Leakage detection for a transmon-based surface code

Journal Article (2020)
Author(s)

Boris Varbanov (TU Delft - QCD/Terhal Group, TU Delft - QuTech Advanced Research Centre)

Francesco Battistel (TU Delft - QCD/Terhal Group, TU Delft - QuTech Advanced Research Centre)

Brian Michael Tarasinski (TU Delft - QuTech Advanced Research Centre, TU Delft - QCD/DiCarlo Lab, Kavli institute of nanoscience Delft)

V.P. Ostroukh (TU Delft - QRD/Wimmer Group, Kavli institute of nanoscience Delft)

Thomas Eugene O’Brien (Google LLC, Universiteit Leiden)

L DiCarlo (TU Delft - QN/DiCarlo Lab, TU Delft - QCD/DiCarlo Lab, Kavli institute of nanoscience Delft, TU Delft - QuTech Advanced Research Centre)

B. M. Terhal (Forschungszentrum Jülich, TU Delft - QCD/Terhal Group, TU Delft - QuTech Advanced Research Centre, TU Delft - Quantum Computing)

Research Group
QCD/Terhal Group
Copyright
© 2020 B.M. Varbanov, F. Battistel, B.M. Tarasinski, V.P. Ostroukh, Thomas Eugene O’Brien, L. DiCarlo, B.M. Terhal
DOI related publication
https://doi.org/10.1038/s41534-020-00330-w
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 B.M. Varbanov, F. Battistel, B.M. Tarasinski, V.P. Ostroukh, Thomas Eugene O’Brien, L. DiCarlo, B.M. Terhal
Research Group
QCD/Terhal Group
Issue number
1
Volume number
6
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Abstract

Leakage outside of the qubit computational subspace, present in many leading experimental platforms, constitutes a threatening error for quantum error correction (QEC) for qubits. We develop a leakage-detection scheme via Hidden Markov models (HMMs) for transmon-based implementations of the surface code. By performing realistic density-matrix simulations of the distance-3 surface code (Surface-17), we observe that leakage is sharply projected and leads to an increase in the surface-code defect probability of neighboring stabilizers. Together with the analog readout of the ancilla qubits, this increase enables the accurate detection of the time and location of leakage. We restore the logical error rate below the memory break-even point by post-selecting out leakage, discarding less than half of the data for the given noise parameters. Leakage detection via HMMs opens the prospect for near-term QEC demonstrations, targeted leakage reduction and leakage-aware decoding and is applicable to other experimental platforms.