Quantum Computer Calibration Now Happens in Just 10 Milliseconds
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Scientists are increasingly focused on mitigating the effects of parameter drift in superconducting qubits, which occurs on timescales faster than conventional calibration methods can address. Malthe A. Marciniak, Rune T. Birke, and Johann B. Severin, working with colleagues from the Center for Quantum Devices and the NNF Quantum Computing Programme at the Niels Bohr Institute, University of Copenhagen, Denmark, present a novel on-FPGA workflow capable of millisecond-scale calibration and benchmarking.
This research is significant because it demonstrates a fully integrated system for pulse generation, data acquisition, analysis, and feed-forward, eliminating delays associated with CPU-based processing. Their implementation of sparse-sampling and on-FPGA inference tools facilitates rapid readout calibration, spectroscopy, pulse-amplitude optimisation, coherence estimation, and benchmarking, ultimately enabling over 74,000 consecutive recalibrations and sustained high-performance gate fidelity through continuous, closed-loop optimisation.
Scientists have developed a calibration and benchmarking workflow for superconducting qubits that operates on millisecond timescales, addressing a critical limitation imposed by rapidly fluctuating qubit parameters. Furthermore, Clifford randomized gate benchmarking, a standard method for assessing gate fidelity, is completed in 107 milliseconds. Deploying a closed-loop recalibration protocol continuously for six hours enabled over 74,000 consecutive recalibrations, consistently yielding superior gate performance compared to initial calibration settings. By quantifying the trade-off between estimation uncertainty and decision time under sparse sampling, the researchers identified optimal parameter regimes for efficient qubit and pulse parameter estimation. Measurements reveal rapid fluctuations in qubit coherence, with T1 values fluctuating over a two-second window. Furthermore, Clifford randomized gate benchmarking was completed in 107 milliseconds. The research profiles the timing budget of each calibration primitive and quantifies the trade-off between time-to-decision and estimator precision under sparse sampling, identifying optimal parameter regimes for efficient estimation of both T1 and pulse parameters. Recognising that superconducting qubit parameters drift on sub-second timescales, the research focused on developing calibration and benchmarking techniques executable on millisecond timescales to counteract these fluctuations. Central to this approach was an on-FPGA workflow, meticulously designed to co-locate pulse generation, data acquisition, analysis, and feed-forward control, thereby eliminating the delays inherent in conventional CPU-based round trips. This contrasts with traditional methods where data is transferred to a central computer for analysis, introducing significant latency. The resulting low-latency primitives were then deployed for tasks including readout calibration, spectroscopy, pulse-amplitude calibration, coherence estimation, and comprehensive benchmarking. Correlation analysis confirmed that this recalibration effectively suppressed the coupling of gate error to control-parameter drift, while simultaneously preserving performance linked to qubit coherence. For years, researchers have battled parameter drift, the subtle but persistent shifts in calibration that degrade performance over time. This work doesn’t simply offer another incremental improvement in coherence or gate fidelity; it presents a fundamentally different approach to managing this drift, shifting the burden from slow, CPU-bound post-processing to rapid, on-chip recalibration. This is a significant leap forward, enabling continuous recalibration, over 74,000 cycles in a six-hour period, and demonstrably improved gate performance. However, the reliance on specific signal models, such as exponential and sine-like functions, represents a limitation. Real quantum systems are rarely so neatly described. Ultimately, the goal is not just to correct for drift, but to build systems resilient enough to withstand it. 👉 More information 🗞 Millisecond-Scale Calibration and Benchmarking of Superconducting Qubits 🧠 ArXiv: https://arxiv.org/abs/2602.11912 Tags: Rohail T. As a quantum scientist exploring the frontiers of physics and technology. My work focuses on uncovering how quantum mechanics, computing, and emerging technologies are transforming our understanding of reality. I share research-driven insights that make complex ideas in quantum science clear, engaging, and relevant to the modern world. Latest Posts by Rohail T.: Statistical Modelling Now Maps Complex Variations with Greater Precision February 17, 2026 Climate Models Assessed to Improve River Flow Projections for Water Management February 16, 2026 Automation of All Work Is Theoretically Possible, New Research Suggests February 16, 2026