def init_plot(self):
plot = ManualPlotter("CR" + str.lower(self.cal_type.name) + "Fit",
x_label=str.lower(self.cal_type.name),
y_label='$<Z_{' + self.qubit_names[1] + '}>$')
plot.add_data_trace("Data 0")
plot.add_fit_trace("Fit 0")
plot.add_data_trace("Data 1")
plot.add_fit_trace("Fit 1")
return plot
def init_plots(self):
self.re_plot = ManualPlotter("Fidelity - Real",
x_label='Bins',
y_label='Real Quadrature')
self.im_plot = ManualPlotter("Fidelity - Imag",
x_label='Bins',
y_label='Imag Quadrature')
self.re_plot.add_trace("Excited",
matplotlib_kwargs={
'color': 'r',
'linestyle': '-',
'linewidth': 2
})
self.re_plot.add_trace("Excited Gaussian Fit",
matplotlib_kwargs={
'color': 'r',
'linestyle': '--',
'linewidth': 2
})
self.re_plot.add_trace("Ground",
matplotlib_kwargs={
'color': 'b',
'linestyle': '-',
'linewidth': 2
})
self.re_plot.add_trace("Ground Gaussian Fit",
matplotlib_kwargs={
'color': 'b',
'linestyle': '--',
'linewidth': 2
})
self.im_plot.add_trace("Excited",
matplotlib_kwargs={
'color': 'r',
'linestyle': '-',
'linewidth': 2
})
self.im_plot.add_trace("Excited Gaussian Fit",
matplotlib_kwargs={
'color': 'r',
'linestyle': '--',
'linewidth': 2
})
self.im_plot.add_trace("Ground",
matplotlib_kwargs={
'color': 'b',
'linestyle': '-',
'linewidth': 2
})
self.im_plot.add_trace("Ground Gaussian Fit",
matplotlib_kwargs={
'color': 'b',
'linestyle': '--',
'linewidth': 2
})
self.add_manual_plotter(self.re_plot)
self.add_manual_plotter(self.im_plot)
def init_plot(self):
plot = ManualPlotter("Ramsey Fit",
x_label='Time (us)',
y_label='Amplitude (Arb. Units)')
plot.add_data_trace("Data")
plot.add_fit_trace("Fit")
return plot
def init_plot(self):
plot = ManualPlotter("Qubit Search",
x_label='Frequency (GHz)',
y_label='Amplitude (Arb. Units)')
plot.add_data_trace("Data")
plot.add_fit_trace("Fit")
return plot
def init_plots(self):
"""Initialize manual plotters for the mixer calibration. Three plot tabs open, one for I,Q offset, one for
phase skew, one for amplitude imbalance.
"""
self.plt1 = ManualPlotter(name="Mixer offset calibration",
x_label='{} {} offset (V)'.format(
self.channel, self.mixer),
y_label='Power (dBm)')
self.plt1.add_data_trace("I-offset", {'color': 'C1'})
self.plt1.add_data_trace("Q-offset", {'color': 'C2'})
self.plt1.add_fit_trace("Fit I-offset",
{'color': 'C1'}) #TODO: fix axis labels
self.plt1.add_fit_trace("Fit Q-offset", {'color': 'C2'})
self.plt2 = ManualPlotter(name="Mixer amp calibration",
x_label='{} {} amplitude (V)'.format(
self.channel, self.mixer),
y_label='Power (dBm)')
self.plt2.add_data_trace("amplitude_factor", {'color': 'C4'})
self.plt2.add_fit_trace("Fit amplitude_factor", {'color': 'C4'})
self.plt3 = ManualPlotter(name="Mixer phase calibration",
x_label='{} {} phase (rad)'.format(
self.channel, self.mixer),
y_label='Power (dBm)')
self.plt3.add_data_trace("phase_skew", {'color': 'C3'})
self.plt3.add_fit_trace("Fit phase_skew", {'color': 'C3'})
self.plotters = [self.plt1, self.plt2, self.plt3]
return self.plotters
class MixerCalibration(Calibration):
"""A calibration experiment that determines the optimal I and Q offsets, amplitude imbalance and phase imbalance
for single-sideband modulation of a mixer. Please see Analog Devices Application Note AN-1039 for an explanation
of the optimization of a mixer for maximum sideband supression.
"""
MIN_OFFSET = -0.4
MAX_OFFSET = 0.4
MIN_AMPLITUDE = 0.2
MAX_AMPLITUDE = 1.5
MIN_PHASE = -0.3
MAX_PHASE = 0.3
def __init__(self,
channel,
spectrum_analyzer,
mixer="control",
first_cal="phase",
offset_range=(-0.2, 0.2),
amp_range=(0.4, 0.8),
phase_range=(-np.pi / 2, np.pi / 2),
nsteps=101,
use_fit=True,
plot=True):
"""A mixer calibration for a specific LogicalChannel and mixer.
Args:
channel: The Auspex LogicalChannel for which to calibrate the mixer.
spectrum_analyzer: The spectrum analyzer instrument to use for calibration.
mixer (optional): 'control' or 'measure', the corresponding mixer to calibrate.
Defaults to 'control'.
first_cal (optional): 'phase' or 'amplitude'. Calibrate the phase skew or amplitude imbalance first.
Defaults to 'phase'.
offset_range (optional): I and Q offset range to sweep over. Defaults to (-0.2, 0.2).
amp_range (optional): Amplitude imbalance range to sweep over. Defaults to (0.4, 0.8).
phase_range (optional): Phase range to sweep over. Defaults to (-pi/2, pi/2).
nsteps (optional): Number of points to sweep over for each calibraton.
use_fit (optional): If true, find power minumum using a fit; otherwise use minimum value from data.
Defaults to True.
plot (optional): Plot the calibration as it happens.
"""
self.channel = channel
self.spectrum_analyzer = spectrum_analyzer
self.mixer = mixer
self.do_plotting = plot
self.first_cal = first_cal
self.offset_range = offset_range
self.amp_range = amp_range
self.phase_range = phase_range
self.nsteps = nsteps
self.use_fit = use_fit
super(MixerCalibration, self).__init__()
def init_plots(self):
"""Initialize manual plotters for the mixer calibration. Three plot tabs open, one for I,Q offset, one for
phase skew, one for amplitude imbalance.
"""
self.plt1 = ManualPlotter(name="Mixer offset calibration",
x_label='{} {} offset (V)'.format(
self.channel, self.mixer),
y_label='Power (dBm)')
self.plt1.add_data_trace("I-offset", {'color': 'C1'})
self.plt1.add_data_trace("Q-offset", {'color': 'C2'})
self.plt1.add_fit_trace("Fit I-offset",
{'color': 'C1'}) #TODO: fix axis labels
self.plt1.add_fit_trace("Fit Q-offset", {'color': 'C2'})
self.plt2 = ManualPlotter(name="Mixer amp calibration",
x_label='{} {} amplitude (V)'.format(
self.channel, self.mixer),
y_label='Power (dBm)')
self.plt2.add_data_trace("amplitude_factor", {'color': 'C4'})
self.plt2.add_fit_trace("Fit amplitude_factor", {'color': 'C4'})
self.plt3 = ManualPlotter(name="Mixer phase calibration",
x_label='{} {} phase (rad)'.format(
self.channel, self.mixer),
y_label='Power (dBm)')
self.plt3.add_data_trace("phase_skew", {'color': 'C3'})
self.plt3.add_fit_trace("Fit phase_skew", {'color': 'C3'})
self.plotters = [self.plt1, self.plt2, self.plt3]
return self.plotters
def _calibrate(self):
"""Run the actual calibration routine.
"""
offset_pts = np.linspace(self.offset_range[0], self.offset_range[1],
self.nsteps)
amp_pts = np.linspace(self.amp_range[0], self.amp_range[1],
self.nsteps)
phase_pts = np.linspace(self.phase_range[0], self.phase_range[1],
self.nsteps)
first_cal = self.first_cal
config_dict = {
"I_offset": 0.0,
"Q_offset": 0.0,
"phase_skew": 0.0,
"amplitude_factor": 1.0,
"sideband_modulation": False
}
I1_amps = self.run_sweeps("I_offset", offset_pts, config_dict)
try:
I1_offset, xpts, ypts = find_null_offset(offset_pts[1:],
I1_amps[1:],
use_fit=self.use_fit)
except:
raise ValueError("Could not find null offset")
self.plt1["I-offset"] = (offset_pts, I1_amps)
self.plt1["Fit I-offset"] = (xpts, ypts)
logger.info("Found first pass I offset of {}.".format(I1_offset))
config_dict['I_offset'] = I1_offset
Q1_amps = self.run_sweeps("Q_offset", offset_pts, config_dict)
try:
Q1_offset, xpts, ypts = find_null_offset(offset_pts[1:],
Q1_amps[1:],
use_fit=self.use_fit)
except:
raise ValueError("Could not find null offset")
self.plt1["Q-offset"] = (offset_pts, Q1_amps)
self.plt1["Fit Q-offset"] = (xpts, ypts)
logger.info("Found first pass Q offset of {}.".format(Q1_offset))
config_dict['Q_offset'] = Q1_offset
I2_amps = self.run_sweeps("I_offset", offset_pts, config_dict)
try:
I2_offset, xpts, ypts = find_null_offset(offset_pts[1:],
I2_amps[1:],
use_fit=self.use_fit)
except:
raise ValueError("Could not find null offset")
self.plt1["I-offset"] = (offset_pts, I2_amps)
self.plt1["Fit I-offset"] = (xpts, ypts)
logger.info("Found second pass I offset of {}.".format(I2_offset))
config_dict['I_offset'] = I2_offset
#this is a bit hacky but OK...
cals = {"phase": "phase_skew", "amplitude": "amplitude_factor"}
cal_pts = {"phase": phase_pts, "amplitude": amp_pts}
correct_plotter = {"phase": self.plt3, "amplitude": self.plt2}
cal_defaults = {"phase": 0.0, "amplitude": 1.0}
if first_cal not in cals.keys():
raise ValueError(
"First calibration should be one of ('phase, amplitude'). Instead got {}"
.format(first_cal))
second_cal = list(set(cals.keys()).difference({
first_cal,
}))[0]
config_dict['sideband_modulation'] = True
amps1 = self.run_sweeps(cals[first_cal], cal_pts[first_cal],
config_dict)
try:
offset1, xpts, ypts = find_null_offset(
cal_pts[first_cal][1:],
amps1[1:],
default=cal_defaults[first_cal],
use_fit=self.use_fit)
except:
raise ValueError("Could not find null offset")
correct_plotter[first_cal][cals[first_cal]] = (cal_pts[first_cal],
amps1)
correct_plotter[first_cal]["Fit " + cals[first_cal]] = (xpts, ypts)
logger.info("Found {} of {}.".format(
str.replace(cals[first_cal], '_', ' '), offset1))
config_dict[cals[first_cal]] = offset1
amps2 = self.run_sweeps(cals[second_cal], cal_pts[second_cal],
config_dict)
try:
offset2, xpts, ypts = find_null_offset(
cal_pts[second_cal][1:],
amps2[1:],
default=cal_defaults[second_cal],
use_fit=self.use_fit)
except:
raise ValueError("Could not find null offset")
correct_plotter[second_cal][cals[second_cal]] = (cal_pts[second_cal],
amps2)
correct_plotter[second_cal]["Fit " + cals[second_cal]] = (xpts, ypts)
logger.info("Found {} of {}.".format(
str.replace(cals[first_cal], '_', ' '), offset2))
config_dict[cals[second_cal]] = offset2
# if write_to_file:
# mce.write_to_file()
logger.info(
("Mixer calibration: I offset = {}, Q offset = {}, "
"Amplitude Imbalance = {}, Phase Skew = {}").format(
config_dict["I_offset"], config_dict["Q_offset"],
config_dict["amplitude_factor"], config_dict["phase_skew"]))
assert config_dict["I_offset"] > self.MIN_OFFSET and config_dict[
"I_offset"] < self.MAX_OFFSET, "I_offset looks suspicious."
assert config_dict["Q_offset"] > self.MIN_OFFSET and config_dict[
"Q_offset"] < self.MAX_OFFSET, "Q_offset looks suspicious."
assert config_dict[
"amplitude_factor"] > self.MIN_AMPLITUDE and config_dict[
"amplitude_factor"] < self.MAX_AMPLITUDE, "amplitude_factor looks suspicious."
assert config_dict["phase_skew"] > self.MIN_PHASE and config_dict[
"phase_skew"] < self.MAX_PHASE, "phase_skew looks suspicious."
self.succeeded = True
self.config_dict = config_dict
def update_settings(self):
"""Update the channel library settings to those found by calibration routine.
"""
self.exp._phys_chan.amp_factor = self.config_dict["amplitude_factor"]
self.exp._phys_chan.phase_skew = self.config_dict["phase_skew"]
self.exp._phys_chan.I_channel_offset = self.config_dict["I_offset"]
self.exp._phys_chan.Q_channel_offset = self.config_dict["Q_offset"]
def run_sweeps(self, sweep_parameter, pts, config_dict):
"""Run the calibration sweeps.
"""
self.exp = MixerCalibrationExperiment(self.channel,
self.spectrum_analyzer,
config_dict,
mixer=self.mixer)
self.exp.add_sweep(getattr(self.exp, sweep_parameter), pts)
self.exp.run_sweeps()
return self.exp.buff.get_data()[0]
class SingleShotFidelityExperiment(QubitExperiment):
"""Experiment to measure single-shot measurement fidelity of a qubit."""
def __init__(self,
qubit_names,
num_shots=10000,
expname=None,
meta_file=None,
save_data=False,
optimize=False,
set_threshold=True,
stream_type='Raw',
**kwargs):
"""Create a single shot fidelity measurement experiment. Assumes that there is a single shot measurement
filter in the filter pipeline.
Arguments:
qubit_names: Names of the qubits to be measured. (str)
num_shots: Total number of 0 and 1 measurements used to reconstruct fidelity histograms (int)
expname: Experiment name for data saving.
meta_file: Meta file for defining custom single-shot fidelity experiment.
save_data: If true, will save the raw or demodulated data.
optimize: if true, will set the swept parameters to their optimum values"""
super(SingleShotFidelityExperiment, self).__init__()
self.qubit_names = qubit_names if isinstance(qubit_names,
list) else [qubit_names]
self.qubit = [QubitFactory(qubit_name)
for qubit_name in qubit_names] if isinstance(
qubit_names, list) else QubitFactory(qubit_names)
# make a copy of the settings to restore default
self.saved_settings = config.load_meas_file(config.meas_file)
self.settings = deepcopy(self.saved_settings)
self.save_data = save_data
self.calibration = True
self.optimize = optimize
self.set_threshold = True
self.name = expname
self.cw_mode = False
self.repeats = num_shots
self.ss_stream_type = stream_type
if meta_file is None:
meta_file = SingleShot(self.qubit)
self._squash_round_robins()
QubitExpFactory.load_meta_info(self, meta_file)
QubitExpFactory.load_instruments(self)
QubitExpFactory.load_qubits(self)
QubitExpFactory.load_filters(self)
if 'sweeps' in self.settings:
QubitExpFactory.load_parameter_sweeps(experiment)
self.ssf = self.find_single_shot_filter()
self.leave_plot_server_open = True
def run_sweeps(self):
#For now, only update histograms if we don't have a parameter sweep.
if not self.sweeper.axes:
self.init_plots()
self.add_manual_plotter(self.re_plot)
self.add_manual_plotter(self.im_plot)
else:
if any([
x.save_kernel.value for x in self.filters.values()
if type(x) is SingleShotMeasurement
]):
logger.warning(
"Kernel saving is not supported if you have parameter sweeps!"
)
super(SingleShotFidelityExperiment, self).run_sweeps()
if not self.sweeper.axes:
self._update_histogram_plots()
if hasattr(self, 'extra_plot_server'):
try:
self.extra_plot_server.stop()
except:
pass
if self.set_threshold:
self.update_threshold()
if self.sweeper.axes and self.optimize:
#select the buffers/writers whose sources are singleshot filters
fid_buffers = [
buff for buff in self.buffers if self.settings['filters'][
buff.name]['source'].strip().split()[1] == 'fidelity'
]
if not fid_buffers:
raise NameError(
"Please connect a buffer to the single-shot filter output in order to optimize fidelity."
)
#set sweep parameters to the values that maximize fidelity. Then update the saved_settings with the new values
for buff in fid_buffers:
dataset, descriptor = buff.get_data(), buff.get_descriptor()
opt_ind = np.argmax(dataset['Data'])
for k, axis in enumerate(self.sweeper.axes):
instr_tree = axis.parameter.instr_tree
param_key = self.saved_settings['instruments']
for key in instr_tree[:-1]:
# go through the tree
param_key = param_key[key]
opt_value = float(dataset[axis.name][opt_ind])
# special case to set APS ch12 amplitudes
if instr_tree[-1] == 'amplitude' and instr_tree[
-2] in self.saved_settings['instruments'].keys():
param_key['tx_channels']['12']['1'][
'amplitude'] = round(float(opt_value), 5)
param_key['tx_channels']['12']['2'][
'amplitude'] = round(float(opt_value), 5)
else:
param_key[instr_tree[-1]] = opt_value
logger.info("Set{} to {}.".format(
" ".join(str(x) for x in instr_tree), opt_value))
if self.set_threshold or (
self.sweeper.axes and
self.optimize): # update settings if something was calibrated
config.dump_meas_file(self.saved_settings, config.meas_file)
def _update_histogram_plots(self):
pdf_data = self.get_results()
self.re_plot.set_data("Ground", pdf_data["I Bins"],
pdf_data["Ground I PDF"])
self.re_plot.set_data("Ground Gaussian Fit", pdf_data["I Bins"],
pdf_data["Ground I Gaussian PDF"])
self.re_plot.set_data("Excited", pdf_data["I Bins"],
pdf_data["Excited I PDF"])
self.re_plot.set_data("Excited Gaussian Fit", pdf_data["I Bins"],
pdf_data["Excited I Gaussian PDF"])
self.im_plot.set_data("Ground", pdf_data["Q Bins"],
pdf_data["Ground Q PDF"])
self.im_plot.set_data("Ground Gaussian Fit", pdf_data["Q Bins"],
pdf_data["Ground Q Gaussian PDF"])
self.im_plot.set_data("Excited", pdf_data["Q Bins"],
pdf_data["Excited Q PDF"])
self.im_plot.set_data("Excited Gaussian Fit", pdf_data["Q Bins"],
pdf_data["Excited Q Gaussian PDF"])
def update_threshold(self):
if 'I Threshold' in self.ssf[0].pdf_data:
self.saved_settings['filters'][self.qubit_to_stream_sel[
self.qubit.label]]['threshold'] = round(
float(self.ssf[0].pdf_data['I Threshold']), 6)
def init_plots(self):
self.re_plot = ManualPlotter("Fidelity - Real",
x_label='Bins',
y_label='Real Quadrature')
self.im_plot = ManualPlotter("Fidelity - Imag",
x_label='Bins',
y_label='Imag Quadrature')
self.re_plot.add_trace("Excited",
matplotlib_kwargs={
'color': 'r',
'linestyle': '-',
'linewidth': 2
})
self.re_plot.add_trace("Excited Gaussian Fit",
matplotlib_kwargs={
'color': 'r',
'linestyle': '--',
'linewidth': 2
})
self.re_plot.add_trace("Ground",
matplotlib_kwargs={
'color': 'b',
'linestyle': '-',
'linewidth': 2
})
self.re_plot.add_trace("Ground Gaussian Fit",
matplotlib_kwargs={
'color': 'b',
'linestyle': '--',
'linewidth': 2
})
self.im_plot.add_trace("Excited",
matplotlib_kwargs={
'color': 'r',
'linestyle': '-',
'linewidth': 2
})
self.im_plot.add_trace("Excited Gaussian Fit",
matplotlib_kwargs={
'color': 'r',
'linestyle': '--',
'linewidth': 2
})
self.im_plot.add_trace("Ground",
matplotlib_kwargs={
'color': 'b',
'linestyle': '-',
'linewidth': 2
})
self.im_plot.add_trace("Ground Gaussian Fit",
matplotlib_kwargs={
'color': 'b',
'linestyle': '--',
'linewidth': 2
})
def _squash_round_robins(self):
"""Make it so that the round robins are set to 1."""
digitizers = [
_ for _ in self.settings['instruments'].keys()
if 'nbr_round_robins' in self.settings['instruments'][_].keys()
]
for d in digitizers:
logger.info(
"Set digitizer {} round robins to 1 for single shot experiment."
.format(d))
self.settings['instruments'][d]['nbr_round_robins'] = 1
# disable averagers
for _, f in self.settings['filters'].items():
if f['type'] == 'Averager':
f['enabled'] = False
def find_single_shot_filter(self):
"""Make sure there is one single shot measurement filter in the pipeline."""
ssf = [
x for x in self.filters.values()
if type(x) is SingleShotMeasurement
]
if len(ssf) > 1:
raise NotImplementedError(
"Single shot fidelity for more than one qubit is not yet implemented."
)
elif len(ssf) == 0:
raise NameError(
"There do not appear to be any single-shot measurements in your filter pipeline. Please add one!"
)
return ssf
def get_results(self):
"""Get the PDF and fidelity numbers from the filters. Returns a dictionary of PDF data with the
filter names as keys."""
ssf = self.find_single_shot_filter()
if len(ssf) > 1: # not implemented
try:
return {x.name: x.pdf_data for x in ssf}
except AttributeError:
raise AttributeError(
"Could not find single shot PDF data in results. Did you run the sweeps?"
)
else:
try:
return ssf[0].pdf_data
except AttributeError:
raise AttributeError(
"Could not find single shot PDF data in results. Did you run the sweeps?"
)
pass
async def run(self):
r = np.power(self.amplitude.value, 2) + 0.1 * np.random.random()
await self.voltage.push(r)
await asyncio.sleep(0.01)
if __name__ == '__main__':
exp = TestExperiment()
exp.leave_plot_server_open = True
# Create the plotter and the actual traces we'll need
plt = ManualPlotter("Manual Plotting Test",
x_label='X Thing',
y_label='Y Thing')
plt.add_data_trace("Example Data")
plt.add_fit_trace("Example Fit")
buff = DataBuffer()
edges = [(exp.voltage, buff.sink)]
exp.set_graph(edges)
# Create a plotter callback
def plot_me(plot):
ys = buff.get_data()['voltage']
xs = buff.descriptor.axes[0].points
plot["Example Data"] = (xs, ys)
plot["Example Fit"] = (xs, ys + 0.1)
def calibrate_mixer(qubit,
mixer="control",
first_cal="phase",
write_to_file=True,
offset_range=(-0.2, 0.2),
amp_range=(0.6, 1.4),
phase_range=(-np.pi / 6, np.pi / 6),
nsteps=51):
"""Calibrates IQ mixer offset, amplitude imbalanace, and phase skew.
See Analog Devices Application note AN-1039. Parses instrument connectivity from
the experiment settings YAML.
Arguments:
qubit: Qubit identifier string.
mixer: One of ("control", "measure") to select which IQ channel is calibrated.
first_cal: One of ("phase", "amplitude") to select which adjustment is attempted
first. You should pick whichever the particular mixer is most sensitive to.
For example, a mixer with -40dBc sideband supression at 1 degree of phase skew
and 0.1 dB amplitude imbalance should calibrate the phase first.
"""
spm = auspex.config.single_plotter_mode
auspex.config.single_plotter_mode = True
def sweep_offset(name, pts):
mce.clear_sweeps()
mce.add_sweep(getattr(mce, name), pts)
mce.keep_instruments_connected = True
mce.run_sweeps()
offset_pts = np.linspace(offset_range[0], offset_range[1], nsteps)
amp_pts = np.linspace(amp_range[0], amp_range[1], nsteps)
phase_pts = np.linspace(phase_range[0], phase_range[1], nsteps)
buff = DataBuffer()
plt = ManualPlotter(name="Mixer offset calibration",
x_label='{} {} offset (V)'.format(qubit, mixer),
y_label='Power (dBm)')
plt.add_data_trace("I-offset", {'color': 'C1'})
plt.add_data_trace("Q-offset", {'color': 'C2'})
plt.add_fit_trace("Fit I-offset",
{'color': 'C1'}) #TODO: fix axis labels
plt.add_fit_trace("Fit Q-offset", {'color': 'C2'})
plt2 = ManualPlotter(name="Mixer amp/phase calibration",
x_label='{} {} amplitude (V)/phase (rad)'.format(
qubit, mixer),
y_label='Power (dBm)')
plt2.add_data_trace("phase_skew", {'color': 'C3'})
plt2.add_data_trace("amplitude_factor", {'color': 'C4'})
plt2.add_fit_trace("Fit phase_skew", {'color': 'C3'})
plt2.add_fit_trace("Fit amplitude_factor", {'color': 'C4'})
mce = MixerCalibrationExperiment(qubit, mixer=mixer)
mce.add_manual_plotter(plt)
mce.add_manual_plotter(plt2)
mce.leave_plot_server_open = True
QubitExpFactory.load_instruments(mce, mce.instruments_to_enable)
edges = [(mce.amplitude, buff.sink)]
mce.set_graph(edges)
sweep_offset("I_offset", offset_pts)
I1_amps = np.array([x[1] for x in buff.get_data()])
try:
I1_offset, xpts, ypts = find_null_offset(offset_pts[1:],
I1_amps[1:])
except:
mce.extra_plot_server.stop()
return
plt["I-offset"] = (offset_pts, I1_amps)
plt["Fit I-offset"] = (xpts, ypts)
logger.info("Found first pass I offset of {}.".format(I1_offset))
mce.I_offset.value = I1_offset
mce.first_exp = False # slight misnomer to indicate that no new plot is needed
sweep_offset("Q_offset", offset_pts)
Q1_amps = np.array([x[1] for x in buff.get_data()])
try:
Q1_offset, xpts, ypts = find_null_offset(offset_pts[1:],
Q1_amps[1:])
except:
mce.extra_plot_server.stop()
return
plt["Q-offset"] = (offset_pts, Q1_amps)
plt["Fit Q-offset"] = (xpts, ypts)
logger.info("Found first pass Q offset of {}.".format(Q1_offset))
mce.Q_offset.value = Q1_offset
sweep_offset("I_offset", offset_pts)
I2_amps = np.array([x[1] for x in buff.get_data()])
try:
I2_offset, xpts, ypts = find_null_offset(offset_pts[1:],
I2_amps[1:])
except:
mce.extra_plot_server.stop()
return
plt["I-offset"] = (offset_pts, I2_amps)
plt["Fit I-offset"] = (xpts, ypts)
logger.info("Found second pass I offset of {}.".format(I2_offset))
mce.I_offset.value = I2_offset
#this is a bit hacky but OK...
cals = {"phase": "phase_skew", "amplitude": "amplitude_factor"}
cal_pts = {"phase": phase_pts, "amplitude": amp_pts}
cal_defaults = {"phase": 0.0, "amplitude": 1.0}
if first_cal not in cals.keys():
raise ValueError(
"First calibration should be one of ('phase, amplitude'). Instead got {}"
.format(first_cal))
second_cal = list(set(cals.keys()).difference({
first_cal,
}))[0]
mce.sideband_modulation = True
sweep_offset(cals[first_cal], cal_pts[first_cal])
amps1 = np.array([x[1] for x in buff.get_data()])
try:
offset1, xpts, ypts = find_null_offset(
cal_pts[first_cal][1:],
amps1[1:],
default=cal_defaults[first_cal])
except:
mce.extra_plot_server.stop()
return
plt2[cals[first_cal]] = (cal_pts[first_cal], amps1)
plt2["Fit " + cals[first_cal]] = (xpts, ypts)
logger.info("Found {} of {}.".format(
str.replace(cals[first_cal], '_', ' '), offset1))
getattr(mce, cals[first_cal]).value = offset1
sweep_offset(cals[second_cal], cal_pts[second_cal])
amps2 = np.array([x[1] for x in buff.get_data()])
try:
offset2, xpts, ypts = find_null_offset(
cal_pts[second_cal][1:],
amps2[1:],
default=cal_defaults[second_cal])
except:
mce.extra_plot_server.stop()
return
plt2[cals[second_cal]] = (cal_pts[second_cal], amps2)
plt2["Fit " + cals[second_cal]] = (xpts, ypts)
logger.info("Found {} of {}.".format(
str.replace(cals[first_cal], '_', ' '), offset2))
getattr(mce, cals[second_cal]).value = offset2
mce.disconnect_instruments()
try:
mce.extra_plot_server.stop()
except:
logger.info('Mixer plot server was not successfully stopped.')
if write_to_file:
mce.write_to_file()
logger.info(("Mixer calibration: I offset = {}, Q offset = {}, "
"Amplitude Imbalance = {}, Phase Skew = {}").format(
mce.I_offset.value, mce.Q_offset.value,
mce.amplitude_factor.value, mce.phase_skew.value))
auspex.config.single_plotter_mode = spm
class SingleShotFidelityExperiment(QubitExperiment):
"""Experiment to measure single-shot measurement fidelity of a qubit.
Args:
qubit: qubit object
output_nodes (optional): the output node of the filter pipeline to use for single-shot readout. The default is choses, if single output.
meta_file (string, optional): path to the QGL sequence meta_file. Default to standard SingleShot sequence
optimize (bool, optional): if True and a qubit_sweep is added, set the parameter corresponding to the maximum measured fidelity at the end of the sweep
"""
def __init__(self,
qubit,
sample_name=None,
output_nodes=None,
meta_file=None,
optimize=True,
set_threshold=True,
**kwargs):
self.pdf_data = []
self.qubit = qubit
self.optimize = optimize
self.set_threshold = set_threshold
if meta_file:
self.meta_file = meta_file
else:
self.meta_file = self._single_shot_sequence(self.qubit)
super(SingleShotFidelityExperiment,
self).__init__(self.meta_file, **kwargs)
if not sample_name:
sample_name = self.qubit.label
if not bbndb.get_cl_session():
raise Exception("Attempting to load Calibrations database, \
but no database session is open! Have the ChannelLibrary and PipelineManager been created?"
)
existing_samples = list(bbndb.get_cl_session().query(
bbndb.calibration.Sample).filter_by(name=sample_name).all())
if len(existing_samples) == 0:
logger.info("Creating a new sample in the calibration database.")
self.sample = bbndb.calibration.Sample(name=sample_name)
bbndb.get_cl_session().add(self.sample)
elif len(existing_samples) == 1:
self.sample = existing_samples[0]
else:
raise Exception(
"Multiple samples found in calibration database with the same name! How?"
)
def guess_output_nodes(self, graph):
output_nodes = []
for qubit in self.qubits:
ds = nx.descendants(graph, self.qubit_proxies[qubit.label])
outputs = [
d for d in ds
if isinstance(d, (bbndb.auspex.Write, bbndb.auspex.Buffer))
]
if len(outputs) != 1:
raise Exception(
f"More than one output node found for {qubit}, please explicitly define output node using output_nodes argument."
)
output_nodes.append(outputs[0])
return output_nodes
def _single_shot_sequence(self, qubit):
seqs = create_cal_seqs((qubit, ), 1)
return compile_to_hardware(seqs, 'SingleShot/SingleShot')
def init_plots(self):
self.re_plot = ManualPlotter("Fidelity - Real",
x_label='Bins',
y_label='Real Quadrature')
self.im_plot = ManualPlotter("Fidelity - Imag",
x_label='Bins',
y_label='Imag Quadrature')
self.re_plot.add_trace("Excited",
matplotlib_kwargs={
'color': 'r',
'linestyle': '-',
'linewidth': 2
})
self.re_plot.add_trace("Excited Gaussian Fit",
matplotlib_kwargs={
'color': 'r',
'linestyle': '--',
'linewidth': 2
})
self.re_plot.add_trace("Ground",
matplotlib_kwargs={
'color': 'b',
'linestyle': '-',
'linewidth': 2
})
self.re_plot.add_trace("Ground Gaussian Fit",
matplotlib_kwargs={
'color': 'b',
'linestyle': '--',
'linewidth': 2
})
self.im_plot.add_trace("Excited",
matplotlib_kwargs={
'color': 'r',
'linestyle': '-',
'linewidth': 2
})
self.im_plot.add_trace("Excited Gaussian Fit",
matplotlib_kwargs={
'color': 'r',
'linestyle': '--',
'linewidth': 2
})
self.im_plot.add_trace("Ground",
matplotlib_kwargs={
'color': 'b',
'linestyle': '-',
'linewidth': 2
})
self.im_plot.add_trace("Ground Gaussian Fit",
matplotlib_kwargs={
'color': 'b',
'linestyle': '--',
'linewidth': 2
})
self.add_manual_plotter(self.re_plot)
self.add_manual_plotter(self.im_plot)
def _update_histogram_plots(self):
self.re_plot["Ground"] = (self.pdf_data[-1]["I Bins"],
self.pdf_data[-1]["Ground I PDF"])
self.re_plot["Ground Gaussian Fit"] = (
self.pdf_data[-1]["I Bins"],
self.pdf_data[-1]["Ground I Gaussian PDF"])
self.re_plot["Excited"] = (self.pdf_data[-1]["I Bins"],
self.pdf_data[-1]["Excited I PDF"])
self.re_plot["Excited Gaussian Fit"] = (
self.pdf_data[-1]["I Bins"],
self.pdf_data[-1]["Excited I Gaussian PDF"])
self.im_plot["Ground"] = (self.pdf_data[-1]["Q Bins"],
self.pdf_data[-1]["Ground Q PDF"])
self.im_plot["Ground Gaussian Fit"] = (
self.pdf_data[-1]["Q Bins"],
self.pdf_data[-1]["Ground Q Gaussian PDF"])
self.im_plot["Excited"] = (self.pdf_data[-1]["Q Bins"],
self.pdf_data[-1]["Excited Q PDF"])
self.im_plot["Excited Gaussian Fit"] = (
self.pdf_data[-1]["Q Bins"],
self.pdf_data[-1]["Excited Q Gaussian PDF"])
def run_sweeps(self):
if not self.sweeper.axes:
self.init_plots()
self.start_manual_plotters()
else:
for f in self.filters:
if isinstance(f, SingleShotMeasurement):
f.save_kernel.value = False
super(SingleShotFidelityExperiment, self).run_sweeps()
self.get_results()
if not self.sweeper.axes:
self._update_histogram_plots()
self.stop_manual_plotters()
if self.set_threshold:
self.stream_selectors[0].threshold = self.get_threshold()[0]
if self.sample:
c = bbndb.calibration.Calibration(value=self.get_fidelity()[0],
sample=self.sample,
name="Readout fid.",
category="Readout")
c.date = datetime.datetime.now()
bbndb.get_cl_session().add(c)
bbndb.get_cl_session().commit()
elif self.optimize:
fidelities = [f['Max I Fidelity'] for f in self.pdf_data]
opt_ind = np.argmax(fidelities)
for k, axis in enumerate(self.sweeper.axes):
set_pair = axis.parameter.set_pair
opt_value = axis.points[opt_ind]
if set_pair[1] == 'amplitude' or set_pair[1] == "offset":
# special case for APS chans
param = [
c for c in self.chan_db.channels
if c.label == set_pair[0]
][0]
attr = 'amp_factor' if set_pair[
1] == 'amplitude' else 'offset'
setattr(param, f'I_channel_{attr}', opt_value)
setattr(param, f'Q_channel_{attr}', opt_value)
else:
param = [
c for c in self.chan_db.all_instruments()
if c.label == set_pair[0]
][0]
setattr(param, set_pair[1], opt_value)
logger.info(
f'Set {set_pair[0]} {set_pair[1]} to optimum value {opt_value}'
)
if self.set_threshold:
self.stream_selectors[0].threshold = self.get_threshold(
)[opt_ind]
logger.info(
f'Set threshold to {self.stream_selectors[0].threshold}')
def find_single_shot_filter(self):
"""Make sure there is one single shot measurement filter in the pipeline."""
ssf = [x for x in self.filters if type(x) is SingleShotMeasurement]
if len(ssf) > 1:
raise NotImplementedError(
"Single shot fidelity for more than one qubit is not yet implemented."
)
elif len(ssf) == 0:
raise NameError(
"There do not appear to be any single-shot measurements in your filter pipeline. Please add one!"
)
return ssf
def get_fidelity(self):
if not self.pdf_data:
raise Exception(
"Could not find single shot PDF data in results. Did you run the sweeps?"
)
return [p["Max I Fidelity"] for p in self.pdf_data]
def get_threshold(self):
if not self.pdf_data:
raise Exception(
"Could not find single shot PDF data in results. Did you run the sweeps?"
)
return [p["I Threshold"] for p in self.pdf_data]
def get_results(self):
"""Get the PDF and fidelity numbers from the filters. Returns a dictionary of PDF data with the
filter names as keys."""
if len(self.pdf_data) == 0:
ssf = self.find_single_shot_filter()
while True:
try:
self.pdf_data.append(ssf[0].pdf_data_queue.get(False))
except queue.Empty as e:
break
if len(self.pdf_data) == 0:
raise Exception(
"Could not find single shot PDF data in results. Did you run the sweeps?"
)