Cross-resonance calibration workflow¶

This notebook sketches a practical CR bring-up for one coupled qubit pair: prepare the single-qubit pulse set, obtain CR parameters, calibrate a ZX90 gate, inspect the resulting schedule, and validate it with Bell measurements and interleaved RB.

1. Create an Experiment¶

Pick a known coupled pair for your device. The example below uses the first two qubits from the selected subset, but you should replace them with a pair that already has a calibrated CR path in your system.

In [ ]:

import numpy as np

import qubex as qx

exp = qx.Experiment(
    system_id="YOUR_SYSTEM_ID",
    muxes=[0],
    # config_dir="/path/to/qubex-config/config",
    # params_dir="/path/to/qubex-config/params/YOUR_SYSTEM_ID",
)

import numpy as np import qubex as qx exp = qx.Experiment( system_id="YOUR_SYSTEM_ID", muxes=[0], # config_dir="/path/to/qubex-config/config", # params_dir="/path/to/qubex-config/params/YOUR_SYSTEM_ID", )

In [ ]:

if len(exp.qubit_labels) < 2:
    raise ValueError("Select at least two coupled qubits for CR calibration.")

cr_control, cr_target = exp.qubit_labels[:2]
cr_label = f"{cr_control}-{cr_target}"

print("control qubit:", cr_control)
print("target qubit:", cr_target)
print("pair label:", cr_label)

if len(exp.qubit_labels) < 2: raise ValueError("Select at least two coupled qubits for CR calibration.") cr_control, cr_target = exp.qubit_labels[:2] cr_label = f"{cr_control}-{cr_target}" print("control qubit:", cr_control) print("target qubit:", cr_target) print("pair label:", cr_label)

2. Connect to the setup¶

Connect before you prepare the single-qubit prerequisites or run any CR measurements.

In [ ]:

exp.connect()

exp.connect()

3. Prepare the single-qubit prerequisites¶

Measure the baseline Rabi response, calibrate the single-qubit pulses, and build the readout classifier before you move to CR calibration.

In [ ]:

result_rabi = exp.obtain_rabi_params()
result_hpi = exp.calibrate_hpi_pulse()
result_pi = exp.calibrate_pi_pulse()
result_drag_hpi = exp.calibrate_drag_hpi_pulse()
result_drag_pi = exp.calibrate_drag_pi_pulse()
result_classifier = exp.build_classifier()

result_rabi = exp.obtain_rabi_params() result_hpi = exp.calibrate_hpi_pulse() result_pi = exp.calibrate_pi_pulse() result_drag_hpi = exp.calibrate_drag_hpi_pulse() result_drag_pi = exp.calibrate_drag_pi_pulse() result_classifier = exp.build_classifier()

4. Obtain the CR interaction parameters¶

Use the CR parameter scan to estimate a usable operating point for the entangling drive.

In [ ]:

result_cr = exp.obtain_cr_params(cr_control, cr_target)

result_cr = exp.obtain_cr_params(cr_control, cr_target)

5. Calibrate the ZX90 gate¶

Run the ZX90 calibration once the CR interaction parameters are in place.

In [ ]:

result_cr_calib = exp.calibrate_zx90(
    control_qubit=cr_control,
    target_qubit=cr_target,
)

result_cr_calib = exp.calibrate_zx90( control_qubit=cr_control, target_qubit=cr_target, )

6. Inspect the cached ZX90 schedule¶

Plot the calibrated schedule so you can inspect the pulse structure directly.

In [ ]:

zx90 = exp.zx90(cr_control, cr_target)

zx90.plot()

zx90 = exp.zx90(cr_control, cr_target) zx90.plot()

7. Repeat the calibrated ZX90 sequence¶

Use a repeated-sequence check to confirm that the calibrated gate behaves sensibly.

In [ ]:

repeat_result = exp.repeat_sequence(zx90)

repeat_result = exp.repeat_sequence(zx90)

8. Run pulse tomography with the control qubit in |0>¶

Reconstruct the repeated ZX90 operation with the control qubit initialized in |0>.

In [ ]:

pulse_tomography_0 = exp.pulse_tomography(zx90, initial_state={cr_control: "0"})

pulse_tomography_0 = exp.pulse_tomography(zx90, initial_state={cr_control: "0"})

9. Run pulse tomography with the control qubit in |1>¶

Repeat the same tomography measurement with the control qubit initialized in |1>.

In [ ]:

pulse_tomography_1 = exp.pulse_tomography(zx90, initial_state={cr_control: "1"})

pulse_tomography_1 = exp.pulse_tomography(zx90, initial_state={cr_control: "1"})

10. Measure the Bell state¶

Use a Bell-state measurement as a direct entangling-gate validation step.

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result_bell = exp.measure_bell_state(cr_control, cr_target)

result_bell_tomography = exp.bell_state_tomography(cr_control, cr_target)

result_bell = exp.measure_bell_state(cr_control, cr_target) result_bell_tomography = exp.bell_state_tomography(cr_control, cr_target)

11. Run interleaved randomized benchmarking¶

Estimate the ZX90 gate error with interleaved RB.

In [ ]:

result_irb = exp.interleaved_randomized_benchmarking(
    cr_label,
    interleaved_clifford="ZX90",
    n_trials=30,
)

result_irb = exp.interleaved_randomized_benchmarking( cr_label, interleaved_clifford="ZX90", n_trials=30, )

12. Save the calibration note¶

Save the final CR calibration once the validation steps look acceptable.

In [ ]:

exp.calib_note.save()

exp.calib_note.save()