Parasitic two-level-system (TLS) defects are a major source of energy relaxation and temporal instability in superconducting quantum processors. Our sub-second adaptive spectroscopyreveals telegraphic switching of TLSs with a characteristic timescale of a few seconds and spectral diffusion with diffusivity D≈0.9 MHz2/s. These timescales are about 3×102 times faster than what is observed in conventional nonadaptive spectroscopy, which typically requires hours of measurement time. We resolve such fast dynamics on a field-programmable gate array (FPGA)-based controller that enables measurement of frequency- and time-resolved relaxations with sub-second temporal resolution in flux-tunable superconducting qubits. We observe similar defect dynamics across multiple qubits in independently fabricated devices measured in different laboratories. We correlate TLS-induced fluctuations with gate-level errors using randomized benchmarking. Our results reveal a previously inaccessible regime of frequency-resolved TLS dynamics and redefine the timescales relevant to TLS-aware characterization and calibration of superconducting quantum processors.
Quantum error correcting codes (QECCs) with asymptotically lower overheads than the surface code require non-local connectivity. Leveraging multi-layer routing and long-range couplingcapabilities in superconducting qubit hardware, we develop Hardware-Aware Layout, HAL: a robust, runtime-efficient heuristic algorithm that automates and optimizes the placement and routing of arbitrary QECCs. Using HAL, we perform a comparative study of hardware cost across various families of QECCs, including the bivariate bicycle codes, the open-boundary tile codes, and the constant-depth-decodable radial codes. The layouts produced by HAL confirm that open boundaries significantly reduce the hardware cost, while incurring reductions in logical efficiency. Among the best-performing codes were low-weight radial codes, despite lacking topological structure. Overall, HAL provides a valuable framework for evaluating the hardware feasibility of existing QECCs and guiding the discovery of new codes compatible with realistic hardware constraints.
We present a real-time method for calibrating the frequency of a resonantly driven qubit. The real-time processing capabilities of a controller dynamically compute adaptive probingsequences for qubit-frequency estimation. Each probing time and drive frequency are calculated to divide the prior probability distribution into two branches, following a locally optimal strategy that mimics a conventional binary search. We show the algorithm’s efficacy by stabilizing a flux-tunable transmon qubit, leading to improved coherence and gate fidelity. By feeding forward the updated qubit frequency, the FPGA-powered control electronics also mitigates non-Markovian noise in the system, which is detrimental to quantum error correction. Our protocol highlights the importance of feedback in improving the calibration and stability of qubits subject to drift and can be readily applied to other qubit platforms.