See also
A Jupyter notebook version of this tutorial can be downloaded here
.
Rabi Oscillations#
Here we will carry out an experiment to measure the Rabi frequency that is required to excite the qubit to \(|1\rangle\).
[1]:
from __future__ import annotations
import json
import numpy as np
import rich # noqa:F401
from qcodes.instrument import find_or_create_instrument
from qcodes.parameters import ManualParameter
import quantify_core.data.handling as dh
from qblox_instruments import Cluster, ClusterType
from quantify_core.measurement.control import MeasurementControl
from quantify_core.visualization.pyqt_plotmon import PlotMonitor_pyqt as PlotMonitor
from quantify_scheduler import Schedule
from quantify_scheduler.device_under_test.quantum_device import QuantumDevice
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, X
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 setup is as follows, by cluster slot: - QCM (Slot 2) - Flux line for q0
. - QCM-RF (Slot 6) - Drive line for q0
using fixed 80 MHz IF. - QRM-RF (Slot 8) - Readout line for q0
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.
[2]:
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
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).
[3]:
!qblox-pnp list
No devices found
[4]:
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.
[5]:
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
),
)
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.
[6]:
quantum_device = QuantumDevice.from_json_file("devices/transmon_device_2q.json")
qubit = quantum_device.get_element("q0")
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
.
[7]:
def configure_measurement_control_loop(
device: QuantumDevice, cluster: Cluster, live_plotting: bool = False
) -> tuple[MeasurementControl, InstrumentCoordinator]:
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)
Rabi Oscillations#
[8]:
def rabi_amp_sched(
qubit, # noqa: ANN001
pulse_amps: np.array,
repetitions: int = 1,
) -> Schedule:
"""
Generate a batched schedule rabi amplitude experiement.
Parameters
----------
qubit
qubit that should be used.
pulse_amps
Sample amplitude for the burst pulse.
repetitions
The amount of times the Schedule will be repeated.
"""
sched = Schedule("rabi_amplitude", repetitions)
for acq_idx, pulse_amp in enumerate(pulse_amps):
sched.add(Reset(qubit.name))
sched.add(X(qubit.name, amp180=pulse_amp))
sched.add(
Measure(qubit.name, acq_index=acq_idx), rel_time=200e-9
) # wait 200ns before measuring
return sched
pulse_amps = ManualParameter(name="pulse_amplitude", unit="V", label="amplitude")
pulse_amps.batched = True
rabi_sched_kwargs = {
"qubit": qubit, # noqa: ANN001
"pulse_amps": pulse_amps,
}
gettable = ScheduleGettable(
quantum_device,
schedule_function=rabi_amp_sched,
schedule_kwargs=rabi_sched_kwargs,
batched=True,
)
meas_ctrl.gettables(gettable)
[9]:
quantum_device.cfg_sched_repetitions(400)
amplitude_setpoints = np.linspace(-0.14, 0.14, 200)
meas_ctrl.settables(pulse_amps)
meas_ctrl.setpoints(amplitude_setpoints)
rabi_ds = meas_ctrl.run("Rabi")
rabi_ds
Starting batched measurement...
Iterative settable(s) [outer loop(s)]:
--- (None) ---
Batched settable(s):
pulse_amplitude
Batch size limit: 200
/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(
[9]:
<xarray.Dataset> Size: 5kB Dimensions: (dim_0: 200) Coordinates: x0 (dim_0) float64 2kB -0.14 -0.1386 -0.1372 ... 0.1372 0.1386 0.14 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: 20240918-145756-706-2c54a4 name: Rabi grid_2d: False grid_2d_uniformly_spaced: False 1d_2_settables_uniformly_spaced: False
qubit.rxy.amp180(0.07)
[10]:
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'] ] } }
[11]:
quantum_device.to_json_file("devices/")
[11]:
'devices/device_2q_2024-09-18_14-57-57_UTC.json'