Learning How to Dynamically Decouple

TL;DR

This paper proposes optimizing dynamical decoupling sequences by tailoring their rotational gates to specific quantum hardware, significantly improving noise suppression in superconducting qubits and enhancing quantum circuit performance.

Contribution

It introduces a method to optimize dynamical decoupling sequences for specific hardware, outperforming standard sequences like CPMG, XY4, and UR6.

Findings

Optimized sequences outperform canonical decoupling methods.

Enhanced noise suppression in superconducting qubits.

Improved quantum circuit fidelity on noisy hardware.

Abstract

Current quantum computers suffer from noise that stems from interactions between the quantum system that constitutes the quantum device and its environment. These interactions can be suppressed through dynamical decoupling to reduce computational errors. However, the performance of dynamical decoupling depends on the type of the system-environment interactions that are present, which often lack an accurate model in quantum devices. We show that the performance of dynamical decoupling can be improved by optimizing its rotational gates to tailor them to the quantum hardware. We find that compared to canonical decoupling sequences, such as CPMG, XY4, and UR6, the optimized dynamical decoupling sequences yield the best performance in suppressing noise in superconducting qubits. Our work thus enhances existing error suppression methods which helps increase circuit depth and result quality on noisy hardware.