Experimental demonstration of Pauli-frame randomization on a superconducting qubit

TL;DR

This paper demonstrates Pauli-frame randomization on a superconducting qubit, significantly reducing non-Markovian errors and aligning errors with a Pauli model without sacrificing fidelity, thus advancing scalable quantum computing.

Contribution

It provides the first experimental implementation of Pauli-frame randomization in superconducting qubits, effectively suppressing non-Markovian errors and validating the approach with detailed error characterization.

Findings

Randomization suppresses non-Markovian signatures from over 43σ to below 3σ.

Errors under randomization are well described by a Pauli error model.

Fidelity is maintained or improved despite error suppression.

Abstract

The promise of quantum computing with imperfect qubits relies on the ability of a quantum computing system to scale cheaply through error correction and fault-tolerance. While fault-tolerance requires relatively mild assumptions about the nature of qubit errors, the overhead associated with coherent and non-Markovian errors can be orders of magnitude larger than the overhead associated with purely stochastic Markovian errors. One proposal to address this challenge is to randomize the circuits of interest, shaping the errors to be stochastic Pauli errors but leaving the aggregate computation unaffected. The randomization technique can also suppress couplings to slow degrees of freedom associated with non-Markovian evolution. Here we demonstrate the implementation of Pauli-frame randomization in a superconducting circuit system, exploiting a flexible programming and control infrastructure to achieve this with low effort. We use high-accuracy gate-set tomography to characterize in detail the properties of the circuit error, with and without the randomization procedure, which allows us to make rigorous statements about Markovianity as well as the nature of the observed errors. We demonstrate that randomization suppresses signatures of non-Markovian evolution to statistically insignificant levels, from a Markovian model violation ranging from $43\sigma$ to $1987\sigma$, down to violations between $0.3\sigma$ and $2.7\sigma$ under randomization. Moreover, we demonstrate that, under randomization, the experimental errors are well described by a Pauli error model, with model violations that are similarly insignificant (between $0.8\sigma$ and $2.7\sigma$). Importantly, all these improvements in the model accuracy were obtained without degradation to fidelity, and with some improvements to error rates as quantified by the diamond norm.