Jeroen Danon

Real-time adaptive tracking of fluctuating relaxation rates in superconducting qubits

  1. Fabrizio Berritta,
  2. Jacob Benestad,
  3. Jan A. Krzywda,
  4. Oswin Krause,
  5. Malthe A. Marciniak,
  6. Svend Krøjer,
  7. Christopher W. Warren,
  8. Emil Hogedal,
  9. Andreas Nylander,
  10. Irshad Ahmad,
  11. Amr Osman,
  12. Janka Biznárová,
  13. Marcus Rommel,
  14. Anita Fadavi Roudsari,
  15. Jonas Bylander,
  16. Giovanna Tancredi,
  17. Jeroen Danon,
  18. Jacob Hastrup,
  19. Ferdinand Kuemmeth,
  20. and Morten Kjaergaard
The fidelity of operations on a solid-state quantum processor is ultimately bounded by decoherence effects induced by a fluctuating environment. Characterizing environmental fluctuations
is challenging because the acquisition time of experimental protocols limits the precision with which the environment can be measured and may obscure the detailed structure of these fluctuations. Here we present a real-time Bayesian method for estimating the relaxation rate of a qubit, leveraging a classical controller with an integrated field-programmable gate array (FPGA). Using our FPGA-powered Bayesian method, we adaptively and continuously track the relaxation-time fluctuations of two fixed-frequency superconducting transmon qubits, which exhibit average relaxation times of approximately 0.17 ms and occasionally exceed 0.5 ms. Our technique allows for the estimation of these relaxation times in a few milliseconds, more than two orders of magnitude faster than previous nonadaptive methods, and allows us to observe fluctuations up to 5 times the qubit’s average relaxation rates on significantly shorter timescales than previously reported. Our statistical analysis reveals that these fluctuations occur on much faster timescales than previously understood, with two-level-system switching rates reaching up to 10 Hz. Our work offers an appealing solution for rapid relaxation-rate characterization in device screening and for improved understanding of fast relaxation dynamics.
arxiv pdf

Efficient Qubit Calibration by Binary-Search Hamiltonian Tracking

  1. Fabrizio Berritta,
  2. Jacob Benestad,
  3. Lukas Pahl,
  4. Melvin Mathews,
  5. Jan A. Krzywda,
  6. Réouven Assouly,
  7. Youngkyu Sung,
  8. David K. Kim,
  9. Bethany M. Niedzielski,
  10. Kyle Serniak,
  11. Mollie E. Schwartz,
  12. Jonilyn L. Yoder,
  13. Anasua Chatterjee,
  14. Jeffrey A. Grover,
  15. Jeroen Danon,
  16. William D. Oliver,
  17. and Ferdinand Kuemmeth
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 probing
sequences 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.
arxiv pdf