Researchers of the Hanoi University of Science and Vietnam National University have achieved an advance in quantum gate control, reducing over-rotation errors on a transmon qubit from 0.997° to -0.007° using a new method called DRAPE. The work demonstrates simultaneous calibration of both rotation and phase errors in a single experiment, a departure from traditional methods requiring iterative measurements for each type of error. This efficiency stems from a parametrization linking the errors to system parameters, enabling a Ramsey-type protocol where sweeping the phase-error correction reveals a precise calibration point. The phase correction is estimated with Heisenberg scaling, while the rotation error reaches the standard quantum limit; the paper reports a phase error reduction to 0.0052° per gate, validated by independent amplification protocols.
Researchers demonstrated DRAPE on an IBM transmon qubit, reversing over-rotation from 0.997° to -0.007° and reducing phase error from 2.52° to 0.0052° per gate. DRAPE achieves Heisenberg scaling for phase error estimation, meaning precision improves with increasing measurement count, while rotation error is limited by the standard quantum limit. Independent phase- and rotation-error amplification protocols validated the results, confirming the protocol’s accuracy. DRAPE offers a pathway toward more efficient and precise control of quantum systems, potentially accelerating progress in quantum computation and simulation.
The prevailing approach to minimizing quantum gate errors typically involves separate, iterative experiments to address rotation and phase inaccuracies; however, a new parametrization offers a unified solution. This connection underpins DRAPE, a Ramsey-type protocol that simultaneously calibrates both errors by identifying a crossing point during phase-error correction sweeps. This simultaneous calibration represents an efficiency gain in quantum control.
👉 More information
🗞 Simultaneous calibration of rotation and phase errors in a single experiment
✍️ Tien D. Nguyen and Hung Q. Nguyen
🧠 ArXiv: https://arxiv.org/abs/2607.19187
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