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    Time-adaptive single-shot crosstalk detector on a superconducting quantum computer

    Haiyue Kang1,*, Benjamin Harper1,2, Muhammad Usman1,2, and Martin Sevior1

    • 1School of Physics, University of Melbourne, Parkville, Victoria 3010, Australia
    • 2Quantum Systems, Data61, CSIRO, Clayton, Victoria 3168, Australia

    • *Contact author: haiyuek@student.unimelb.edu.au

    Phys. Rev. Applied 24, 024034 – Published 14 August, 2025

    DOI: https://doi.org/10.1103/mbkk-j663

    Abstract

    Quantum crosstalk, which stems from unwanted interference of quantum operations with nearby qubits, is a major source of noise or errors in a quantum processor. In the context of shared quantum computing, it is challenging to mitigate the crosstalk effect between quantum computations being simultaneously run by multiple users since the exact spatiotemporal gate distributions are not apparent due to privacy concerns. It is therefore important to develop techniques for accurate detection and mitigation of crosstalk to enable high-fidelity quantum computing. Assuming prior knowledge of crosstalk parameters, we propose a time-adaptive detection method leveraging spectator qubits and multiple quantum coherence to amplify crosstalk-induced perturbations. We demonstrate its utility in detecting random sparsely distributed crosstalk within a time window. Our work evaluates its performance in two scenarios: simulation using an artificial noise model with gate-induced crosstalk and always-on idlings channels; and the simulation using noise sampled from an IBM quantum computer parameterized by the reduced Hamiltonian, stochastic, and affine (HSA) error model. The presented results show our method’s efficacy hinges on the dominance of single-qubit coherent noise across channels, and the effect of angle mismatching is suppressed as spectator qubits increase. From simulation using real-device noise parameters, our strategy outperforms the previous constant-frequency detection method of Harper et al. [arXiv:2402.02753] in the detection success rate, achieving an average detection success probability of 0.852±0.022 (equally scaled noise channels) and 0.933±0.024 (asymmetrically scaled noise channels) from one to seven crosstalk counts.

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