Coupled qubits characterization#

Note

This notebook uses some python helper functions and example data. You can find both in a zipfile accessible with this link: gitlab.

The experiments of this tutorial are meant to be executed with a Qblox Cluster controlling a flux-tunable 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. However, when using a dummy device, the analysis will not work because the experiments will return np.nan values. In this case, example data is loaded from the "./example_data/" directory.

Hardware setup#

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

Configuration file#

This is a template hardware configuration file for a 2-qubit system (we name the qubits q0 and q1), with dedicated flux-control lines.

The hardware setup is as follows, by cluster slot: 1. QCM-RF - Drive line for q0 using fixed 80 MHz IF. - Drive line for q1 using fixed 80 MHz IF. 2. QCM - Flux line for q0. - Flux line for q1. 6. QRM-RF - 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.

[1]:

hardware_cfg = {
    "backend": "quantify_scheduler.backends.qblox_backend.hardware_compile",
    "cluster0": {
        "sequence_to_file": False,  # Boolean flag which dumps waveforms and program dict to JSON file
        "ref": "internal",  # Use shared clock reference of the cluster
        "instrument_type": "Cluster",
        # ============ DRIVE ============#
        "cluster0_module1": {
            "instrument_type": "QCM_RF",
            "complex_output_0": {
                "output_att": 0,
                "dc_mixer_offset_I": 0.0,
                "dc_mixer_offset_Q": 0.0,
                "portclock_configs": [
                    {
                        "port": "q0:mw",
                        "clock": "q0.01",
                        "interm_freq": 80e6,
                        "mixer_amp_ratio": 1.0,
                        "mixer_phase_error_deg": 0.0,
                    }
                ],
            },
            "complex_output_1": {
                "output_att": 0,
                "dc_mixer_offset_I": 0.0,
                "dc_mixer_offset_Q": 0.0,
                "portclock_configs": [
                    {
                        "port": "q1:mw",
                        "clock": "q1.01",
                        "interm_freq": 80e6,
                        "mixer_amp_ratio": 1.0,
                        "mixer_phase_error_deg": 0.0,
                    }
                ],
            },
        },
        # ============ FLUX ============#
        "cluster0_module2": {
            "instrument_type": "QCM",
            "real_output_0": {"portclock_configs": [{"port": "q0:fl", "clock": "cl0.baseband"}]},
            "real_output_1": {"portclock_configs": [{"port": "q1:fl", "clock": "cl0.baseband"}]},
        },
        # ============ READOUT ============#
        "cluster0_module3": {
            "instrument_type": "QRM_RF",
            "complex_output_0": {
                "output_att": 0,
                "input_att": 0,
                "dc_mixer_offset_I": 0.0,
                "dc_mixer_offset_Q": 0.0,
                "lo_freq": 7.5e9,
                "portclock_configs": [
                    {
                        "port": "q0:res",
                        "clock": "q0.ro",
                        "mixer_amp_ratio": 1.0,
                        "mixer_phase_error_deg": 0.0,
                    },
                    {
                        "port": "q1:res",
                        "clock": "q1.ro",
                        "mixer_amp_ratio": 1.0,
                        "mixer_phase_error_deg": 0.0,
                    },
                ],
            },
        },
    },
}

Scan For Clusters#

We scan for the available clusters on our network using the Plug & Play functionality of the Qblox Instruments package (see Plug & Play for more info).

[2]:

import warnings

import ipywidgets as widgets
from IPython.display import display

from qblox_instruments import PlugAndPlay

warnings.simplefilter("ignore")

# Scan for available devices and display
with PlugAndPlay() as p:
    # Get info of all devices
    device_list = p.list_devices()

names = {dev_id: dev_info["description"]["name"] for dev_id, dev_info in device_list.items()}
names["dummy_cluster"] = "dummy_cluster"
ip_addresses = {dev_id: dev_info["identity"]["ip"] for dev_id, dev_info in device_list.items()}


# Create widget for names and ip addresses
connect = widgets.Dropdown(
    options=[["Dummy-Cluster", "dummy_cluster"]]
    + [(f"{names[dev_id]} @{ip_addresses[dev_id]}", dev_id) for dev_id in device_list],
    description="Select Device",
)
display(connect)

Connect to Cluster#

We now make a connection with the Cluster selected in the dropdown widget. We also define a function to find the modules we’re interested in. We select the readout and control module we want to use.

[3]:

from pathlib import Path

from qcodes import Instrument

from qblox_instruments import Cluster, ClusterType

# Close all existing QCoDeS Instrument instances
Instrument.close_all()

# Select the device
dev_id = connect.value

# Here we have the option to use a dummy device so that you can run your tests without a physical cluster
dummy_cfg = (
    {
        1: ClusterType.CLUSTER_QCM_RF,
        2: ClusterType.CLUSTER_QCM,
        3: ClusterType.CLUSTER_QRM_RF,
    }
    if dev_id == "dummy_cluster"
    else None
)

cluster = Cluster(name="cluster0", identifier=ip_addresses.get(dev_id), dummy_cfg=dummy_cfg)

print(f"{connect.label} connected")

Dummy-Cluster connected

Reset the Cluster#

We reset the Cluster to enter a well-defined state. Note that resetting will clear all stored parameters and repeats startup calibration, so resetting between experiments is usually not desirable.

[4]:

cluster.reset()
print(cluster.get_system_state())

Status: CRITICAL, Flags: TEMPERATURE_OUT_OF_RANGE, Slot flags: SLOT1_TEMPERATURE_OUT_OF_RANGE, SLOT2_TEMPERATURE_OUT_OF_RANGE, SLOT3_TEMPERATURE_OUT_OF_RANGE

Note that a dummy cluster will raise error flags, this is expected behavior and can be ignored.

Experiment setup#

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.

[5]:

import contextlib

from quantify_scheduler.device_under_test.quantum_device import QuantumDevice
from quantify_scheduler.device_under_test.transmon_element import BasicTransmonElement

# Close QCoDeS instruments with conflicting names
for name in ["device_2q", "q0", "q1"]:
    with contextlib.suppress(KeyError):
        Instrument.find_instrument(name).close()


q0 = BasicTransmonElement("q0")
q0.measure.acq_channel(0)

q1 = BasicTransmonElement("q1")
q1.measure.acq_channel(1)

quantum_device = QuantumDevice("device_2q")
quantum_device.hardware_config(hardware_cfg)

quantum_device.add_element(q0)
quantum_device.add_element(q1)

Set calibrations#

This tutorial explicitly only deals with 2-qubit experiments. As such, we assume that both the qubits and their resonators have already been characterized. For information on how to do this, please see the single transmon qubit tutorial. In order to use this tutorial on your own system, you must first change the calibrated values to match your own system.

For the sake of this tutorial, we will use some template values for both qubits.

[6]:

from utils.tutorial_utils import show_parameters

# ============ READOUT ============ #
q0.reset.duration(100e-6)
q0.measure.acq_delay(100e-9)
q0.measure.pulse_amp(0.05)
q0.measure.pulse_duration(2e-6)
q0.measure.integration_time(1.9e-6)

q1.reset.duration(100e-6)
q1.measure.acq_delay(100e-9)
q1.measure.pulse_amp(0.05)
q1.measure.pulse_duration(2e-6)
q1.measure.integration_time(1.9e-6)

q0.clock_freqs.readout(7.6e9)
q1.clock_freqs.readout(7.7e9)

# ============ DRIVE ============ #
q0.rxy.amp180(0.1)
q0.rxy.motzoi(0.05)
q0.rxy.duration(40e-9)

q1.rxy.amp180(0.1)
q1.rxy.motzoi(0.05)
q1.rxy.duration(40e-9)

q0.clock_freqs.f01(5.1e9)
q1.clock_freqs.f01(5.2e9)

show_parameters(q0, q1)

                                  Type  Unit            q0            q1
Parameter
pulse_type                     measure         SquarePulse   SquarePulse
pulse_amp                      measure                0.05          0.05
pulse_duration                 measure   (s)      0.000002      0.000002
acq_channel                    measure   (#)             0             1
acq_delay                      measure   (s)     0.0000001     0.0000001
integration_time               measure   (s)     0.0000019     0.0000019
reset_clock_phase              measure                True          True
acq_weights_a                  measure                None          None
acq_weights_b                  measure                None          None
acq_weights_sampling_rate      measure                None          None
acq_weight_type                measure                 SSB           SSB
acq_rotation                   measure                   0             0
acq_threshold                  measure                   0             0
duration                         reset   (s)        0.0001        0.0001
f01                        clock_freqs  (Hz)  5100000000.0  5200000000.0
f12                        clock_freqs  (Hz)           NaN           NaN
readout                    clock_freqs  (Hz)  7600000000.0  7700000000.0
amp180                             rxy                 0.1           0.1
motzoi                             rxy                0.05          0.05
duration                           rxy   (s)    0.00000004    0.00000004
microwave                        ports               q0:mw         q1:mw
flux                             ports               q0:fl         q1:fl
readout                          ports              q0:res        q1:res

Configure measurement control loop#

We will use a MeasurementControl object for data acquisition as well as an InstrumentCoordinator for controlling the instruments in our setup.

The PlotMonitor is used for live plotting.

All of these are then associated with the QuantumDevice.

[7]:

from quantify_core.measurement.control import MeasurementControl
from quantify_core.visualization.pyqt_plotmon import PlotMonitor_pyqt as PlotMonitor
from quantify_scheduler.instrument_coordinator import InstrumentCoordinator
from quantify_scheduler.instrument_coordinator.components.qblox import ClusterComponent


def configure_measurement_control_loop(
    device: QuantumDevice, cluster: Cluster, live_plotting: bool = False
) -> None:
    # Close QCoDeS instruments with conflicting names
    for name in [
        "PlotMonitor",
        "meas_ctrl",
        "ic",
        "ic_generic",
        f"ic_{cluster.name}",
    ] + [f"ic_{module.name}" for module in cluster.modules]:
        with contextlib.suppress(KeyError):
            Instrument.find_instrument(name).close()

    meas_ctrl = MeasurementControl("meas_ctrl")
    ic = InstrumentCoordinator("ic")

    # Add cluster to instrument coordinator
    ic_cluster = ClusterComponent(cluster)
    ic.add_component(ic_cluster)

    if live_plotting:
        # Associate plot monitor with measurement controller
        plotmon = PlotMonitor("PlotMonitor")
        meas_ctrl.instr_plotmon(plotmon.name)

    # Associate measurement controller and instrument coordinator with the quantum device
    device.instr_measurement_control(meas_ctrl.name)
    device.instr_instrument_coordinator(ic.name)

    return (meas_ctrl, ic)


meas_ctrl, instrument_coordinator = configure_measurement_control_loop(quantum_device, cluster)

Set data directory#

This directory is where all of the experimental data as well as all of the post processing will go.

[8]:

import quantify_core.data.handling as dh

# Enter your own dataset directory here!
dh.set_datadir(Path("example_data").resolve())

Configure external flux control#

We need to have some way of controlling the external flux.

This can be done by setting an output bias on a module of the cluster which is then connected to the flux-control line.

# e.g. nullify external flux by setting current to 0 A
cluster.module2.out0_current(0.0)

Here we are nullifying the external flux on both qubits.

[9]:

from utils.tutorial_utils import show_args

from quantify_scheduler.helpers.collections import find_port_clock_path


def find_flux_settable(qubit: BasicTransmonElement) -> callable:
    """Return flux port voltage offset for qubit."""
    path = find_port_clock_path(
        quantum_device.hardware_config(), qubit.ports.flux(), "cl0.baseband"
    )
    module = getattr(cluster, path[1].split("_")[1])
    settable = getattr(module, f"out{path[2].split('_')[-1]}_offset")
    return settable


flux_settables = {q.name: find_flux_settable(q) for q in (q0, q1)}

for flux_settable in flux_settables.values():
    flux_settable(0.0)

show_args(flux_settables)

q0 = cluster0_module2_out0_offset
q1 = cluster0_module2_out1_offset

[10]:

flux_settables[q0.name](0.0)  # enter your own value here for qubit 0
flux_settables[q1.name](0.0)  # enter your own value here for qubit 1

Activate NCO delay compensation#

Compensate for the digital propagation delay for each qubit (i.e each sequencer)

For more info, please see: https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/api_reference/sequencer.html#Sequencer.nco_prop_delay_comp

To avoid mismatches between modulation and demodulation, the delay between any readout frequency or phase changes and the next acquisition should be equal or greater than the total propagation delay (146ns + user defined value).

[11]:

for i in range(6):
    getattr(cluster.module3, f"sequencer{i}").nco_prop_delay_comp_en(True)
    getattr(cluster.module3, f"sequencer{i}").nco_prop_delay_comp(10)

Set attenuation#

We ought to make sure that our excitation and readout pulses have the appropriate power. Since we are assuming that the qubits and resonators have already been individually characterised, we use the same attenuation that we used in the single transmon qubit tutorial.

[12]:

from utils.tutorial_utils import set_drive_attenuation, set_readout_attenuation

set_readout_attenuation(quantum_device, q0, out_att=50, in_att=0)
set_readout_attenuation(quantum_device, q1, out_att=50, in_att=0)

set_drive_attenuation(quantum_device, q0, out_att=18)
set_drive_attenuation(quantum_device, q1, out_att=18)

Experiments#

As in the single qubit tuneup tutorial, the sweep setpoints for all experiments in this section are only examples. The sweep setpoints should be changed to match your own system. In this section we assume that each individual qubit has already been characterized, and that they have been biased to their sweetspots.

We will examine the flux response of the 2-qubit system. By “flux response” we mean the measured response of the system when the parameterization of a flux pulse is varied.

We consider two separate experiments which have their own separate parameterizations, they are:

Controlled phase calibration (a.k.a. two-qubit Chevron experiment)
- Used to measure coupling strength between the two qubits.
- Used to find the location of the \(|11\rangle \leftrightarrow |02\rangle\) avoided crossing.
Conditional oscillations
- Used to measure the conditional phase of the controlled phase gate.
- Used to estimate leakage to \(|02\rangle\).
- Can also be used to measure single-qubit phases on the individual qubits.

In both of these experiments, we apply the flux pulse on the flux-control line of q1 (on top of the sweetspot bias) which we take to be the qubit with the higher frequency, i.e. \(\omega_1\) > \(\omega_0\).

Coupled qubits characterization#

Hardware setup#

Configuration file#

Scan For Clusters#

Connect to Cluster#

Reset the Cluster#

Experiment setup#

Quantum device settings#

Set calibrations#

Configure measurement control loop#

Set data directory#

Configure external flux control#

Activate NCO delay compensation#

Set attenuation#

Experiments#

Controlled phase calibration#

Conditional oscillations#