch2_pts
else:
if self.cfg['readout']['channel'] == 1:
expt_data = (expt_data * ii + ch1_pts) / (ii +
1.0)
elif self.cfg['readout']['channel'] == 2:
expt_data = (expt_data * ii + ch2_pts) / (ii +
1.0)
if self.cfg['readout']['heterodyne_freq'] == 0:
# homodyne
expt_avg_data = mean(expt_data, 1)
else:
# heterodyne
heterodyne_freq = self.cfg['readout'][
'heterodyne_freq']
# ifft by numpy default has the correct 1/N normalization
expt_data_fft_amp = np.abs(np.fft.ifft(expt_data))
hetero_f_ind = int(
round(heterodyne_freq * tpts.size *
1e-9)) # position in ifft
# todo: do the proper sum here
# expt_avg_data = np.average(expt_data_fft_amp[:, (hetero_f_ind - 1):(hetero_f_ind + 1)], axis=1)
expt_avg_data = expt_data_fft_amp[:, hetero_f_ind]
else:
# average first, then divide by pi_calibration values
if expt_data is None:
if self.cfg['readout']['channel'] == 1:
expt_data = ch1_pts[:-2]
zero_amp_curr = mean(ch1_pts[-2])
pi_amp_curr = mean(ch1_pts[-1])
elif self.cfg['readout']['channel'] == 2:
expt_data = ch2_pts[:-2]
zero_amp_curr = mean(ch2_pts[-2])
pi_amp_curr = mean(ch2_pts[-1])
zero_amp = zero_amp_curr
pi_amp = pi_amp_curr
else:
if self.cfg['readout']['channel'] == 1:
expt_data = (expt_data * ii +
ch1_pts[:-2]) / (ii + 1.0)
zero_amp_curr = mean(ch1_pts[-2])
pi_amp_curr = mean(ch1_pts[-1])
elif self.cfg['readout']['channel'] == 2:
expt_data = (expt_data * ii +
ch2_pts[:-2]) / (ii + 1.0)
zero_amp_curr = mean(ch2_pts[-2])
pi_amp_curr = mean(ch2_pts[-1])
zero_amp = (zero_amp * ii + zero_amp_curr) / (ii +
1.0)
pi_amp = (pi_amp * ii + pi_amp_curr) / (ii + 1.0)
# todo: add heterodyne with pi_cal
expt_avg_data = mean(
(expt_data - zero_amp) / (pi_amp - zero_amp), 1)
# self.slab_file = self.datafile(data_file=self.data_file)
with self.slab_file as f:
f.add('expt_2d', expt_data)
f.add('expt_avg_data', expt_avg_data)
f.add('expt_pts', self.expt_pts)
# save pi_cal amps, to be able to monitor fluctuations
if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
f.append_pt('zero_amps', zero_amp_curr)
f.append_pt('pi_amps', pi_amp_curr)
f.close()
else: # here saves all single shot data
if self.prefix == 'Vacuum_Rabi':
print('vacuum_rabi')
het_IFreqList = [self.cfg['readout']['heterodyne_freq']]
het_read_freq_list = [0]
elif self.cfg['readout']['is_multitone_heterodyne']:
het_carrier_freq = self.cfg['readout'][
'heterodyne_carrier_freq']
het_read_freq_list = array(
self.cfg['readout']['heterodyne_freq_list'])
het_IFreqList = het_read_freq_list - het_carrier_freq
else:
het_carrier_freq = self.readout_freq - self.cfg['readout'][
'heterodyne_freq']
het_read_freq_list = array([self.readout_freq])
het_IFreqList = het_read_freq_list - het_carrier_freq
avgPerAcquisition = int(
min(self.cfg[self.expt_cfg_name]['averages'], 100))
numAcquisition = int(
np.ceil(self.cfg[self.expt_cfg_name]['averages'] / 100))
# (ch1/2, exp_pts, heterodyne_freq, cos/sin, all averages)
ss_data = zeros((2, len(self.expt_pts), len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition))
# (ch1/2, heterodyne_freq, cos/sin, all averages)
ss_cal_g = zeros((2, len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition))
ss_cal_e = zeros((2, len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition))
ss_cal_f = zeros((2, len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition))
if self.cfg['readout']['save_trajectory_data']:
# (ch1/2, exp_pts, heterodyne_freq, cos/sin, all averages, traj)
traj_data = zeros(
(2, len(self.expt_pts), len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition,
self.cfg['readout']['pts_per_traj']))
# (ch1/2, heterodyne_freq, cos/sin, all averages, traj)
traj_cal_g = zeros((2, len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition,
self.cfg['readout']['pts_per_traj']))
traj_cal_e = zeros((2, len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition,
self.cfg['readout']['pts_per_traj']))
traj_cal_f = zeros((2, len(het_IFreqList), 2,
avgPerAcquisition * numAcquisition,
self.cfg['readout']['pts_per_traj']))
for ii in tqdm(arange(numAcquisition)):
if not self.cfg['readout']['is_hetero_phase_ref']:
# single_data1/2: index: (hetero_freqs, cos/sin, all_seqs)
single_data1, single_data2, single_record1, single_record2 = \
adc.acquire_singleshot_heterodyne_multitone_data(het_IFreqList, prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'])
# saving the raw time traces
# single_data1, single_data2, single_record1, single_record2 = \
# adc.acquire_singleshot_heterodyne_multitone_data(het_IFreqList, prep_function=self.awg_prep,
# start_function=self.awg_run,
# excise=None, save_raw_data=True)
elif self.cfg['readout']['save_trajectory_data']:
excise = [0, self.cfg['readout']['window'][1]]
single_data1, single_data2, single_record1, single_record2, single_traj1, single_traj2= \
adc.acquire_singleshot_heterodyne_multitone_data_phase_ref_save_traj(het_IFreqList,
self.cfg['readout'][
'hetero_phase_ref_freq'],
prep_function=self.awg_prep,
start_function=self.awg_run,
excise=excise,
isCompensatePhase=True,
save_raw_data=False, pts_per_traj=self.cfg['readout']['pts_per_traj'])
else:
# single_data1/2: index: (hetero_freqs, cos/sin, all_seqs)
single_data1, single_data2, single_record1, single_record2 = \
adc.acquire_singleshot_heterodyne_multitone_data_phase_ref(het_IFreqList,
self.cfg['readout']['hetero_phase_ref_freq'],
prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'],
isCompensatePhase=True,
save_raw_data=False)
single_data = array([single_data1, single_data2])
# index: (ch1/2, hetero_freqs, cos / sin, avgs, seq(exp_pts))
single_data = np.reshape(
single_data,
(single_data.shape[0], single_data.shape[1],
single_data.shape[2],
int(self.cfg['alazar']['recordsPerAcquisition'] /
self.pulse_sequence.sequence_length),
self.pulse_sequence.sequence_length))
# index: (ch1/2, exp_pts, hetero_freqs, cos / sin, avgs)
single_data = np.transpose(single_data, (0, 4, 1, 2, 3))
if (self.cfg[self.expt_cfg_name]['use_g-e-f_calibration']):
ss_data[:, :, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:,
0:-3]
ss_cal_g[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:, -3]
ss_cal_e[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:, -2]
ss_cal_f[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:, -1]
elif (self.cfg[self.expt_cfg_name]['use_pi_calibration']):
ss_data[:, :, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:,
0:-2]
ss_cal_g[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:, -2]
ss_cal_e[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:, -1]
else:
ss_data[:, :, :, :, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)] = single_data[:, :]
####
if self.cfg['readout']['save_trajectory_data']:
# index: (hetero_freqs, cos/sin, all_seqs, traj)
single_traj = array([single_traj1, single_traj2])
# index: (ch1/2, hetero_freqs, cos / sin, avgs, seq(exp_pts), traj)
single_traj = np.reshape(
single_traj,
(single_traj.shape[0], single_traj.shape[1],
single_traj.shape[2],
self.cfg['alazar']['recordsPerAcquisition'] /
self.pulse_sequence.sequence_length,
self.pulse_sequence.sequence_length,
single_traj.shape[-1]))
# index: (ch1/2, exp_pts, hetero_freqs, cos / sin, avgs, traj)
single_traj = np.transpose(single_traj,
(0, 4, 1, 2, 3, 5))
# print single_traj.shape
if (self.cfg[self.expt_cfg_name]
['use_g-e-f_calibration']):
traj_data[:, :, :, :, (ii * avgPerAcquisition):(
(ii + 1) *
avgPerAcquisition), :] = single_traj[:,
0:-3, :]
traj_cal_g[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) *
avgPerAcquisition), :] = single_traj[:, -3, :]
traj_cal_e[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) *
avgPerAcquisition), :] = single_traj[:, -2, :]
traj_cal_f[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) *
avgPerAcquisition), :] = single_traj[:, -1, :]
elif (self.cfg[self.expt_cfg_name]
['use_pi_calibration']):
traj_data[:, :, :, :, (ii * avgPerAcquisition):(
(ii + 1) *
avgPerAcquisition), :] = single_traj[:,
0:-2, :]
traj_cal_g[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) *
avgPerAcquisition), :] = single_traj[:, -2, :]
traj_cal_e[:, :, :, (ii * avgPerAcquisition):(
(ii + 1) *
avgPerAcquisition), :] = single_traj[:, -1, :]
else:
traj_data[:, :, :, :, (ii * avgPerAcquisition):(
(ii + 1) *
avgPerAcquisition), :] = single_traj[:, :, :]
####
# old way for easy plotting
# only calculate for 1st het_readout_freq
if het_IFreqList[0] == 0:
# take cos of ch1/ch2
expt_avg_data = mean(
ss_data[0, :, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
expt_avg_data2 = mean(
ss_data[1, :, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
zero_amp_avg = mean(
ss_cal_g[0, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
zero_amp_avg2 = mean(
ss_cal_g[1, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
pi_amp_avg = mean(
ss_cal_e[0, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
pi_amp_avg2 = mean(
ss_cal_e[1, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
zero_amp_curr = mean(
ss_cal_g[0, 0, 0, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)], -1)
zero_amp_curr2 = mean(
ss_cal_g[1, 0, 0, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)], -1)
pi_amp_curr = mean(
ss_cal_e[0, 0, 0, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)], -1)
pi_amp_curr2 = mean(
ss_cal_e[1, 0, 0, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)], -1)
expt_avg_data = (expt_avg_data - zero_amp_avg) / (
pi_amp_avg - zero_amp_avg)
expt_avg_data2 = (expt_avg_data2 - zero_amp_avg2
) / (pi_amp_avg2 - zero_amp_avg2)
else:
# take cos/sin of ch1
expt_avg_data = mean(
ss_data[0, :, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
expt_avg_data2 = mean(
ss_data[0, :, 0, 1,
0:((ii + 1) * avgPerAcquisition)], -1)
if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
zero_amp_avg = mean(
ss_cal_g[0, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
zero_amp_avg2 = mean(
ss_cal_g[0, 0, 1,
0:((ii + 1) * avgPerAcquisition)], -1)
pi_amp_avg = mean(
ss_cal_e[0, 0, 0,
0:((ii + 1) * avgPerAcquisition)], -1)
pi_amp_avg2 = mean(
ss_cal_e[0, 0, 1,
0:((ii + 1) * avgPerAcquisition)], -1)
zero_amp_curr = mean(
ss_cal_g[0, 0, 0, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)], -1)
zero_amp_curr2 = mean(
ss_cal_g[0, 0, 1, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)], -1)
pi_amp_curr = mean(
ss_cal_e[0, 0, 0, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)], -1)
pi_amp_curr2 = mean(
ss_cal_e[0, 0, 1, (ii * avgPerAcquisition):(
(ii + 1) * avgPerAcquisition)], -1)
expt_avg_data = (expt_avg_data - zero_amp_avg) / (
pi_amp_avg - zero_amp_avg)
expt_avg_data2 = (expt_avg_data2 - zero_amp_avg2
) / (pi_amp_avg2 - zero_amp_avg2)
# this needs to stay here
# if self.data_file != None:
# self.slab_file = SlabFile(self.data_file)
# else:
# self.slab_file = self.datafile()
self.slab_file = self.datafile(data_file=self.data_file)
with self.slab_file as f:
f.add(
'ss_data',
ss_data[:, :, :, :,
0:((ii + 1) * avgPerAcquisition)])
f.add('single_record1', single_record1)
f.add('single_record2', single_record2)
if (self.cfg[self.expt_cfg_name]['use_pi_calibration']
):
f.add(
'ss_cal_g',
ss_cal_g[:, :, :,
0:((ii + 1) * avgPerAcquisition)])
f.add(
'ss_cal_e',
ss_cal_e[:, :, :,
0:((ii + 1) * avgPerAcquisition)])
if (self.cfg[self.expt_cfg_name]
['use_g-e-f_calibration']):
f.add(
'ss_cal_g',
ss_cal_g[:, :, :,
0:((ii + 1) * avgPerAcquisition)])
f.add(
'ss_cal_e',
ss_cal_e[:, :, :,
0:((ii + 1) * avgPerAcquisition)])
f.add(
'ss_cal_f',
ss_cal_f[:, :, :,
0:((ii + 1) * avgPerAcquisition)])
if self.cfg['readout']['save_trajectory_data']:
f.add(
'traj_data',
traj_data[:, :, :, :,
0:((ii + 1) * avgPerAcquisition), :])
if (self.cfg[self.expt_cfg_name]
['use_pi_calibration']):
f.add(
'traj_cal_g',
traj_cal_g[:, :, :,
0:((ii + 1) *
avgPerAcquisition), :])
f.add(
'traj_cal_e',
traj_cal_e[:, :, :,
0:((ii + 1) *
avgPerAcquisition), :])
if (self.cfg[self.expt_cfg_name]
['use_g-e-f_calibration']):
f.add(
'traj_cal_g',
traj_cal_g[:, :, :,
0:((ii + 1) *
avgPerAcquisition), :])
f.add(
'traj_cal_e',
traj_cal_e[:, :, :,
0:((ii + 1) *
avgPerAcquisition), :])
f.add(
'traj_cal_f',
traj_cal_f[:, :, :,
0:((ii + 1) *
avgPerAcquisition), :])
f.add('expt_avg_data', expt_avg_data.flatten())
f.add('expt_avg_data2', expt_avg_data2.flatten())
f.add('expt_pts', self.expt_pts)
f.add('het_read_freq_list', het_read_freq_list)
if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
f.append_pt('zero_amps', zero_amp_curr)
f.append_pt('pi_amps', pi_amp_curr)
f.append_pt('zero_amps2', zero_amp_curr2)
f.append_pt('pi_amps2', pi_amp_curr2)
f.close()
####
if self.cfg["visdom_plot_livedata"]:
viz.updateTrace(X=self.expt_pts,
Y=expt_avg_data,
env=eid,
win=win1,
append=False)
viz.updateTrace(X=self.expt_pts,
Y=expt_avg_data2,
env=eid,
win=win2,
append=False)
if ii == 0:
viz.updateTrace(X=array(range(
len(single_record1))),
Y=single_record2,
env=eid,
win=win3,
name='2',
append=False)
viz.updateTrace(X=array(range(
len(single_record1))),
Y=single_record1,
env=eid,
win=win3,
name='1',
append=False)
####
if self.post_run is not None:
self.post_run(self.expt_pts, expt_avg_data)
if self.cfg['stop_awgs'] == True:
self.awg_prep()
print('stop_awg = True, seqs stopped.')
else:
print('stop_awg = False, seqs left running.')
# closes Alazar card and releases buffer
adc.close()
def take_data(self):
print('take_data() in HistogramHetero')
if self.pre_run is not None:
self.pre_run()
if self.adc == None:
print("Prep Card")
adc = Alazar(self.cfg['alazar'])
else:
adc = self.adc
###
het_IFreqList = array([self.cfg['readout']['heterodyne_freq']])
avgPerAcquisition = int(min(self.cfg[self.expt_cfg_name]['averages'], 100))
numAcquisition = int(np.ceil(self.cfg[self.expt_cfg_name]['averages'] / 100))
attenpts = arange(self.cfg[self.expt_cfg_name]['atten_start'], self.cfg[self.expt_cfg_name]['atten_stop'], self.cfg[self.expt_cfg_name]['atten_step'])
freqpts = arange(self.cfg[self.expt_cfg_name]['freq_start'], self.cfg[self.expt_cfg_name]['freq_stop'], self.cfg[self.expt_cfg_name]['freq_step'])
# (channel, atten, freq, g/e/f, average)
ss_cos_data_all = zeros((2, len(attenpts), len(freqpts), 3, avgPerAcquisition * numAcquisition) )
ss_sin_data_all = zeros((2, len(attenpts), len(freqpts), 3, avgPerAcquisition * numAcquisition) )
for xx, atten in enumerate(attenpts):
try:
# im = InstrumentManager()
# atten2 = im['atten2']
# atten2.set_attenuator(atten)
self.readout_atten.set_attenuator(atten)
print(atten, "Digital atten:") #, self.readout_atten.get_attenuator())
time.sleep(0.5)
atten2 = None
except:
print("Digital attenuator not loaded.")
# pump_freqs = arange(6.90e9, 7.04e9, 4e6)
# pump_powers = arange(-6.0, -5, 0.2)
#
# self.im['RF6'].set_power( pump_powers[(atten % 5)] )
# print("TWPA Pump power:", pump_powers[(atten % 5)])
# self.im['RF6'].set_frequency( pump_freqs[int(atten/5)] )
# print("TWPA Pump freq:", pump_freqs[int(atten/5)])
#
# try:
# self.readout_atten.set_attenuator(16.0)
# # print("Digital atten:", atten)
# except:
# print("Digital attenuator not loaded.")
# (ch1/2, exp_pts, heterodyne_freq, cos/sin, all averages)
ss_data = zeros((2, len(self.expt_pts), len(het_IFreqList), 2, avgPerAcquisition * numAcquisition))
for ii in tqdm(arange(numAcquisition)):
if not self.cfg['readout']['is_hetero_phase_ref']:
# single_data1/2: index: (hetero_freqs, cos/sin, all_seqs)
single_data1, single_data2, single_record1, single_record2 = \
adc.acquire_singleshot_heterodyne_multitone_data(het_IFreqList, prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'])
# saving the raw time traces
# single_data1, single_data2, single_record1, single_record2 = \
# adc.acquire_singleshot_heterodyne_multitone_data(het_IFreqList, prep_function=self.awg_prep,
# start_function=self.awg_run,
# excise=None, save_raw_data=True)
else:
# single_data1/2: index: (hetero_freqs, cos/sin, all_seqs)
single_data1, single_data2, single_record1, single_record2 = \
adc.acquire_singleshot_heterodyne_multitone_data_phase_ref(het_IFreqList,
self.cfg['readout']['hetero_phase_ref_freq'],
prep_function=self.awg_prep,
start_function=self.awg_run,
excise=self.cfg['readout']['window'],
isCompensatePhase=True,
save_raw_data=False)
single_data = array([single_data1, single_data2])
# reshape to fit into histogram data
# index: (ch1/2, hetero_freqs(0), cos / sin, avgs, freqpts(exp seq), g/e/f)
single_data = np.reshape(single_data,
(single_data.shape[0], single_data.shape[1], single_data.shape[2],
int(self.cfg['alazar'][
'recordsPerAcquisition'] / self.pulse_sequence.sequence_length),
int(self.pulse_sequence.sequence_length/3), 3))
# (channel, hetero_freqs(0), cos/sin, freqpts(exp seq), g/e/f, average)
single_data = np.transpose(single_data, (0, 1, 2, 4, 5, 3))
# (channel, atten, freqpts, g/e/f, average)
ss_cos_data_all[:, xx, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:, 0, 0, :, :, :]
ss_sin_data_all[:, xx, :, :, (ii * avgPerAcquisition):((ii + 1) * avgPerAcquisition)] = single_data[:, 0, 1, :, :, :]
# this needs to stay here
self.slab_file = self.datafile(data_file=self.data_file)
with self.slab_file as f:
f.add('attenpts', attenpts)
f.add('freqpts', freqpts)
f.add('het_IFreqList', het_IFreqList)
f.add('ss_cos_data_ch1', ss_cos_data_all[0])
f.add('ss_cos_data_ch2', ss_cos_data_all[1])
f.add('ss_sin_data_ch1', ss_sin_data_all[0])
f.add('ss_sin_data_ch2', ss_sin_data_all[1])
f.append_line('single_record1', single_record1)
f.append_line('single_record2', single_record2)
f.close()
###
# if self.post_run is not None:
# self.post_run(self.expt_pts, expt_avg_data)
if self.cfg['stop_awgs'] == True:
self.awg_prep()
# close Alazar and release buffer
adc.close()
def go(self):
if self.liveplot_enabled:
self.plotter.clear()
print("Prep Instruments")
self.readout.set_frequency(self.cfg['readout']['frequency'])
self.readout.set_power(self.cfg['readout']['power'])
self.readout.set_ext_pulse(mod=True)
# self.readout_shifter.set_phase(self.cfg['readout']['start_phase'] + self.cfg['readout']['phase_slope'] * (
# self.cfg['readout']['frequency'] - self.cfg['readout']['bare_frequency']), self.cfg['readout']['frequency'])
self.drive.set_frequency(
self.cfg['qubit']['frequency'] -
self.cfg['pulse_info'][self.pulse_type]['iq_freq'])
self.drive.set_power(self.cfg['drive']['power'])
self.drive.set_ext_pulse(mod=True)
self.drive.set_output(True)
self.readout_atten.set_attenuator(self.cfg['readout']['dig_atten'])
self.trigger.set_period(self.trigger_period)
try:
self.cfg['freq_flux']['flux'] = self.extra_args['flux']
except:
pass
try:
self.cfg['freq_flux']['freq_flux_slope'] = self.extra_args[
'freq_flux_slope']
except:
pass
try:
self.cfg['freq_flux']['flux_offset'] += self.extra_args[
'flux_offset']
except:
pass
if self.cfg['freq_flux']['current']:
try:
self.flux_volt.ramp_current(self.cfg['freq_flux']['flux'])
except:
pass
elif self.cfg['freq_flux']['voltage']:
try:
self.flux_volt.ramp_volt(self.cfg['freq_flux']['flux'])
except:
pass
self.awg.set_amps_offsets(self.cfg['cal']['iq_amps'],
self.cfg['cal']['iq_offsets'])
if self.pre_run is not None:
self.pre_run()
if self.adc == None:
print("Prep Card")
adc = Alazar(self.cfg['alazar'])
else:
adc = self.adc
expt_data = None
current_data = None
for ii in tqdm(
arange(max(1,
self.cfg[self.expt_cfg_name]['averages'] / 100))):
tpts, ch1_pts, ch2_pts = adc.acquire_avg_data_by_record(
prep_function=self.awg_prep,
start_function=self.awg.run,
excise=self.cfg['readout']['window'])
### to skip the first 100 averages data point, because we saw a weird ramp in the RF output
if ii == 0:
time.sleep(0.1)
continue
mag = sqrt(ch1_pts**2 + ch2_pts**2)
if not self.cfg[self.expt_cfg_name]['use_pi_calibration']:
if expt_data is None:
if self.cfg['readout']['channel'] == 1:
expt_data = ch1_pts
elif self.cfg['readout']['channel'] == 2:
expt_data = ch2_pts
else:
if self.cfg['readout']['channel'] == 1:
expt_data = (expt_data * ii + ch1_pts) / (ii + 1.0)
elif self.cfg['readout']['channel'] == 2:
expt_data = (expt_data * ii + ch2_pts) / (ii + 1.0)
expt_avg_data = mean(expt_data, 1)
else:
if expt_data is None:
if self.cfg['readout']['channel'] == 1:
expt_data = ch1_pts
elif self.cfg['readout']['channel'] == 2:
expt_data = ch2_pts
else:
if self.cfg['readout']['channel'] == 1:
expt_data = (expt_data * ii + ch1_pts) / (ii + 1.0)
elif self.cfg['readout']['channel'] == 2:
expt_data = (expt_data * ii + ch2_pts) / (ii + 1.0)
expt_avg_data = mean(expt_data, 1)
expt_avg_data = (expt_avg_data[:-2] - expt_avg_data[-2]) / (
expt_avg_data[-1] - expt_avg_data[-2])
# temporary hack. Alazar card seems to shift two data points (problem disappeared after reboot computer)
# expt_avg_data = np.concatenate((expt_avg_data[2:],expt_avg_data[:2]))
# if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
# expt_avg_data = (expt_avg_data[:-2]-expt_avg_data[-2])/(expt_avg_data[-1]-expt_avg_data[-2])
# else:
# if self.cfg['readout']['channel']==1:
# zero_amp = mean(ch1_pts[-2])
# pi_amp = mean(ch1_pts[-1])
# current_data= (ch1_pts[:-2]-zero_amp)/(pi_amp-zero_amp)
# elif self.cfg['readout']['channel']==2:
# zero_amp = mean(ch2_pts[-2])
# pi_amp = mean(ch2_pts[-1])
# current_data= (ch2_pts[:-2]-zero_amp)/(pi_amp-zero_amp)
# if expt_data is None:
# expt_data = current_data
# else:
# expt_data = (expt_data * ii + current_data) / (ii + 1.0)
# expt_avg_data = mean(expt_data, 1)
if self.liveplot_enabled:
self.plotter.plot_z(self.prefix + ' Data', expt_data.T)
self.plotter.plot_xy(self.prefix + ' XY',
self.pulse_sequence.expt_pts,
expt_avg_data)
# print ii * min(self.cfg[self.expt_cfg_name]['averages'], 100)
if self.data_file == None:
self.slab_file = self.datafile()
with self.slab_file as f:
f.add('expt_2d', expt_data)
f.add('expt_avg_data', expt_avg_data)
f.add('expt_pts', self.expt_pts)
f.close()
if self.data_file != None:
self.slab_file = SlabFile(self.data_file)
with self.slab_file as f:
f.append_line('expt_avg_data', expt_avg_data)
f.append_line('expt_pts', self.expt_pts)
f.close()
if not self.adc_predefined:
adc.close()
if self.post_run is not None:
self.post_run(self.expt_pts, expt_avg_data)
def run_multimode_sequential_experiment(expt_name):
import os
import difflib
expt_list = ['Multimode_Rabi']
datapath = os.getcwd() + '\data'
config_file = os.path.join(datapath, "..\\config" + ".json")
with open(config_file, 'r') as fid:
cfg_str = fid.read()
cfg = AttrDict(json.loads(cfg_str))
def prepare_alazar(cfg, expt_name, expt=None):
if expt == None:
cfg['alazar']['samplesPerRecord'] = 2**(cfg['readout']['width'] -
1).bit_length()
sequence_length = int((cfg[expt_name.lower()]['stop'] -
cfg[expt_name.lower()]['start']) /
cfg[expt_name.lower()]['step'])
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
else:
cfg['alazar']['samplesPerRecord'] = 2**(cfg['readout']['width'] -
1).bit_length()
sequence_length = int((cfg[expt_name.lower()][expt]['stop'] -
cfg[expt_name.lower()][expt]['start']) /
cfg[expt_name.lower()][expt]['step'])
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length *
min(cfg[expt_name.lower()][expt]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
return adc
expt = None
experiment_started = False
if expt_name.lower() == 'calibrate_multimode':
experiment_started = True
multimode_pulse_calibration()
if expt_name.lower() == 'multimode_rabi_sweep':
experiment_started = True
cfg['alazar']['samplesPerRecord'] = 2**(cfg['readout']['width'] -
1).bit_length()
sequence_length = (
cfg[expt_name.lower()]['stop'] -
cfg[expt_name.lower()]['start']) / cfg[expt_name.lower()]['step']
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
flux_freq_pts = arange(cfg[expt_name.lower()]['freq_start'],
cfg[expt_name.lower()]['freq_stop'],
cfg[expt_name.lower()]['freq_step'])
prefix = 'Multimode_Rabi_Sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeRabiSweepExperiment
# Do Multimode Rabi
for ii, flux_freq in enumerate(flux_freq_pts):
print("Running Multimode Rabi Sweep with flux frequency: " +
str(flux_freq))
expt = MultimodeRabiSweepExperiment(path=datapath,
data_file=data_file,
adc=adc,
flux_freq=flux_freq,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
pass
if expt_name.lower() == 'multimode_ef_rabi_sweep':
experiment_started = True
cfg['alazar']['samplesPerRecord'] = 2**(cfg['readout']['width'] -
1).bit_length()
sequence_length = (
cfg[expt_name.lower()]['stop'] -
cfg[expt_name.lower()]['start']) / cfg[expt_name.lower()]['step']
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
flux_freq_pts = arange(cfg[expt_name.lower()]['freq_start'],
cfg[expt_name.lower()]['freq_stop'],
cfg[expt_name.lower()]['freq_step'])
prefix = 'Multimode_EF_Rabi_Sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeEFRabiSweepExperiment
# Do Multimode Rabi
for ii, flux_freq in enumerate(flux_freq_pts):
print("Running Multimode EF Rabi Sweep with flux frequency: " +
str(flux_freq))
expt = MultimodeEFRabiSweepExperiment(path=datapath,
data_file=data_file,
adc=adc,
flux_freq=flux_freq,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
pass
if expt_name.lower() == 'multimode_cphase_optimization_sweep':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import CPhaseOptimizationSweepExperiment
adc = prepare_alazar(cfg, expt_name)
idle_time_pts = arange(cfg[expt_name.lower()]['length_start'],
cfg[expt_name.lower()]['length_stop'],
cfg[expt_name.lower()]['length_step'])
prefix = 'multimode_cphase_optimization_sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
for ii, idle_time in enumerate(idle_time_pts):
print("Idle_time: " + str(idle_time))
expt = CPhaseOptimizationSweepExperiment(path=datapath,
data_file=data_file,
adc=adc,
idle_time=idle_time,
liveplot_enabled=True)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'multimode_general_entanglement':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeGeneralEntanglementExperiment
adc = prepare_alazar(cfg, expt_name)
list_num = array([7])
for list in list_num:
if (list == 2):
idm_list = array([9, 1, 6, 4, 5, 3])
numberlist = arange(3, 1, -1)
elif (list == 3):
idm_list = array([9, 6, 1, 4, 5, 3])
numberlist = arange(6, 1, -1)
elif (list == 4):
idm_list = array([6, 1, 4, 5, 9, 3])
numberlist = arange(6, 1, -1)
elif (list == 5):
idm_list = array([1, 4, 6, 5, 9, 3])
numberlist = array([3])
elif (list == 6):
idm_list = array([1, 6, 9, 4, 5, 3])
# numberlist =arange(6,1,-1)
numberlist = array([3])
elif (list == 7):
idm_list = array([6, 1, 9, 4, 5, 3])
# numberlist =arange(6,1,-1)
numberlist = array([3])
for number in numberlist:
# frequency_stabilization()
for ii, idm in enumerate(idm_list):
prefix = 'multimode_general_entanglement_' + str(
number) + '_l_' + str(list) + '_experiment'
data_file = os.path.join(
datapath,
get_next_filename(datapath, prefix, suffix='.h5'))
print("Measured mode " + str(idm))
expt = MultimodeGeneralEntanglementExperiment(
path=datapath,
data_file=data_file,
adc=adc,
idm=idm,
id1=idm_list[0],
id2=idm_list[1],
id3=idm_list[2],
id4=idm_list[3],
id5=idm_list[4],
id6=idm_list[5],
number=number,
liveplot_enabled=True)
expt.go()
# expt.save_config()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'multimode_two_resonator_tomography_phase_sweep':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import \
MultimodeTwoResonatorTomographyPhaseSweepExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
adc = prepare_alazar(cfg, expt_name)
tom_pts = arange(0, 15)
state_pts = arange(3, 7)
prefix = 'multimode_two_resonator_tomography_phase_sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
for state_num in state_pts:
print("State_number: " + str(state_num))
# frequency_stabilization()
for ii, tomography_num in enumerate(tom_pts):
prefix = 'multimode_two_resonator_tomography_phase_sweep_' + str(
state_num) + '_' + str(tomography_num) + '_experiment'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
print("Tomography_pulse_number: " + str(tomography_num))
expt = MultimodeTwoResonatorTomographyPhaseSweepExperiment(
path=datapath,
data_file=data_file,
adc=adc,
tomography_num=tomography_num,
state_num=state_num,
liveplot_enabled=True)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'multimode_three_mode_correlation_experiment':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import \
MultimodeThreeModeCorrelationExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
adc = prepare_alazar(cfg, expt_name)
# tom_pts = arange(0, 9)
state_pts = array([0])
tom_pts = array([7])
prefix = 'multimode_two_resonator_tomography_phase_sweep'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix, suffix='.h5'))
for state_num in state_pts:
print("State_number: " + str(state_num))
# frequency_stabilization()
for ii, tomography_num in enumerate(tom_pts):
prefix = 'multimode_three_mode_tomography_4_' + str(
state_num) + '_' + str(tomography_num) + '_experiment'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
print("Tomography_pulse_number: " + str(tomography_num))
expt = MultimodeThreeModeCorrelationExperiment(
path=datapath,
data_file=data_file,
adc=adc,
tomography_num=tomography_num,
state_num=state_num,
liveplot_enabled=True)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'multimode_calibrate_offset_experiment':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeCalibrateOffsetExperiment
calibrate_sideband = False
save_to_file = True
# mode_pts = array([0, 1, 3, 4, 5, 6, 9])
mode_pts = array([4])
for ii, mode_num in enumerate(mode_pts):
if calibrate_sideband:
adc = prepare_alazar(cfg, expt_name, 'multimode_rabi')
prefix = 'multimode_rabi_mode_' + str(mode_num) + '_experiment'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
expt = MultimodeCalibrateOffsetExperiment(
path=datapath,
data_file=data_file,
adc=adc,
exp='multimode_rabi',
dc_offset_guess=0,
mode=mode_num,
data_prefix=prefix,
liveplot_enabled=True)
expt.go()
if save_to_file:
expt.save_config()
print(
"Saved Multimode Rabi pi and 2pi lengths to the config file"
)
else:
pass
adc.close()
expt = None
del expt
gc.collect()
else:
adc = prepare_alazar(cfg, expt_name, 'short_multimode_ramsey')
prefix = 'short_multimode_ramsey_mode_' + str(
mode_num) + '_experiment'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
expt = MultimodeCalibrateOffsetExperiment(
path=datapath,
data_file=data_file,
adc=adc,
exp='short_multimode_ramsey',
dc_offset_guess=0,
mode=mode_num,
liveplot_enabled=True)
expt.go()
print(expt.suggested_dc_offset_freq)
dc_offset_guess = expt.suggested_dc_offset_freq
adc.close()
expt = None
del expt
gc.collect()
adc = prepare_alazar(cfg, expt_name, 'long_multimode_ramsey')
prefix = 'long_multimode_ramsey_mode_' + str(
mode_num) + '_experiment'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
expt = MultimodeCalibrateOffsetExperiment(
path=datapath,
data_file=data_file,
adc=adc,
exp='long_multimode_ramsey',
mode=mode_num,
dc_offset_guess=dc_offset_guess,
liveplot_enabled=True)
expt.go()
print(expt.suggested_dc_offset_freq)
expt.save_config()
expt = None
adc.close()
gc.collect()
if expt_name.lower() == 'multimode_calibrate_ef_sideband_experiment':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeCalibrateEFSidebandExperiment
mode_pts = array([6, 9])
calibrate_sideband = False
save_to_file = True
for ii, mode_num in enumerate(mode_pts):
if calibrate_sideband:
adc = prepare_alazar(cfg, expt_name, 'multimode_ef_rabi')
prefix = 'multimode_ef_rabi_mode_' + str(
mode_num) + '_experiment'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
expt = MultimodeCalibrateEFSidebandExperiment(
path=datapath,
data_file=data_file,
adc=adc,
exp='multimode_ef_rabi',
dc_offset_guess_ef=0,
mode=mode_num,
liveplot_enabled=True)
expt.go()
expt.save_config()
adc.close()
expt = None
print()
del expt
gc.collect()
print("Calibrated ge sideband for mode %s" % (mode_num))
else:
adc = prepare_alazar(cfg, expt_name,
'short_multimode_ef_ramsey')
prefix = 'multimode_ef_ramsey_mode_' + str(
mode_num) + '_experiment'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
expt = MultimodeCalibrateEFSidebandExperiment(
path=datapath,
data_file=data_file,
adc=adc,
exp='short_multimode_ef_ramsey',
dc_offset_guess_ef=0,
mode=mode_num,
liveplot_enabled=True)
expt.go()
print(expt.suggested_dc_offset_freq_ef)
dc_offset_guess_ef = expt.suggested_dc_offset_freq_ef
adc.close()
expt = None
print()
del expt
gc.collect()
adc = prepare_alazar(cfg, expt_name,
'long_multimode_ef_ramsey')
prefix = 'long_multimode_ef_ramsey_mode_' + str(
mode_num) + '_experiment'
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
expt = MultimodeCalibrateEFSidebandExperiment(
path=datapath,
data_file=data_file,
adc=adc,
exp='long_multimode_ef_ramsey',
mode=mode_num,
dc_offset_guess_ef=dc_offset_guess_ef,
liveplot_enabled=True)
expt.go()
print(expt.suggested_dc_offset_freq_ef)
expt.save_config()
expt = None
adc.close()
gc.collect()
if expt_name.lower() == 'multimode_dc_offset_experiment':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeDCOffsetExperiment
# freq_pts = [2.14e9,2.45e9,2.63e9,2.94e9]
freq_pts = linspace(1328859060.4, 2e9, 100)
amp_pts = array([0.25])
i = 7
j = 0
frequency_stabilization()
adc = prepare_alazar(cfg, expt_name)
for freq in freq_pts:
# i+=1
for ii, amp in enumerate(amp_pts):
if j % 10 == 0:
frequency_stabilization()
j += 1
prefix1 = 'Multimode_DC_Offset_'
prefix2 = str(i)
prefix3 = '_Experiment'
prefix = prefix1 + prefix2 + prefix3
data_file = os.path.join(
datapath, get_next_filename(datapath, prefix,
suffix='.h5'))
expt = MultimodeDCOffsetExperiment(path=datapath,
data_file=data_file,
adc=adc,
amp=amp,
freq=freq,
data_prefix=prefix,
liveplot_enabled=True)
expt.go()
expt = None
print()
del expt
gc.collect()
adc.close()
if expt_name.lower() == 'sequential_single_mode_randomized_benchmarking':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeSingleResonatorRandomizedBenchmarkingExperiment
for i in arange(32):
pulse_calibration(phase_exp=True)
multimode_pulse_calibration()
expt = MultimodeSingleResonatorRandomizedBenchmarkingExperiment(
liveplot_enabled=False, path=datapath, trigger_period=0.001)
expt.go()
del expt
gc.collect()
if not experiment_started:
close_match = difflib.get_close_matches(expt_name, expt_list)
print("No experiment found for: " + expt_name)
print("Do you mean: " + close_match[0] + "?")
def run_multimode_sequential_experiment(expt_name):
import os
import difflib
expt_list = ['Multimode_Rabi']
datapath = os.getcwd() + '\data'
config_file = os.path.join(datapath, "..\\config" + ".json")
with open(config_file, 'r') as fid:
cfg_str = fid.read()
cfg = AttrDict(json.loads(cfg_str))
def prepare_alazar(cfg, expt_name, expt=None):
if expt == None:
cfg['alazar']['samplesPerRecord'] = 2 ** (cfg['readout']['width'] - 1).bit_length()
sequence_length = int(
(cfg[expt_name.lower()]['stop'] - cfg[expt_name.lower()]['start']) / cfg[expt_name.lower()]['step'])
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
else:
cfg['alazar']['samplesPerRecord'] = 2 ** (cfg['readout']['width'] - 1).bit_length()
sequence_length = int((cfg[expt_name.lower()][expt]['stop'] - cfg[expt_name.lower()][expt]['start']) /
cfg[expt_name.lower()][expt]['step'])
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()][expt]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
return adc
expt = None
experiment_started = False
if expt_name.lower() == 'calibrate_multimode':
experiment_started = True
multimode_pulse_calibration()
if expt_name.lower() == 'multimode_rabi_sweep':
experiment_started = True
cfg['alazar']['samplesPerRecord'] = 2 ** (cfg['readout']['width'] - 1).bit_length()
sequence_length = (cfg[expt_name.lower()]['stop'] - cfg[expt_name.lower()]['start']) / cfg[expt_name.lower()][
'step']
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
flux_freq_pts = arange(cfg[expt_name.lower()]['freq_start'], cfg[expt_name.lower()]['freq_stop'],
cfg[expt_name.lower()]['freq_step'])
prefix = 'Multimode_Rabi_Sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeRabiSweepExperiment
# Do Multimode Rabi
for ii, flux_freq in enumerate(flux_freq_pts):
print("Running Multimode Rabi Sweep with flux frequency: " + str(flux_freq))
expt = MultimodeRabiSweepExperiment(path=datapath, data_file=data_file, adc=adc, flux_freq=flux_freq,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
pass
if expt_name.lower() == 'multimode_ef_rabi_sweep':
experiment_started = True
cfg['alazar']['samplesPerRecord'] = 2 ** (cfg['readout']['width'] - 1).bit_length()
sequence_length = (cfg[expt_name.lower()]['stop'] - cfg[expt_name.lower()]['start']) / cfg[expt_name.lower()][
'step']
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length += 2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
flux_freq_pts = arange(cfg[expt_name.lower()]['freq_start'], cfg[expt_name.lower()]['freq_stop'],
cfg[expt_name.lower()]['freq_step'])
prefix = 'Multimode_EF_Rabi_Sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeEFRabiSweepExperiment
# Do Multimode Rabi
for ii, flux_freq in enumerate(flux_freq_pts):
print("Running Multimode EF Rabi Sweep with flux frequency: " + str(flux_freq))
expt = MultimodeEFRabiSweepExperiment(path=datapath, data_file=data_file, adc=adc, flux_freq=flux_freq,
liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
pass
if expt_name.lower() == 'multimode_cphase_optimization_sweep':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import CPhaseOptimizationSweepExperiment
adc = prepare_alazar(cfg, expt_name)
idle_time_pts = arange(cfg[expt_name.lower()]['length_start'], cfg[expt_name.lower()]['length_stop'],
cfg[expt_name.lower()]['length_step'])
prefix = 'multimode_cphase_optimization_sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
for ii, idle_time in enumerate(idle_time_pts):
print("Idle_time: " + str(idle_time))
expt = CPhaseOptimizationSweepExperiment(path=datapath, data_file=data_file, adc=adc, idle_time=idle_time,
liveplot_enabled=True)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'multimode_general_entanglement':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeGeneralEntanglementExperiment
adc = prepare_alazar(cfg, expt_name)
list_num = array([7])
for list in list_num:
if(list == 2):
idm_list = array([9, 1, 6, 4, 5, 3])
numberlist =arange(3,1,-1)
elif(list==3):
idm_list = array([9, 6, 1, 4, 5, 3])
numberlist =arange(6,1,-1)
elif(list==4):
idm_list = array([6, 1, 4, 5, 9, 3])
numberlist =arange(6,1,-1)
elif(list==5):
idm_list = array([1, 4, 6, 5, 9, 3])
numberlist =array([3])
elif(list==6):
idm_list = array([1,6,9,4,5,3])
# numberlist =arange(6,1,-1)
numberlist =array([3])
elif(list==7):
idm_list = array([6,1,9,4,5,3])
# numberlist =arange(6,1,-1)
numberlist =array([3])
for number in numberlist:
# frequency_stabilization()
for ii, idm in enumerate(idm_list):
prefix = 'multimode_general_entanglement_' + str(number) + '_l_' + str(list)+'_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
print("Measured mode " + str(idm))
expt = MultimodeGeneralEntanglementExperiment(path=datapath, data_file=data_file, adc=adc, idm=idm, id1=idm_list[0],
id2=idm_list[1], id3=idm_list[2], id4=idm_list[3], id5=idm_list[4], id6=idm_list[5], number=number,
liveplot_enabled=True)
expt.go()
# expt.save_config()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'multimode_two_resonator_tomography_phase_sweep':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import \
MultimodeTwoResonatorTomographyPhaseSweepExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
adc = prepare_alazar(cfg, expt_name)
tom_pts = arange(0, 15)
state_pts = arange(3, 7)
prefix = 'multimode_two_resonator_tomography_phase_sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
for state_num in state_pts:
print("State_number: " + str(state_num))
# frequency_stabilization()
for ii, tomography_num in enumerate(tom_pts):
prefix = 'multimode_two_resonator_tomography_phase_sweep_' + str(state_num) + '_' + str(
tomography_num) + '_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
print("Tomography_pulse_number: " + str(tomography_num))
expt = MultimodeTwoResonatorTomographyPhaseSweepExperiment(path=datapath, data_file=data_file, adc=adc,
tomography_num=tomography_num,
state_num=state_num, liveplot_enabled=True)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'multimode_three_mode_correlation_experiment':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import \
MultimodeThreeModeCorrelationExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
adc = prepare_alazar(cfg, expt_name)
# tom_pts = arange(0, 9)
state_pts = array([0])
tom_pts =array([7])
prefix = 'multimode_two_resonator_tomography_phase_sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
for state_num in state_pts:
print("State_number: " + str(state_num))
# frequency_stabilization()
for ii, tomography_num in enumerate(tom_pts):
prefix = 'multimode_three_mode_tomography_4_' + str(state_num) + '_' + str(
tomography_num) + '_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
print("Tomography_pulse_number: " + str(tomography_num))
expt = MultimodeThreeModeCorrelationExperiment(path=datapath, data_file=data_file, adc=adc,
tomography_num=tomography_num,
state_num=state_num, liveplot_enabled=True)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'multimode_calibrate_offset_experiment':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeCalibrateOffsetExperiment
calibrate_sideband = False
save_to_file = True
# mode_pts = array([0, 1, 3, 4, 5, 6, 9])
mode_pts = array([4])
for ii, mode_num in enumerate(mode_pts):
if calibrate_sideband:
adc = prepare_alazar(cfg, expt_name, 'multimode_rabi')
prefix = 'multimode_rabi_mode_' + str(mode_num) + '_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
expt = MultimodeCalibrateOffsetExperiment(path=datapath, data_file=data_file, adc=adc,
exp='multimode_rabi', dc_offset_guess=0, mode=mode_num,
data_prefix = prefix,
liveplot_enabled=True)
expt.go()
if save_to_file:
expt.save_config()
print("Saved Multimode Rabi pi and 2pi lengths to the config file")
else:
pass
adc.close()
expt = None
del expt
gc.collect()
else:
adc = prepare_alazar(cfg, expt_name, 'short_multimode_ramsey')
prefix = 'short_multimode_ramsey_mode_' + str(mode_num) + '_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
expt = MultimodeCalibrateOffsetExperiment(path=datapath, data_file=data_file, adc=adc,
exp='short_multimode_ramsey', dc_offset_guess=0,
mode=mode_num, liveplot_enabled=True)
expt.go()
print(expt.suggested_dc_offset_freq)
dc_offset_guess = expt.suggested_dc_offset_freq
adc.close()
expt = None
del expt
gc.collect()
adc = prepare_alazar(cfg, expt_name, 'long_multimode_ramsey')
prefix = 'long_multimode_ramsey_mode_' + str(mode_num) + '_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
expt = MultimodeCalibrateOffsetExperiment(path=datapath, data_file=data_file, adc=adc,
exp='long_multimode_ramsey', mode=mode_num,
dc_offset_guess=dc_offset_guess, liveplot_enabled=True)
expt.go()
print(expt.suggested_dc_offset_freq)
expt.save_config()
expt = None
adc.close()
gc.collect()
if expt_name.lower() == 'multimode_calibrate_ef_sideband_experiment':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeCalibrateEFSidebandExperiment
mode_pts = array([6,9])
calibrate_sideband = False
save_to_file = True
for ii, mode_num in enumerate(mode_pts):
if calibrate_sideband:
adc = prepare_alazar(cfg, expt_name, 'multimode_ef_rabi')
prefix = 'multimode_ef_rabi_mode_' + str(mode_num) + '_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
expt = MultimodeCalibrateEFSidebandExperiment(path=datapath, data_file=data_file, adc=adc,
exp='multimode_ef_rabi', dc_offset_guess_ef=0,
mode=mode_num, liveplot_enabled=True)
expt.go()
expt.save_config()
adc.close()
expt = None
print()
del expt
gc.collect()
print("Calibrated ge sideband for mode %s" %(mode_num))
else:
adc = prepare_alazar(cfg, expt_name, 'short_multimode_ef_ramsey')
prefix = 'multimode_ef_ramsey_mode_' + str(mode_num) + '_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
expt = MultimodeCalibrateEFSidebandExperiment(path=datapath, data_file=data_file, adc=adc,
exp='short_multimode_ef_ramsey', dc_offset_guess_ef=0,
mode=mode_num, liveplot_enabled=True)
expt.go()
print(expt.suggested_dc_offset_freq_ef)
dc_offset_guess_ef = expt.suggested_dc_offset_freq_ef
adc.close()
expt = None
print()
del expt
gc.collect()
adc = prepare_alazar(cfg, expt_name, 'long_multimode_ef_ramsey')
prefix = 'long_multimode_ef_ramsey_mode_' + str(mode_num) + '_experiment'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
expt = MultimodeCalibrateEFSidebandExperiment(path=datapath, data_file=data_file, adc=adc,
exp='long_multimode_ef_ramsey', mode=mode_num,
dc_offset_guess_ef=dc_offset_guess_ef,
liveplot_enabled=True)
expt.go()
print(expt.suggested_dc_offset_freq_ef)
expt.save_config()
expt = None
adc.close()
gc.collect()
if expt_name.lower() == 'multimode_dc_offset_experiment':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeDCOffsetExperiment
# freq_pts = [2.14e9,2.45e9,2.63e9,2.94e9]
freq_pts = linspace(1328859060.4,2e9,100)
amp_pts = array([0.25])
i=7
j=0
frequency_stabilization()
adc = prepare_alazar(cfg, expt_name)
for freq in freq_pts:
# i+=1
for ii, amp in enumerate(amp_pts):
if j%10 == 0:
frequency_stabilization()
j+=1
prefix1 = 'Multimode_DC_Offset_'
prefix2 = str(i)
prefix3 = '_Experiment'
prefix = prefix1 + prefix2 + prefix3
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
expt = MultimodeDCOffsetExperiment(path=datapath, data_file=data_file, adc=adc,amp = amp, freq= freq, data_prefix = prefix, liveplot_enabled=True)
expt.go()
expt = None
print()
del expt
gc.collect()
adc.close()
if expt_name.lower() == 'sequential_single_mode_randomized_benchmarking':
experiment_started = True
from slab.experiments.Multimode.MultimodePulseSequenceExperiment import MultimodeSingleResonatorRandomizedBenchmarkingExperiment
for i in arange(32):
pulse_calibration(phase_exp=True)
multimode_pulse_calibration()
expt = MultimodeSingleResonatorRandomizedBenchmarkingExperiment(liveplot_enabled=False, path=datapath, trigger_period=0.001)
expt.go()
del expt
gc.collect()
if not experiment_started:
close_match = difflib.get_close_matches(expt_name, expt_list)
print("No experiment found for: " + expt_name)
print("Do you mean: " + close_match[0] + "?")
def run_sequential_experiment(expt_name):
import os
import difflib
expt_list = ['Frequency_Calibration','Rabi_Sweep','HalfPiXOptimization_sweep', 'tune_up_experiment']
datapath = os.getcwd() + '\data'
config_file = os.path.join(datapath, "..\\config" + ".json")
with open(config_file, 'r') as fid:
cfg_str = fid.read()
cfg = AttrDict(json.loads(cfg_str))
expt = None
experiment_started = False
if expt_name.lower() == 'calibration_experiment':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RabiExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRabiExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRamseyExperiment
# Do Frequency Calibration
expt = RamseyExperiment(path=datapath)
expt.go()
print(expt.offset_freq)
expt = RabiExperiment(path=datapath)
expt.go()
expt = EFRabiExperiment(path=datapath)
expt.go()
expt = EFRamseyExperiment(path=datapath)
expt.go()
del expt
gc.collect()
if expt_name.lower() == 'monitor_frequency_experiment':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRamseyExperiment
# Do Frequency Calibration
for i in arange(20):
expt = RamseyExperiment(path=datapath)
expt.go()
print(expt.offset_freq)
expt = EFRamseyExperiment(path=datapath)
expt.go()
del expt
gc.collect()
if expt_name.lower() == 'tomography_tune_up_experiment':
experiment_started = True
print(expt_name + " is running!")
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RamseyExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RabiExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRabiExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import EFRamseyExperiment
from slab.experiments.General.SingleQubitPulseSequenceExperiment import HalfPiYPhaseOptimizationExperiment
# Do Frequency Calibration
expt = RamseyExperiment(path=datapath)
expt.go()
if (abs(expt.offset_freq) < 50e3):
pass
else:
print(expt.flux)
flux_offset = -expt.offset_freq/(expt.freq_flux_slope)
print(flux_offset)
if (abs(flux_offset) < 0.000002):
flux2 = expt.flux + flux_offset
print(flux2)
expt = RamseyExperiment(path=datapath, flux = flux2)
expt.go()
offset_freq2 = expt.offset_freq
flux_offset2 = -expt.offset_freq/(expt.freq_flux_slope)
flux3 = flux2 + flux_offset2
if (abs(offset_freq2) < 50e3):
print("Great success! Frequency calibrated")
expt.save_config()
else:
if (abs(flux_offset2) < 0.000002):
expt = RamseyExperiment(path=datapath, flux = flux3)
expt.go()
if (abs(expt.offset_freq) < 100e3):
print("Frequency calibrated")
expt.save_config()
else:
print("Try again: not converged after 2 tries")
else:
print("Large change in flux is required; please do so manually")
pass
else:
print("Large change in flux is required; please do so manually")
pass
expt = RabiExperiment(path=datapath)
expt.go()
print("ge pi and pi/2 pulses recalibrated")
expt.save_config()
expt = EFRabiExperiment(path=datapath)
expt.go()
print("ef pi and pi/2 pulses recalibrated")
expt.save_config()
expt = EFRamseyExperiment(path=datapath)
expt.go()
expt.save_config()
expt.go()
# #
# expt = HalfPiYPhaseOptimizationExperiment(path=datapath)
# expt.go()
# #
# print flux2
del expt
gc.collect()
if expt_name.lower() == 'offset_phase_calibration_experiment':
qubit_dc_offset_list_pi = linspace(-0.25e6,0.25e6,5)
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import HalfPiYPhaseOptimizationExperiment
# Do Frequency Calibration
frequency_stabilization()
for qubit_dc_offset in qubit_dc_offset_list_pi:
expt = HalfPiYPhaseOptimizationExperiment(path=datapath, qubit_dc_offset = qubit_dc_offset)
expt.go()
expt.save_config()
del expt
gc.collect()
if expt_name.lower() == 'frequency_calibration':
frequency_stabilization()
if expt_name.lower() == 'rabi_sweep':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RabiSweepExperiment
cfg['alazar']['samplesPerRecord'] = 2 ** (cfg['readout']['width'] - 1).bit_length()
sequence_length = (cfg[expt_name.lower()]['stop']-cfg[expt_name.lower()]['start'])/cfg[expt_name.lower()]['step']
if (cfg[expt_name.lower()]['use_pi_calibration']):
sequence_length+=2
cfg['alazar']['recordsPerBuffer'] = sequence_length
cfg['alazar']['recordsPerAcquisition'] = int(
sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
print("Prep Card")
adc = Alazar(cfg['alazar'])
drive_freq_pts = arange(cfg[expt_name.lower()]['freq_start'],cfg[expt_name.lower()]['freq_stop'],cfg[expt_name.lower()]['freq_step'])
prefix = 'Rabi_Sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
for ii, drive_freq in enumerate(drive_freq_pts):
print(drive_freq)
expt = RabiSweepExperiment(path=datapath,data_file=data_file, adc=adc, drive_freq=drive_freq, liveplot_enabled=False)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'rabi_ramsey_t1_flux_sweep':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import RabiRamseyT1FluxSweepExperiment
prefix = 'rabi_ramsey_t1_flux_sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
flux_pts = load(r'S:\_Data\160711 - Nb Tunable Coupler\data\flux_total.npy')
drive_pts = load(r'S:\_Data\160711 - Nb Tunable Coupler\data\probe_frequencies_total.npy')
readout_pts = load(r'S:\_Data\160711 - Nb Tunable Coupler\data\read_frequencies_7_28.npy')
# flux_pts=[-0.012]
# drive_pts=[4.844e9]
# readout_pts=[5257100000.0]
qubit_alpha = cfg['qubit']['alpha']
for ii, flux in enumerate(flux_pts):
drive_freq = drive_pts[ii]
readout_freq = readout_pts[ii]
print("Flux: " + str(flux))
print("Drive frequency: " + str(drive_freq))
print("Readout frequency: " + str(readout_freq))
### 1st Rabi
print("### Running 1st Rabi.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep','rabi')
expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'rabi', flux = flux,data_file=data_file, adc=adc,drive_freq=drive_freq, readout_freq = readout_freq,liveplot_enabled=liveplot_enabled)
expt.go()
pi_length = expt.pi_length
half_pi_length = expt.half_pi_length
adc.close()
expt = None
del expt
gc.collect()
### 1st Ramsey
print("### Running 1st Ramsey.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep','ramsey')
expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'ramsey', flux = flux,half_pi_length=half_pi_length,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled)
expt.go()
suggested_qubit_freq = expt.suggested_qubit_freq
drive_freq = suggested_qubit_freq
adc.close()
expt = None
del expt
gc.collect()
### 2nd Rabi
print("### Running 2nd Rabi.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep','rabi')
expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'rabi', flux = flux,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled)
expt.go()
pi_length = expt.pi_length
half_pi_length = expt.half_pi_length
adc.close()
expt = None
del expt
gc.collect()
### Ramsey long
print("### Running Ramsey Long.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep','ramsey_long')
expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'ramsey_long', flux = flux,half_pi_length=half_pi_length,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled)
expt.go()
adc.close()
expt = None
del expt
gc.collect()
## Rabi Long
# print "### Running Rabi Long."
# adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep','rabi_long')
# expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'rabi_long', flux = flux,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled)
# expt.go()
# # pi_length = expt.pi_length
# # half_pi_length = expt.half_pi_length
#
# adc.close()
# expt = None
# del expt
# gc.collect()
### remove adc
adc = None
del adc
### t1
print("### Running T1.")
adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 't1')
expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 't1', flux = flux,pi_length=pi_length,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled)
expt.go()
adc.close()
expt = None
del expt
gc.collect()
# ### Pi/2 phase sweep
# print "### Running pi/2 phase sweep experiment"
# adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep','half_pi_phase_sweep')
# expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'half_pi_phase_sweep', flux = flux,half_pi_length=half_pi_length,data_file=data_file, adc=adc,drive_freq=drive_freq, readout_freq = readout_freq,liveplot_enabled=liveplot_enabled)
# expt.go()
#
# adc.close()
# expt = None
# del expt
# gc.collect()
#
#
# ### EF Rabi
# print "### Running EF Rabi."
# adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_rabi')
# expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'ef_rabi', flux = flux,pi_length=pi_length,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled, alpha=qubit_alpha)
# expt.go()
# ef_pi_length = expt.pi_length
# ef_half_pi_length = expt.half_pi_length
#
# adc.close()
# expt = None
# del expt
# gc.collect()
#
# ### EF Ramsey
# print "### Running EF Ramsey."
# adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_ramsey')
# expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'ef_ramsey', flux = flux,pi_length=pi_length,ef_half_pi_length=ef_half_pi_length,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled, alpha=qubit_alpha)
# expt.go()
# suggested_alpha_freq = expt.suggested_qubit_alpha
# print "Suggested alpha frequency: " + str(suggested_alpha_freq)
# qubit_alpha = suggested_alpha_freq
#
# adc.close()
# expt = None
# del expt
# gc.collect()
#
# ### EF Rabi
# print "### Running EF Rabi."
# adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_rabi')
# expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'ef_rabi', flux = flux,pi_length=pi_length,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled, alpha=qubit_alpha)
# expt.go()
# ef_pi_length = expt.pi_length
# ef_half_pi_length = expt.half_pi_length
#
# adc.close()
# expt = None
# del expt
# gc.collect()
#
#
# ### EF T1
# print "### Running EF T1."
# adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_t1')
# expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'ef_t1', flux = flux,pi_length=pi_length,ef_pi_length=ef_pi_length,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled, alpha=qubit_alpha)
# expt.go()
#
# adc.close()
# expt = None
# del expt
# gc.collect()
#
#
# ## EF Ramsey Long
# print "### Running EF Ramsey."
# adc = prepare_alazar(cfg, 'rabi_ramsey_t1_flux_sweep', 'ef_ramsey_long')
# expt = RabiRamseyT1FluxSweepExperiment(path=datapath,exp = 'ef_ramsey_long', flux = flux,pi_length=pi_length,ef_half_pi_length=ef_half_pi_length,data_file=data_file, adc=adc, drive_freq=drive_freq, readout_freq = readout_freq, liveplot_enabled=liveplot_enabled, alpha=qubit_alpha)
# expt.go()
# suggested_alpha_freq = expt.suggested_qubit_alpha
# print "Suggested alpha frequency: " + str(suggested_alpha_freq)
# qubit_alpha = suggested_alpha_freq
#
# adc.close()
# expt = None
# del expt
# gc.collect()
#
# ### remove adc
# adc = None
# del adc
#
# gc.collect()
if expt_name.lower() == 'halfpixoptimization_sweep':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import HalfPiXOptimizationSweepExperiment
adc = prepare_alazar(cfg, expt_name)
if cfg[expt_name.lower()]['sweep_param'] == "length":
pulse_sweep_pts = arange(cfg[expt_name.lower()]['length_start'],cfg[expt_name.lower()]['length_stop'],cfg[expt_name.lower()]['length_step'])
pulse_amp = cfg[expt_name.lower()]['amp']
elif cfg[expt_name.lower()]['sweep_param'] == "amp":
pulse_sweep_pts = arange(cfg[expt_name.lower()]['amp_start'],cfg[expt_name.lower()]['amp_stop'],cfg[expt_name.lower()]['amp_step'])
pulse_length = cfg[expt_name.lower()]['length']
prefix = 'HalfPiXOptimization_Sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
if cfg[expt_name.lower()]['sweep_param'] == "length":
for ii, pulse_sweep in enumerate(pulse_sweep_pts):
print("Pulse Sweep: " + str(pulse_sweep))
expt = HalfPiXOptimizationSweepExperiment(path=datapath,data_file=data_file, adc=adc, pulse_length=pulse_sweep, pulse_amp = pulse_amp, liveplot_enabled = False)
expt.go()
expt = None
del expt
gc.collect()
elif cfg[expt_name.lower()]['sweep_param'] == "amp":
for ii, pulse_sweep in enumerate(pulse_sweep_pts):
print("Pulse Sweep: " + str(pulse_sweep))
expt = HalfPiXOptimizationSweepExperiment(path=datapath,data_file=data_file, adc=adc, pulse_length=pulse_length, pulse_amp = pulse_sweep, liveplot_enabled = False)
expt.go()
expt = None
del expt
gc.collect()
if expt_name.lower() == 'pixoptimization_sweep':
experiment_started = True
from slab.experiments.General.SingleQubitPulseSequenceExperiment import PiXOptimizationSweepExperiment
# cfg['alazar']['samplesPerRecord'] = 2 ** (cfg['readout']['width'] - 1).bit_length()
# sequence_length = (cfg[expt_name.lower()]['stop']-cfg[expt_name.lower()]['start'])/cfg[expt_name.lower()]['step']
# if (cfg[expt_name.lower()]['use_pi_calibration']):
# sequence_length+=2
#
# cfg['alazar']['recordsPerBuffer'] = sequence_length
# cfg['alazar']['recordsPerAcquisition'] = int(
# sequence_length * min(cfg[expt_name.lower()]['averages'], 100))
# print "Prep Card"
# adc = Alazar(cfg['alazar'])
adc = prepare_alazar(cfg, expt_name)
if cfg[expt_name.lower()]['sweep_param'] == "length":
pulse_sweep_pts = arange(cfg[expt_name.lower()]['length_start'],cfg[expt_name.lower()]['length_stop'],cfg[expt_name.lower()]['length_step'])
pulse_amp = cfg[expt_name.lower()]['amp']
elif cfg[expt_name.lower()]['sweep_param'] == "amp":
pulse_sweep_pts = arange(cfg[expt_name.lower()]['amp_start'],cfg[expt_name.lower()]['amp_stop'],cfg[expt_name.lower()]['amp_step'])
pulse_length = cfg[expt_name.lower()]['length']
prefix = 'PiXOptimization_Sweep'
data_file = os.path.join(datapath, get_next_filename(datapath, prefix, suffix='.h5'))
# for ii, pulse_sweep in enumerate(pulse_sweep_pts):
# print "Pulse Sweep: " + str(pulse_sweep)
# expt = PiXOptimizationSweepExperiment(path=datapath,data_file=data_file, adc=adc, pulse_length=pulse_sweep, liveplot_enabled = False)
# expt.go()
#
# expt = None
# del expt
#
# gc.collect()
if cfg[expt_name.lower()]['sweep_param'] == "length":
for ii, pulse_sweep in enumerate(pulse_sweep_pts):
print("Pulse Sweep: " + str(pulse_sweep))
expt = PiXOptimizationSweepExperiment(path=datapath,data_file=data_file, adc=adc, pulse_length=pulse_sweep, pulse_amp = pulse_amp, liveplot_enabled = False)
expt.go()
expt = None
del expt
gc.collect()
elif cfg[expt_name.lower()]['sweep_param'] == "amp":
for ii, pulse_sweep in enumerate(pulse_sweep_pts):
print("Pulse Sweep: " + str(pulse_sweep))
expt = PiXOptimizationSweepExperiment(path=datapath,data_file=data_file, adc=adc, pulse_length=pulse_length, pulse_amp = pulse_sweep, liveplot_enabled = False)
expt.go()
expt = None
del expt
gc.collect()
if not experiment_started:
close_match = difflib.get_close_matches(expt_name, expt_list)
print("No experiment found for: " + expt_name)
print("Do you mean: " + close_match[0] + "?")
def go(self):
if self.liveplot_enabled:
self.plotter.clear()
print("Prep Instruments")
self.readout.set_frequency(self.cfg['readout']['frequency'])
self.readout.set_power(self.cfg['readout']['power'])
self.readout.set_ext_pulse(mod=True)
# self.readout_shifter.set_phase(self.cfg['readout']['start_phase'] + self.cfg['readout']['phase_slope'] * (
# self.cfg['readout']['frequency'] - self.cfg['readout']['bare_frequency']), self.cfg['readout']['frequency'])
self.drive.set_frequency(self.cfg['qubit']['frequency'] - self.cfg['pulse_info'][self.pulse_type]['iq_freq'])
self.drive.set_power(self.cfg['drive']['power'])
self.drive.set_ext_pulse(mod=True)
self.drive.set_output(True)
self.readout_atten.set_attenuator(self.cfg['readout']['dig_atten'])
self.trigger.set_period(self.trigger_period)
try:
self.cfg['freq_flux']['flux']=self.extra_args['flux']
except:
pass
try:
self.cfg['freq_flux']['freq_flux_slope']=self.extra_args['freq_flux_slope']
except:
pass
try:
self.cfg['freq_flux']['flux_offset']+=self.extra_args['flux_offset']
except:
pass
if self.cfg['freq_flux']['current']:
try: self.flux_volt.ramp_current(self.cfg['freq_flux']['flux'])
except:pass
elif self.cfg['freq_flux']['voltage']:
try: self.flux_volt.ramp_volt(self.cfg['freq_flux']['flux'])
except: pass
self.awg.set_amps_offsets(self.cfg['cal']['iq_amps'], self.cfg['cal']['iq_offsets'])
if self.pre_run is not None:
self.pre_run()
if self.adc==None:
print("Prep Card")
adc = Alazar(self.cfg['alazar'])
else:
adc = self.adc
expt_data = None
current_data = None
for ii in tqdm(arange(max(1, self.cfg[self.expt_cfg_name]['averages'] / 100))):
tpts, ch1_pts, ch2_pts = adc.acquire_avg_data_by_record(prep_function=self.awg_prep,
start_function=self.awg.run,
excise=self.cfg['readout']['window'])
### to skip the first 100 averages data point, because we saw a weird ramp in the RF output
if ii == 0:
time.sleep(0.1)
continue
mag = sqrt(ch1_pts**2+ch2_pts**2)
if not self.cfg[self.expt_cfg_name]['use_pi_calibration']:
if expt_data is None:
if self.cfg['readout']['channel']==1:
expt_data = ch1_pts
elif self.cfg['readout']['channel']==2:
expt_data = ch2_pts
else:
if self.cfg['readout']['channel']==1:
expt_data = (expt_data * ii + ch1_pts) / (ii + 1.0)
elif self.cfg['readout']['channel']==2:
expt_data = (expt_data * ii + ch2_pts) / (ii + 1.0)
expt_avg_data = mean(expt_data, 1)
else:
if expt_data is None:
if self.cfg['readout']['channel']==1:
expt_data = ch1_pts
elif self.cfg['readout']['channel']==2:
expt_data = ch2_pts
else:
if self.cfg['readout']['channel']==1:
expt_data = (expt_data * ii + ch1_pts) / (ii + 1.0)
elif self.cfg['readout']['channel']==2:
expt_data = (expt_data * ii + ch2_pts) / (ii + 1.0)
expt_avg_data = mean(expt_data, 1)
expt_avg_data = (expt_avg_data[:-2]-expt_avg_data[-2])/(expt_avg_data[-1]-expt_avg_data[-2])
# temporary hack. Alazar card seems to shift two data points (problem disappeared after reboot computer)
# expt_avg_data = np.concatenate((expt_avg_data[2:],expt_avg_data[:2]))
# if self.cfg[self.expt_cfg_name]['use_pi_calibration']:
# expt_avg_data = (expt_avg_data[:-2]-expt_avg_data[-2])/(expt_avg_data[-1]-expt_avg_data[-2])
# else:
# if self.cfg['readout']['channel']==1:
# zero_amp = mean(ch1_pts[-2])
# pi_amp = mean(ch1_pts[-1])
# current_data= (ch1_pts[:-2]-zero_amp)/(pi_amp-zero_amp)
# elif self.cfg['readout']['channel']==2:
# zero_amp = mean(ch2_pts[-2])
# pi_amp = mean(ch2_pts[-1])
# current_data= (ch2_pts[:-2]-zero_amp)/(pi_amp-zero_amp)
# if expt_data is None:
# expt_data = current_data
# else:
# expt_data = (expt_data * ii + current_data) / (ii + 1.0)
# expt_avg_data = mean(expt_data, 1)
if self.liveplot_enabled:
self.plotter.plot_z(self.prefix + ' Data', expt_data.T)
self.plotter.plot_xy(self.prefix + ' XY', self.pulse_sequence.expt_pts, expt_avg_data)
# print ii * min(self.cfg[self.expt_cfg_name]['averages'], 100)
if self.data_file == None:
self.slab_file = self.datafile()
with self.slab_file as f:
f.add('expt_2d', expt_data)
f.add('expt_avg_data', expt_avg_data)
f.add('expt_pts', self.expt_pts)
f.close()
if self.data_file != None:
self.slab_file = SlabFile(self.data_file)
with self.slab_file as f:
f.append_line('expt_avg_data', expt_avg_data)
f.append_line('expt_pts', self.expt_pts)
f.close()
if not self.adc_predefined:
adc.close()
if self.post_run is not None:
self.post_run(self.expt_pts, expt_avg_data)