Coupled qubits characterization

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,
                    },
                ],
            },
        },
    },
}

[2]:

import warnings
from pathlib import Path

import ipywidgets as widgets
import numpy as np
import quantify_core.data.handling as dh
import matplotlib.pyplot as plt
from IPython.display import display
from qblox_instruments import Cluster, ClusterType, PlugAndPlay
from qcodes import Instrument
from qcodes.parameters import ManualParameter
from quantify_core.analysis.single_qubit_timedomain import RabiAnalysis, RamseyAnalysis, T1Analysis
from quantify_core.measurement.control import MeasurementControl
from quantify_core.visualization.pyqt_plotmon import PlotMonitor_pyqt as PlotMonitor
from quantify_scheduler.device_under_test.quantum_device import QuantumDevice
from quantify_scheduler.device_under_test.transmon_element import BasicTransmonElement
from quantify_scheduler.gettables import ScheduleGettable
from quantify_scheduler.instrument_coordinator import InstrumentCoordinator
from quantify_scheduler.instrument_coordinator.components.qblox import ClusterComponent
from quantify_scheduler.operations.gate_library import Measure, Reset
from quantify_scheduler.operations.pulse_library import SetClockFrequency, SquarePulse
from quantify_scheduler.resources import ClockResource
from quantify_scheduler.schedules import heterodyne_spec_sched_nco, rabi_sched, t1_sched
from quantify_scheduler.schedules.timedomain_schedules import ramsey_sched
from quantify_scheduler.schedules.schedule import Schedule
from quantify_scheduler.helpers.collections import find_port_clock_path

from utils.tutorial_analysis_classes import (
    QubitFluxSpectroscopyAnalysis,
    QubitSpectroscopyAnalysis,
    ResonatorFluxSpectroscopyAnalysis,
    ConditionalOscillationAnalysis
)
from utils.tutorial_utils import (
    set_drive_attenuation,
    set_readout_attenuation,
    show_args,
    show_parameters
)

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).

[3]:

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.keys()
    ],
    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.

[4]:

# 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.

[5]:

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

Status: CRITICAL, Flags: CARRIER_TEMPERATURE_OUT_OF_RANGE, FPGA_TEMPERATURE_OUT_OF_RANGE, Slot flags: SLOT1_CARRIER_TEMPERATURE_OUT_OF_RANGE, SLOT1_FPGA_TEMPERATURE_OUT_OF_RANGE, SLOT2_CARRIER_TEMPERATURE_OUT_OF_RANGE, SLOT2_FPGA_TEMPERATURE_OUT_OF_RANGE, SLOT3_CARRIER_TEMPERATURE_OUT_OF_RANGE, SLOT3_FPGA_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.

[6]:

# Close QCoDeS instruments with conflicting names
for name in ["device_2q", "q0", "q1"]:
    try:
        Instrument.find_instrument(name).close()
    except KeyError as kerr:
        pass

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.

[7]:

# ============ 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
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.

[8]:

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]:
        try:
            Instrument.find_instrument(name).close()
        except KeyError as kerr:
            pass

    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.

[9]:

# 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.

[10]:

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

[11]:

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#pulsar-qcm-sequencer-nco-prop-delay-comp-en

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).

[12]:

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.

[13]:

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)