See also

A Jupyter notebook version of this tutorial can be downloaded here.

Single transmon qubit spectroscopy

Here we will carry out qubit spectroscopy on a single transmon in order to find the \(|0\rangle \rightarrow |1\rangle\) drive frequency.

import numpy as np
from qcodes.parameters import ManualParameter

from quantify_scheduler.gettables import ScheduleGettable
from quantify_scheduler.operations.gate_library import Measure, Reset, X
from quantify_scheduler.schedules.schedule import Schedule

import json

import rich  # noqa:F401

import quantify_core.data.handling as dh
from quantify_scheduler.device_under_test.quantum_device import QuantumDevice

from utils import initialize_hardware, run  # noqa:F401

Setup

In this section we configure the hardware configuration which specifies the connectivity of our system.

The experiments of this tutorial are meant to be executed with a Qblox Cluster controlling a transmon system. The experiments can also be executed using a dummy Qblox device that is created via an instance of the Cluster class, and is initialized with a dummy configuration. When using a dummy device, the analysis will not work because the experiments will return np.nan values.

Configuration file

This is a template hardware configuration file for a 2-qubit system with a flux-control line which can be used to tune the qubit frequency. We will only work with qubit 0.

The hardware connectivity is as follows, by cluster slot: - QCM (Slot 2) - \(\text{O}^{1}\): Flux line for q0. - \(\text{O}^{2}\): Flux line for q1. - QCM-RF (Slot 6) - \(\text{O}^{1}\): Drive line for q0 using fixed 80 MHz IF. - \(\text{O}^{2}\): Drive line for q1 using fixed 80 MHz IF. - QRM-RF (Slot 8) - \(\text{O}^{1}\) and \(\text{I}^{1}\): Shared readout line for q0/q1 using a fixed LO set at 7.5 GHz.

Note that in the hardware configuration below the mixers are uncorrected, but for high fidelity experiments this should also be done for all the modules.

with open("configs/tuning_transmon_coupled_pair_hardware_config.json") as hw_cfg_json_file:
    hardware_cfg = json.load(hw_cfg_json_file)

# Enter your own dataset directory here!
dh.set_datadir(dh.default_datadir())

Data will be saved in:
/root/quantify-data

Quantum device settings

Here we initialize our QuantumDevice and our qubit parameters, checkout this tutorial for further details.

In short, a QuantumDevice contains device elements where we save our found parameters. Here we are loading a template for 2 qubits, but we will only use qubit 0.

quantum_device = QuantumDevice.from_json_file("devices/transmon_device_2q.json")
qubit = quantum_device.get_element("q0")
quantum_device.hardware_config(hardware_cfg)
meas_ctrl, _, cluster = initialize_hardware(quantum_device, ip=None)

/usr/local/lib/python3.9/site-packages/quantify_scheduler/backends/types/qblox.py:1220: ValidationWarning: Setting `auto_lo_cal=on_lo_interm_freq_change` will overwrite settings `dc_offset_i=0.0` and `dc_offset_q=0.0`. To suppress this warning, do not set either `dc_offset_i` or `dc_offset_q` for this port-clock.
  warnings.warn(
/usr/local/lib/python3.9/site-packages/quantify_scheduler/backends/types/qblox.py:1235: ValidationWarning: Setting `auto_sideband_cal=on_interm_freq_change` will overwrite settings `amp_ratio=1.0` and `phase_error=0.0`. To suppress this warning, do not set either `amp_ratio` or `phase_error` for this port-clock.
  warnings.warn(

Qubit spectroscopy

def two_tone_spec_sched_nco(
    qubit,  # noqa: ANN001
    spec_pulse_frequencies: np.array,
    repetitions: int = 1,
) -> Schedule:
    """
    Generate a batched schedule for performing fast two-tone spectroscopy.

    Using the X gate to perform the frequency sweep on the qubit.

    Parameters
    ----------
    qubit
        qubit that should be used.
    spec_pulse_frequencies
        Sample frequencies for the spectroscopy pulse in Hertz.
    repetitions
        The amount of times the Schedule will be repeated.

    """
    sched = Schedule("two-tone", repetitions)

    for acq_idx, spec_pulse_freq in enumerate(spec_pulse_frequencies):
        sched.add(Reset(qubit.name))
        sched.add(X(qubit.name, freq=spec_pulse_freq))
        sched.add(Measure(qubit.name, acq_index=acq_idx), rel_time=200e-9)
    return sched

freqs = ManualParameter(name="freq", unit="Hz", label="Frequency")
freqs.batched = True

qubit_spec_sched_kwargs = dict(
    qubit=qubit,
    spec_pulse_frequencies=freqs,
)

gettable = ScheduleGettable(
    quantum_device,
    schedule_function=two_tone_spec_sched_nco,
    schedule_kwargs=qubit_spec_sched_kwargs,
    real_imag=False,
    batched=True,
)

meas_ctrl.gettables(gettable)

quantum_device.cfg_sched_repetitions(300)
center = 6.1e9
frequency_setpoints = np.linspace(center - 20e6, center + 20e6, 300)
meas_ctrl.settables(freqs)
meas_ctrl.setpoints(frequency_setpoints)

qs_ds = meas_ctrl.run("Two-tone")
qs_ds

Starting batched measurement...
Iterative settable(s) [outer loop(s)]:
         --- (None) ---
Batched settable(s):
         freq
Batch size limit: 300

<xarray.Dataset> Size: 7kB
Dimensions:  (dim_0: 300)
Coordinates:
    x0       (dim_0) float64 2kB 6.08e+09 6.08e+09 ... 6.12e+09 6.12e+09
Dimensions without coordinates: dim_0
Data variables:
    y0       (dim_0) float64 2kB nan nan nan nan nan nan ... nan nan nan nan nan
    y1       (dim_0) float64 2kB nan nan nan nan nan nan ... nan nan nan nan nan
Attributes:
    tuid:                             20241017-131132-831-17681b
    name:                             Two-tone
    grid_2d:                          False
    grid_2d_uniformly_spaced:         False
    1d_2_settables_uniformly_spaced:  False

xarray.Dataset

• Dimensions:
  • dim_0: 300
• Coordinates: (1)
  • x0
    (dim_0)
    float64
    6.08e+09 6.08e+09 ... 6.12e+09

    name :

    freq

    long_name :

    Frequency

    units :

    Hz

    batched :

    True

    array([6.08000000e+09, 6.08013378e+09, 6.08026756e+09, 6.08040134e+09,
           6.08053512e+09, 6.08066890e+09, 6.08080268e+09, 6.08093645e+09,
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           6.08909699e+09, 6.08923077e+09, 6.08936455e+09, 6.08949833e+09,
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           6.09016722e+09, 6.09030100e+09, 6.09043478e+09, 6.09056856e+09,
    ...
           6.10943144e+09, 6.10956522e+09, 6.10969900e+09, 6.10983278e+09,
           6.10996656e+09, 6.11010033e+09, 6.11023411e+09, 6.11036789e+09,
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           6.11103679e+09, 6.11117057e+09, 6.11130435e+09, 6.11143813e+09,
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           6.11317726e+09, 6.11331104e+09, 6.11344482e+09, 6.11357860e+09,
           6.11371237e+09, 6.11384615e+09, 6.11397993e+09, 6.11411371e+09,
           6.11424749e+09, 6.11438127e+09, 6.11451505e+09, 6.11464883e+09,
           6.11478261e+09, 6.11491639e+09, 6.11505017e+09, 6.11518395e+09,
           6.11531773e+09, 6.11545151e+09, 6.11558528e+09, 6.11571906e+09,
           6.11585284e+09, 6.11598662e+09, 6.11612040e+09, 6.11625418e+09,
           6.11638796e+09, 6.11652174e+09, 6.11665552e+09, 6.11678930e+09,
           6.11692308e+09, 6.11705686e+09, 6.11719064e+09, 6.11732441e+09,
           6.11745819e+09, 6.11759197e+09, 6.11772575e+09, 6.11785953e+09,
           6.11799331e+09, 6.11812709e+09, 6.11826087e+09, 6.11839465e+09,
           6.11852843e+09, 6.11866221e+09, 6.11879599e+09, 6.11892977e+09,
           6.11906355e+09, 6.11919732e+09, 6.11933110e+09, 6.11946488e+09,
           6.11959866e+09, 6.11973244e+09, 6.11986622e+09, 6.12000000e+09])

• Data variables: (2)
  • y0
    (dim_0)
    float64
    nan nan nan nan ... nan nan nan nan

    name :

    magn

    long_name :

    Magnitude0

    units :

    V

    batched :

    True

    batch_size :

    1024

    array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
           nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
           nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
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           nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
           nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
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           nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
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           nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
           nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
           nan])

  • y1
    (dim_0)
    float64
    nan nan nan nan ... nan nan nan nan

    name :

    phase

    long_name :

    Phase0

    units :

    deg

    batched :

    True

    batch_size :

    1024

    array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
           nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
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           nan])

• Indexes: (0)
• Attributes: (5)

  tuid :

  20241017-131132-831-17681b

  name :

  Two-tone

  grid_2d :

  False

  grid_2d_uniformly_spaced :

  False

  1d_2_settables_uniformly_spaced :

  False

qubit.clock_freqs.f01(6.1e9)

rich.print(quantum_device.hardware_config())

{
    'config_type': 'quantify_scheduler.backends.qblox_backend.QbloxHardwareCompilationConfig',
    'hardware_description': {
        'cluster0': {
            'instrument_type': 'Cluster',
            'modules': {
                '6': {'instrument_type': 'QCM_RF'},
                '2': {'instrument_type': 'QCM'},
                '8': {'instrument_type': 'QRM_RF'}
            },
            'sequence_to_file': False,
            'ref': 'internal'
        }
    },
    'hardware_options': {
        'output_att': {'q0:mw-q0.01': 10, 'q1:mw-q1.01': 10, 'q0:res-q0.ro': 60, 'q1:res-q1.ro': 60},
        'mixer_corrections': {
            'q0:mw-q0.01': {
                'auto_lo_cal': 'on_lo_interm_freq_change',
                'auto_sideband_cal': 'on_interm_freq_change',
                'dc_offset_i': None,
                'dc_offset_q': None,
                'amp_ratio': 1.0,
                'phase_error': 0.0
            },
            'q1:mw-q1.01': {
                'auto_lo_cal': 'on_lo_interm_freq_change',
                'auto_sideband_cal': 'on_interm_freq_change',
                'dc_offset_i': None,
                'dc_offset_q': None,
                'amp_ratio': 1.0,
                'phase_error': 0.0
            },
            'q0:res-q0.ro': {
                'auto_lo_cal': 'on_lo_interm_freq_change',
                'auto_sideband_cal': 'on_interm_freq_change',
                'dc_offset_i': None,
                'dc_offset_q': None,
                'amp_ratio': 1.0,
                'phase_error': 0.0
            },
            'q1:res-q1.ro': {
                'auto_lo_cal': 'on_lo_interm_freq_change',
                'auto_sideband_cal': 'on_interm_freq_change',
                'dc_offset_i': None,
                'dc_offset_q': None,
                'amp_ratio': 1.0,
                'phase_error': 0.0
            }
        },
        'modulation_frequencies': {
            'q0:mw-q0.01': {'interm_freq': 80000000.0},
            'q1:mw-q1.01': {'interm_freq': 80000000.0},
            'q0:res-q0.ro': {'lo_freq': 7500000000.0},
            'q1:res-q1.ro': {'lo_freq': 7500000000.0}
        }
    },
    'connectivity': {
        'graph': [
            ['cluster0.module6.complex_output_0', 'q0:mw'],
            ['cluster0.module6.complex_output_1', 'q1:mw'],
            ['cluster0.module2.real_output_0', 'q0:fl'],
            ['cluster0.module2.real_output_1', 'q1:fl'],
            ['cluster0.module8.complex_output_0', 'q0:res'],
            ['cluster0.module8.complex_output_0', 'q1:res']
        ]
    }
}

quantum_device.to_json_file("devices/")

'devices/device_2q_2024-10-17_13-11-33_UTC.json'