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]:
import numpy as np
from quantify_scheduler import Schedule
from quantify_scheduler.operations.gate_library import Measure, Reset, X
[2]:
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.
[3]:
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.
[4]:
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(
Rabi Oscillations#
[5]:
pulse_amps = np.linspace(-0.14, 0.14, 200)
sched = Schedule("rabi_amplitude", 400)
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=20e-9) # wait 20ns before measuring
rabi_ds = run(schedule=sched, quantum_device=quantum_device)
rabi_ds
[5]:
<xarray.Dataset> Size: 5kB Dimensions: (acq_index_0: 200) Coordinates: * acq_index_0 (acq_index_0) int64 2kB 0 1 2 3 4 5 ... 194 195 196 197 198 199 Data variables: 0 (acq_index_0) complex128 3kB (nan+nanj) ... (nan+nanj)
[6]:
qubit.rxy.amp180(0.07)
[7]:
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'] ] } }
[8]:
quantum_device.to_json_file("devices/")
[8]:
'devices/device_2q_2024-10-28_02-36-46_UTC.json'