def ramsey_seq_multiple_detunings(times,
pulse_pars,
RO_pars,
artificial_detunings=None,
cal_points=True,
upload=True,
return_seq=False):
'''
Ramsey sequence for a single qubit using the tektronix.
SSB_Drag pulse is used for driving, simple modualtion used for RO
!!! Each value in the times array must be repeated len(artificial_detunings)
times!!!
Input pars:
times: array of times between (start of) pulses (s)
pulse_pars: dict containing the pulse parameters
RO_pars: dict containing the RO parameters
artificial_detunings: list of artificial_detunings (Hz) implemented
using phase
cal_points: whether to use calibration points or not
'''
seq_name = 'Ramsey_sequence_multiple_detunings'
seq = sequence.Sequence(seq_name)
ps.Pulsar.get_instance().update_channel_settings()
seg_list = []
# First extract values from input, later overwrite when generating
# waveforms
pulses = get_pulse_dict_from_pars(pulse_pars)
pulse_pars_x2 = deepcopy(pulses['X90'])
pulse_pars_x2['ref_point'] = 'start'
for i, tau in enumerate(times):
pulse_pars_x2['pulse_delay'] = tau
art_det = artificial_detunings[i % len(artificial_detunings)]
if art_det is not None:
Dphase = ((tau - times[0]) * art_det * 360) % 360
pulse_pars_x2['phase'] = Dphase
if cal_points and (i == (len(times) - 4) or i == (len(times) - 3)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['I'], RO_pars])
elif cal_points and (i == (len(times) - 2) or i == (len(times) - 1)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['X180'], RO_pars])
else:
seg = segment.Segment('segment_{}'.format(i),
[pulses['X90'], pulse_pars_x2, RO_pars])
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name
def ramsey_seq_VZ(times,
pulse_pars,
RO_pars,
artificial_detuning=None,
cal_points=True,
upload=True,
return_seq=False):
'''
Ramsey sequence for a single qubit using the tektronix.
SSB_Drag pulse is used for driving, simple modualtion used for RO
Input pars:
times: array of times between (start of) pulses (s)
pulse_pars: dict containing the pulse parameters
RO_pars: dict containing the RO parameters
artificial_detuning: artificial_detuning (Hz) implemented using phase
cal_points: whether to use calibration points or not
'''
if np.any(times > 1e-3):
logging.warning('The values in the times array might be too large.'
'The units should be seconds.')
seq_name = 'Ramsey_sequence'
seq = sequence.Sequence(seq_name)
seg_list = []
# First extract values from input, later overwrite when generating
# waveforms
pulses = get_pulse_dict_from_pars(pulse_pars)
pulse_pars_x2 = deepcopy(pulses['X90'])
pulse_pars_x2['ref_point'] = 'start'
for i, tau in enumerate(times):
pulse_pars_x2['pulse_delay'] = tau
if artificial_detuning is not None:
Dphase = ((tau - times[0]) * artificial_detuning * 360) % 360
else:
Dphase = ((tau - times[0]) * 1e6 * 360) % 360
Z_gate = Z(Dphase, pulse_pars)
if cal_points and (i == (len(times) - 4) or i == (len(times) - 3)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['I'], RO_pars])
elif cal_points and (i == (len(times) - 2) or i == (len(times) - 1)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['X180'], RO_pars])
else:
pulse_list = [pulses['X90'], Z_gate, pulse_pars_x2, RO_pars]
seg = segment.Segment('segment_{}'.format(i), pulse_list)
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name
def echo_seq(times,
pulse_pars,
RO_pars,
artificial_detuning=None,
cal_points=True,
upload=True,
return_seq=False):
'''
Echo sequence for a single qubit using the tektronix.
Input pars:
times: array of times between (start of) pulses (s)
artificial_detuning: artificial_detuning (Hz) implemented using phase
pulse_pars: dict containing the pulse parameters
RO_pars: dict containing the RO parameters
cal_points: whether to use calibration points or not
'''
seq_name = 'Echo_sequence'
seq = sequence.Sequence(seq_name)
seg_list = []
pulses = get_pulse_dict_from_pars(pulse_pars)
center_X180 = deepcopy(pulses['X180'])
final_X90 = deepcopy(pulses['X90'])
center_X180['ref_point'] = 'start'
final_X90['ref_point'] = 'start'
for i, tau in enumerate(times):
center_X180['pulse_delay'] = tau / 2
final_X90['pulse_delay'] = tau / 2
if artificial_detuning is not None:
final_X90['phase'] = (tau - times[0]) * artificial_detuning * 360
if cal_points and (i == (len(times) - 4) or i == (len(times) - 3)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['I'], RO_pars])
elif cal_points and (i == (len(times) - 2) or i == (len(times) - 1)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['X180'], RO_pars])
else:
seg = segment.Segment(
'segment_{}'.format(i),
[pulses['X90'], center_X180, final_X90, RO_pars])
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name
def interleaved_pulse_list_equatorial_seg(qubit_names,
operation_dict,
interleaved_pulse_list,
phase,
pihalf_spacing=None,
prep_params=None,
segment_name='equatorial_segment'):
prep_params = {} if prep_params is None else prep_params
pulse_list = []
for notfirst, qbn in enumerate(qubit_names):
pulse_list.append(deepcopy(operation_dict['X90 ' + qbn]))
pulse_list[-1]['ref_point'] = 'start'
if not notfirst:
pulse_list[-1]['name'] = 'refpulse'
pulse_list += interleaved_pulse_list
for notfirst, qbn in enumerate(qubit_names):
pulse_list.append(deepcopy(operation_dict['X90 ' + qbn]))
pulse_list[-1]['phase'] = phase
if notfirst:
pulse_list[-1]['ref_point'] = 'start'
elif pihalf_spacing is not None:
pulse_list[-1]['ref_pulse'] = 'refpulse'
pulse_list[-1]['ref_point'] = 'start'
pulse_list[-1]['pulse_delay'] = pihalf_spacing
pulse_list += generate_mux_ro_pulse_list(qubit_names, operation_dict)
pulse_list = add_preparation_pulses(pulse_list, operation_dict,
qubit_names, **prep_params)
return segment.Segment(segment_name, pulse_list)
def n_qubit_ref_seq(qubit_names,
operation_dict,
ref_desc,
upload=True,
return_seq=False,
preselection=False,
ro_spacing=1e-6):
"""
Calibration points for arbitrary combinations
Arguments:
qubits: List of calibrated qubits for obtaining the pulse
dictionaries.
ref_desc: Description of the calibration sequence. Dictionary
name of the state as key, and list of pulses names as values.
"""
# create the elements
seq_name = 'Calibration'
seq = sequence.Sequence(seq_name)
seg_list = []
# calibration elements
# calibration_sequences = []
# for pulses in ref_desc:
# calibration_sequences.append(
# [pulse+' '+qb for qb, pulse in zip(qubit_names, pulses)])
calibration_sequences = []
for pulses in ref_desc:
calibration_sequence_new = []
for i, pulse in enumerate(pulses):
if i == 0:
qb = ' ' + qubit_names[i]
else:
qb = 's ' + qubit_names[i]
calibration_sequence_new.append(pulse + qb)
calibration_sequences.append(calibration_sequence_new)
for i, calibration_sequence in enumerate(calibration_sequences):
pulse_list = []
pulse_list.extend(
[operation_dict[pulse] for pulse in calibration_sequence])
ro_pulses = generate_mux_ro_pulse_list(qubit_names, operation_dict)
pulse_list.extend(ro_pulses)
if preselection:
ro_pulses_presel = generate_mux_ro_pulse_list(
qubit_names, operation_dict, 'RO_presel', 'start', -ro_spacing)
pulse_list.extend(ro_pulses_presel)
seg = segment.Segment('calibration_{}'.format(i), pulse_list)
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name
def pulse_list_list_seq(pulse_list_list,
name='pulse_list_list_sequence',
upload=True,
fast_mode=False):
seq = sequence.Sequence(name)
for i, pulse_list in enumerate(pulse_list_list):
seq.add(
segment.Segment('segment_{}'.format(i),
pulse_list,
fast_mode=fast_mode))
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
return seq
def n_qubit_tomo_seq(qubit_names,
operation_dict,
prep_sequence=None,
prep_name=None,
rots_basis=tomo.DEFAULT_BASIS_ROTS,
upload=True,
return_seq=False,
preselection=False,
ro_spacing=1e-6):
"""
"""
# create the sequence
if prep_name is None:
seq_name = 'N-qubit tomography'
else:
seq_name = prep_name + ' tomography'
seq = sequence.Sequence(seq_name)
seg_list = []
if prep_sequence is None:
prep_sequence = ['Y90 ' + qubit_names[0]]
# tomography elements
tomography_sequences = get_tomography_pulses(*qubit_names,
basis_pulses=rots_basis)
for i, tomography_sequence in enumerate(tomography_sequences):
pulse_list = [operation_dict[pulse] for pulse in prep_sequence]
# tomography_sequence.append('RO mux')
# if preselection:
# tomography_sequence.append('RO mux_presel')
# tomography_sequence.append('RO presel_dummy')
pulse_list.extend(
[operation_dict[pulse] for pulse in tomography_sequence])
ro_pulses = generate_mux_ro_pulse_list(qubit_names, operation_dict)
pulse_list.extend(ro_pulses)
if preselection:
ro_pulses_presel = generate_mux_ro_pulse_list(
qubit_names, operation_dict, 'RO_presel', 'start', -ro_spacing)
pulse_list.extend(ro_pulses_presel)
seg = segment.Segment('tomography_{}'.format(i), pulse_list)
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name
def over_under_rotation_seq(qb_name,
nr_pi_pulses_array,
operation_dict,
pi_pulse_amp=None,
cal_points=True,
upload=True):
seq_name = 'Over-under rotation sequence'
seq = sequence.Sequence(seq_name)
seg_list = []
X90 = deepcopy(operation_dict['X90 ' + qb_name])
X180 = deepcopy(operation_dict['X180 ' + qb_name])
if pi_pulse_amp is not None:
X90['amplitude'] = pi_pulse_amp / 2
X180['amplitude'] = pi_pulse_amp
for i, N in enumerate(nr_pi_pulses_array):
if cal_points and (i == (len(nr_pi_pulses_array) - 4)
or i == (len(nr_pi_pulses_array) - 3)):
seg = segment.Segment('segment_{}'.format(i), [
operation_dict['I ' + qb_name], operation_dict['RO ' + qb_name]
])
elif cal_points and (i == (len(nr_pi_pulses_array) - 2)
or i == (len(nr_pi_pulses_array) - 1)):
seg = segment.Segment('segment_{}'.format(i), [
operation_dict['X180 ' + qb_name],
operation_dict['RO ' + qb_name]
])
else:
pulse_list = [X90]
pulse_list += N * [X180]
pulse_list += [operation_dict['RO ' + qb_name]]
seg = segment.Segment('segment_{}'.format(i), pulse_list)
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
return
def single_state_active_reset(operation_dict,
qb_name,
state='e',
upload=True,
prep_params={}):
'''
OffOn sequence for a single qubit using the tektronix.
SSB_Drag pulse is used for driving, simple modualtion used for RO
Input pars:
pulse_pars: dict containing the pulse parameters
RO_pars: dict containing the RO parameters
pulse_pars_2nd: dict containing the pulse parameters of ef transition.
Required if state is 'f'.
Initialize: adds an exta measurement before state preparation
to allow initialization by post-selection
Post-measurement delay: should be sufficiently long to avoid
photon-induced gate errors when post-selecting.
state: specifies for which state a pulse should be
generated (g,e,f)
preselection: adds an extra readout pulse before other pulses.
'''
seq_name = 'single_state_sequence'
seq = sequence.Sequence(seq_name)
# Create dicts with the parameters for all the pulses
state_ops = dict(g=["I", "RO"],
e=["X180", "RO"],
f=["X180", "X180_ef", "RO"])
pulses = [
deepcopy(operation_dict[op])
for op in add_suffix(state_ops[state], " " + qb_name)
]
#add preparation pulses
pulses_with_prep = \
add_preparation_pulses(pulses, operation_dict, [qb_name], **prep_params)
seg = segment.Segment('segment_{}_level'.format(state), pulses_with_prep)
seq.add(seg)
# reuse sequencer memory by repeating readout pattern
seq.repeat_ro(f"RO {qb_name}", operation_dict)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
return seq, np.arange(seq.n_acq_elements())
def readout_pulse_scope_seq(delays,
pulse_pars,
RO_pars,
RO_separation,
cal_points=((-4, -3), (-2, -1)),
comm_freq=225e6,
upload=True,
return_seq=False,
prep_pulses=None,
verbose=False):
"""
Prepares the AWGs for a readout pulse shape and timing measurement.
The sequence consists of two readout pulses where the drive pulse start
time is swept through the first readout pulse. Because the photons in the
readout resonator induce an ac-Stark shift of the qubit frequency, we can
determine the readout pulse shape by sweeping the drive frequency in an
outer loop to determine the qubit frequency.
Important: This sequence includes two readouts per segment. For this reason
the calibration points are also duplicated.
Args:
delays: A list of delays between the start of the first readout pulse
and the end of the drive pulse.
pulse_pars: Pulse dictionary for the drive pulse.
RO_pars: Pulse dictionary for the readout pulse.
RO_separation: Separation between the starts of the two readout pulses.
If the comm_freq parameter is not None, the used value
is increased to satisfy the commensurability constraint.
cal_points: True for default calibration points, False for no
calibration points or a list of two lists, containing
the indices of the calibration segments for the ground
and excited state.
comm_freq: The readout pulse separation will be a multiple of
1/comm_freq
Returns:
The sequence object and the element list if return_seq is True. Else
return the sequence name.
"""
if cal_points:
cal_points = ((-4, -3), (-2, -1))
elif not cal_points or cal_points is None:
cal_points = ((), ())
if prep_pulses is None:
prep_pulses = []
if comm_freq:
RO_separation -= RO_separation % (-1 / comm_freq)
seq_name = 'readout_pulse_scope_sequence'
seq = sequence.Sequence(seq_name)
seg_list = []
pulses = get_pulse_dict_from_pars(pulse_pars)
min_delay = min(delays)
readout_x1 = deepcopy(RO_pars)
readout_x1['ref_point'] = 'end'
readout_x2 = deepcopy(RO_pars)
readout_x2['pulse_delay'] = RO_separation
readout_x2['ref_point'] = 'start'
probe_pulse = deepcopy(pulses['X180'])
prep_pulses = [deepcopy(pulses[pulse_name]) for pulse_name in prep_pulses]
for pulse in prep_pulses:
pulse['pulse_delay'] = -2 * np.abs(min_delay)
for i, tau in enumerate(delays):
if i in cal_points[0] or i - len(delays) in cal_points[0]:
seg = segment.Segment('segment_{}'.format(2 * i),
[pulses['I'], RO_pars])
seg_list.append(seg)
seq.add(seg)
seg = segment.Segment('segment_{}'.format(2 * i + 1),
[pulses['I'], RO_pars])
seg_list.append(seg)
seq.add(seg)
elif i in cal_points[1] or i - len(delays) in cal_points[1]:
seg = segment.Segment('segment_{}'.format(2 * i),
[pulses['X180'], RO_pars])
seg_list.append(seg)
seq.add(seg)
seg = segment.Segment('segment_{}'.format(2 * i + 1),
[pulses['X180'], RO_pars])
seg_list.append(seg)
seq.add(seg)
else:
probe_pulse['pulse_delay'] = tau - min_delay
readout_x1['pulse_delay'] = -tau
seg = segment.Segment(
'segment_{}'.format(2 * i),
prep_pulses + [probe_pulse, readout_x1, readout_x2])
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name
def create_segments(self,
operation_dict,
pulse_modifs=None,
segment_prefix='calibration_',
**prep_params):
segments = []
if pulse_modifs is None:
pulse_modifs = dict()
if self.pulse_modifs is not None:
pm = deepcopy(self.pulse_modifs)
pm.update(pulse_modifs)
pulse_modifs = pm
for i, seg_states in enumerate(self.states):
pulse_list = []
for j, qbn in enumerate(self.qb_names):
unique, counts = np.unique(self.get_states(qbn)[qbn],
return_counts=True)
cal_pt_idx = i % np.squeeze(
counts[np.argwhere(unique == seg_states[j])])
for k, pulse_name in enumerate(
self.pulse_label_map[seg_states[j]]):
pulse = deepcopy(operation_dict[pulse_name + qbn])
pulse['name'] = f"{seg_states[j]}_{pulse_name + qbn}_" \
f"{cal_pt_idx}"
if k == 0:
pulse['ref_pulse'] = 'segment_start'
if len(pulse_modifs) > 0:
# The pulse(s) to which the pulse_modifs refer might
# not be present in all calibration segments. We
# thus disable the pulse_not_found_warning.
pulse = sweep_pulse_params(
[pulse],
pulse_modifs,
pulse_not_found_warning=False)[0][0]
# reset the name as sweep_pulse_params deletes it
pulse['name'] = f"{seg_states[j]}_{pulse_name + qbn}_" \
f"{cal_pt_idx}"
pulse_list.append(pulse)
state_prep_pulse_names = [p['name'] for p in pulse_list]
pulse_list = add_preparation_pulses(pulse_list, operation_dict,
[qbn for qbn in self.qb_names],
**prep_params)
ro_pulses = generate_mux_ro_pulse_list(self.qb_names,
operation_dict)
# reference all readout pulses to all pulses of the pulse list, to ensure
# readout happens after the last pulse (e.g. if doing "f" on some qubits
# and "e" on others). In the future we could use the circuitBuilder
# and Block here
[
rp.update({
'ref_pulse': state_prep_pulse_names,
"ref_point": 'end'
}) for rp in ro_pulses
]
pulse_list += ro_pulses
seg = segment.Segment(segment_prefix + f'{i}', pulse_list)
segments.append(seg)
return segments
def ramsey_seq_cont_drive(times,
pulse_pars,
RO_pars,
artificial_detuning=None,
cal_points=True,
upload=True,
return_seq=False,
**kw):
'''
Ramsey sequence for a single qubit using the tektronix.
SSB_Drag pulse is used for driving, simple modualtion used for RO
Input pars:
times: array of times between (start of) pulses (s)
pulse_pars: dict containing the pulse parameters
RO_pars: dict containing the RO parameters
artificial_detuning: artificial_detuning (Hz) implemented using phase
cal_points: whether to use calibration points or not
'''
if np.any(times > 1e-3):
logging.warning('The values in the times array might be too large.'
'The units should be seconds.')
seq_name = 'Ramsey_sequence'
seq = sequence.Sequence(seq_name)
seg_list = []
# First extract values from input, later overwrite when generating
# waveforms
pulses = get_pulse_dict_from_pars(pulse_pars)
pulse_pars_x2 = deepcopy(pulses['X90'])
DRAG_length = pulse_pars['nr_sigma'] * pulse_pars['sigma']
cont_drive_ampl = 0.1 * pulse_pars['amplitude']
X180_pulse = deepcopy(pulses['X180'])
cos_pulse = {
'pulse_type': 'CosPulse_gauss_rise',
'channel': X180_pulse['I_channel'],
'frequency': X180_pulse['mod_frequency'],
'length': 0,
'phase': X180_pulse['phi_skew'],
'amplitude': cont_drive_ampl * X180_pulse['alpha'],
'pulse_delay': 0,
'ref_point': 'end'
}
sin_pulse = {
'pulse_type': 'CosPulse_gauss_rise',
'channel': X180_pulse['Q_channel'],
'frequency': X180_pulse['mod_frequency'],
'length': 0,
'phase': 90,
'amplitude': cont_drive_ampl * X180_pulse['alpha'],
'pulse_delay': 0,
'ref_point': 'simultaneous'
}
for i, tau in enumerate(times):
if artificial_detuning is not None:
Dphase = ((tau - times[0]) * artificial_detuning * 360) % 360
pulse_pars_x2['phase'] = Dphase
if cal_points and (i == (len(times) - 4) or i == (len(times) - 3)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['I'], RO_pars])
elif cal_points and (i == (len(times) - 2) or i == (len(times) - 1)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['X180'], RO_pars])
else:
X90_separation = tau - DRAG_length
if X90_separation > 0:
pulse_pars_x2['ref_point'] = 'end'
cos_pls1 = deepcopy(cos_pulse)
sin_pls1 = deepcopy(sin_pulse)
cos_pls1['length'] = X90_separation / 2
sin_pls1['length'] = X90_separation / 2
cos_pls2 = deepcopy(cos_pls1)
sin_pls2 = deepcopy(sin_pls1)
cos_pls2['amplitude'] = -cos_pls1['amplitude']
cos_pls2['pulse_type'] = 'CosPulse_gauss_fall'
sin_pls2['amplitude'] = -sin_pls1['amplitude']
sin_pls2['pulse_type'] = 'CosPulse_gauss_fall'
pulse_dict_list = [
pulses['X90'], cos_pls1, sin_pls1, cos_pls2, sin_pls2,
pulse_pars_x2, RO_pars
]
else:
pulse_pars_x2['ref_point'] = 'start'
pulse_pars_x2['pulse_delay'] = tau
pulse_dict_list = [pulses['X90'], pulse_pars_x2, RO_pars]
seg = segment.Segment('segment_{}'.format(i), pulse_dict_list)
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name
def ramsey_seq_Echo(times,
pulse_pars,
RO_pars,
nr_echo_pulses=4,
artificial_detuning=None,
cal_points=True,
cpmg_scheme=True,
upload=True,
return_seq=False):
'''
Ramsey sequence for a single qubit using the tektronix.
SSB_Drag pulse is used for driving, simple modualtion used for RO
Input pars:
times: array of times between (start of) pulses (s)
pulse_pars: dict containing the pulse parameters
RO_pars: dict containing the RO parameters
artificial_detuning: artificial_detuning (Hz) implemented using phase
cal_points: whether to use calibration points or not
'''
if np.any(times > 1e-3):
logging.warning('The values in the times array might be too large.'
'The units should be seconds.')
seq_name = 'Ramsey_sequence'
seq = sequence.Sequence(seq_name)
seg_list = []
# First extract values from input, later overwrite when generating
# waveforms
pulses = get_pulse_dict_from_pars(pulse_pars)
pulse_pars_x2 = deepcopy(pulses['X90'])
pulse_pars_x2['ref_point'] = 'start'
X180_pulse = deepcopy(pulses['X180'])
Echo_pulses = nr_echo_pulses * [X180_pulse]
DRAG_length = pulse_pars['nr_sigma'] * pulse_pars['sigma']
for i, tau in enumerate(times):
if artificial_detuning is not None:
Dphase = ((tau - times[0]) * artificial_detuning * 360) % 360
pulse_pars_x2['phase'] = Dphase
if cal_points and (i == (len(times) - 4) or i == (len(times) - 3)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['I'], RO_pars])
elif cal_points and (i == (len(times) - 2) or i == (len(times) - 1)):
seg = segment.Segment('segment_{}'.format(i),
[pulses['X180'], RO_pars])
else:
X90_separation = tau - DRAG_length
if cpmg_scheme:
if i == 0:
print('cpmg')
echo_pulse_delay = (X90_separation -
nr_echo_pulses*DRAG_length) / \
nr_echo_pulses
if echo_pulse_delay < 0:
pulse_pars_x2['pulse_delay'] = tau
pulse_dict_list = [pulses['X90'], pulse_pars_x2, RO_pars]
else:
pulse_dict_list = [pulses['X90']]
start_end_delay = echo_pulse_delay / 2
for p_nr, pulse_dict in enumerate(Echo_pulses):
pd = deepcopy(pulse_dict)
pd['ref_point'] = 'end'
pd['pulse_delay'] = \
(start_end_delay if p_nr == 0 else echo_pulse_delay)
pulse_dict_list.append(pd)
pulse_pars_x2['ref_point'] = 'end'
pulse_pars_x2['pulse_delay'] = start_end_delay
pulse_dict_list += [pulse_pars_x2, RO_pars]
else:
if i == 0:
print('UDD')
pulse_positions_func = \
lambda idx, N: np.sin(np.pi*idx/(2*N+2))**2
pulse_delays_func = (lambda idx, N: X90_separation *
(pulse_positions_func(idx, N) -
pulse_positions_func(idx - 1, N)) - (
(0.5
if idx == 1 else 1) * DRAG_length))
if nr_echo_pulses * DRAG_length > X90_separation:
pulse_pars_x2['pulse_delay'] = tau
pulse_dict_list = [pulses['X90'], pulse_pars_x2, RO_pars]
else:
pulse_dict_list = [pulses['X90']]
for p_nr, pulse_dict in enumerate(Echo_pulses):
pd = deepcopy(pulse_dict)
pd['ref_point'] = 'end'
pd['pulse_delay'] = pulse_delays_func(
p_nr + 1, nr_echo_pulses)
pulse_dict_list.append(pd)
pulse_pars_x2['ref_point'] = 'end'
pulse_pars_x2['pulse_delay'] = pulse_delays_func(
1, nr_echo_pulses)
pulse_dict_list += [pulse_pars_x2, RO_pars]
seg = segment.Segment('segment_{}'.format(i), pulse_dict_list)
seg_list.append(seg)
seq.add(seg)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name
def n_qubit_off_on(pulse_pars_list,
RO_pars_list,
return_seq=False,
parallel_pulses=False,
preselection=False,
upload=True,
RO_spacing=2000e-9):
n = len(pulse_pars_list)
seq_name = '{}_qubit_OffOn_sequence'.format(n)
seq = sequence.Sequence(seq_name)
seg_list = []
RO_pars_list_presel = deepcopy(RO_pars_list)
for i, RO_pars in enumerate(RO_pars_list):
RO_pars['name'] = 'RO_{}'.format(i)
RO_pars['element_name'] = 'RO'
if i != 0:
RO_pars['ref_point'] = 'start'
for i, RO_pars_presel in enumerate(RO_pars_list_presel):
RO_pars_presel['ref_pulse'] = RO_pars_list[-1]['name']
RO_pars_presel['ref_point'] = 'start'
RO_pars_presel['element_name'] = 'RO_presel'
RO_pars_presel['pulse_delay'] = -RO_spacing
# Create a dict with the parameters for all the pulses
pulse_dict = dict()
for i, pulse_pars in enumerate(pulse_pars_list):
pars = pulse_pars.copy()
if i == 0 and parallel_pulses:
pars['ref_pulse'] = 'segment_start'
if i != 0 and parallel_pulses:
pars['ref_point'] = 'start'
pulses = add_suffix_to_dict_keys(get_pulse_dict_from_pars(pars),
' {}'.format(i))
pulse_dict.update(pulses)
# Create a list of required pulses
pulse_combinations = []
for pulse_list in itertools.product(*(n * [['I', 'X180']])):
pulse_comb = (n) * ['']
for i, pulse in enumerate(pulse_list):
pulse_comb[i] = pulse + ' {}'.format(i)
pulse_combinations.append(pulse_comb)
for i, pulse_comb in enumerate(pulse_combinations):
pulses = []
for j, p in enumerate(pulse_comb):
pulses += [pulse_dict[p]]
pulses += RO_pars_list
if preselection:
pulses = pulses + RO_pars_list_presel
seg = segment.Segment('segment_{}'.format(i), pulses)
seg_list.append(seg)
seq.add(seg)
repeat_dict = {}
repeat_pattern = ((1.0 + int(preselection)) * len(pulse_combinations), 1)
for i, RO_pars in enumerate(RO_pars_list):
repeat_dict = seq.repeat(RO_pars, None, repeat_pattern)
if upload:
ps.Pulsar.get_instance().program_awgs(seq)
if return_seq:
return seq, seg_list
else:
return seq_name