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.

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: - QCM-RF (Slot 6) - Drive line for q0 using fixed 80 MHz IF. - Drive line for q1 using fixed 80 MHz IF. - QCM (Slot 2) - Flux line for q0. - Flux line for q1. - QRM-RF (Slot 8) - 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]:

import json

import rich

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

Scan For Clusters#

We scan for the available devices connected via ethernet using the Plug & Play functionality of the Qblox Instruments package (see Plug & Play for more info).

[2]:

!qblox-pnp list

No devices found

[3]:

cluster_ip = None  # To run this tutorial on hardware, fill in the IP address of the cluster here
cluster_name = "cluster0"

Connect to Cluster#

We now make a connection with the Cluster.

[4]:

from qcodes.instrument import find_or_create_instrument

from qblox_instruments import Cluster, ClusterType

cluster = find_or_create_instrument(
    Cluster,
    recreate=True,
    name=cluster_name,
    identifier=cluster_ip,
    dummy_cfg=(
        {
            2: ClusterType.CLUSTER_QCM,
            4: ClusterType.CLUSTER_QRM,
            6: ClusterType.CLUSTER_QCM_RF,
            8: ClusterType.CLUSTER_QRM_RF,
        }
        if cluster_ip is None
        else None
    ),
)

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.

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.

[5]:

from quantify_scheduler.device_under_test.quantum_device import QuantumDevice

quantum_device = QuantumDevice.from_json_file("devices/transmon_device_2q.json")
q0 = quantum_device.get_element("q0")
q1 = quantum_device.get_element("q1")
quantum_device.hardware_config(hardware_cfg)

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.

[6]:

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
):
    meas_ctrl = find_or_create_instrument(MeasurementControl, recreate=True, name="meas_ctrl")
    ic = find_or_create_instrument(InstrumentCoordinator, recreate=True, name="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 = find_or_create_instrument(PlotMonitor, recreate=False, name="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.

[7]:

import quantify_core.data.handling as dh

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

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

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.

Here we are nullifying the external flux on both qubits.

[8]:

flux_settables = {q0.name: cluster.module2.out0_offset, q1.name: cluster.module2.out1_offset}

for flux_settable in flux_settables.values():
    flux_settable.inter_delay = 100e-9  # Delay time in seconds between consecutive set operations.
    flux_settable.step = 0.3e-3  # Stepsize in V that this Parameter uses during set operation.
    flux_settable()  # Get before setting to avoid jumps.
    flux_settable(0.0)

[9]:

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/main/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).

[10]:

for i in range(6):
    getattr(cluster.module8, f"sequencer{i}").nco_prop_delay_comp_en(True)
    getattr(cluster.module8, f"sequencer{i}").nco_prop_delay_comp(10)

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. \(\omega_1\) > \(\omega_0\).