Identifying Materials-Level Sources of Performance Variation in Superconducting Transmon Qubits

  1. Akshay A. Murthy,
  2. Mustafa Bal,
  3. Michael J. Bedzyk,
  4. Hilal Cansizoglu,
  5. Randall K. Chan,
  6. Venkat Chandrasekhar,
  7. Francesco Crisa,
  8. Amlan Datta,
  9. Yanpei Deng,
  10. Celeo D. Matute Diaz,
  11. Vinayak P. Dravid,
  12. David A. Garcia-Wetten,
  13. Sabrina Garattoni,
  14. Sunil Ghimire,
  15. Dominic P. Goronzy,
  16. Sebastian de Graaf,
  17. Sam Haeuser,
  18. Mark C. Hersam,
  19. Dieter Isheim,
  20. Kamal Joshi,
  21. Richard Kim,
  22. Saagar Kolachina,
  23. Cameron J. Kopas,
  24. Matthew J. Kramer,
  25. Ella O. Lachman,
  26. Jaeyel Lee,
  27. Peter G. Lim,
  28. Andrei Lunin,
  29. William Mah,
  30. Jayss Marshall,
  31. Josh Y. Mutus,
  32. Jin-Su Oh,
  33. David Olaya,
  34. David P. Pappas,
  35. Joong-mok Park,
  36. Ruslan Prozorov,
  37. Roberto dos Reis,
  38. David N. Seidman,
  39. Zuhawn Sung,
  40. Makariy Tanatar,
  41. Mitchell J. Walker,
  42. Jigang Wang,
  43. Haotian Wu,
  44. Lin Zhou,
  45. Shaojiang Zhu,
  46. Anna Grassellino,
  47. and Alexander Romanenko
The Superconducting Materials and Systems (SQMS) Center, a DOE National Quantum Information Science Research Center, has conducted a comprehensive and coordinated study using superconducting
transmon qubit chips with known performance metrics to identify the underlying materials-level sources of device-to-device performance variation. Following qubit coherence measurements, these qubits of varying base superconducting metals and substrates have been examined with various nondestructive and invasive material characterization techniques at Northwestern University, Ames National Laboratory, and Fermilab as part of a blind study. We find trends in variations of the depth of the etched substrate trench, the thickness of the surface oxide, and the geometry of the sidewall, which when combined, lead to correlations with the T1 lifetime across different devices. In addition, we provide a list of features that varied from device to device, for which the impact on performance requires further studies. Finally, we identify two low-temperature characterization techniques that may potentially serve as proxy tools for qubit measurements. These insights provide materials-oriented solutions to not only reduce performance variations across neighboring devices, but also to engineer and fabricate devices with optimal geometries to achieve performance metrics beyond the state-of-the-art values.

Potential Nanoscale Sources of Decoherence in Niobium based Transmon Qubit Architectures

  1. Akshay A. Murthy,
  2. Paul Masih Das,
  3. Stephanie M. Ribet,
  4. Cameron Kopas,
  5. Jaeyel Lee,
  6. Matthew J. Reagor,
  7. Lin Zhou,
  8. Matthew J. Kramer,
  9. Mark C. Hersam,
  10. Mattia Checchin,
  11. Anna Grassellino,
  12. Roberto dos Reis,
  13. Vinayak P. Dravid,
  14. and Alexander Romanenko
Superconducting thin films of niobium have been extensively employed in transmon qubit architectures. Although these architectures have demonstrated remarkable improvements in recent
years, further improvements in performance through materials engineering will aid in large-scale deployment. Here, we use information retrieved from electron microscopy and analysis to conduct a detailed assessment of potential decoherence sources in transmon qubit test devices. In the niobium thin film, we observe the presence of localized strain at interfaces, which may amplify interactions between two-level systems and impose limits on T1 and T2 relaxation times. Additionally, we observe the presence of a surface oxide with varying stoichiometry and bond distances, which can generate a broad two-level system noise spectrum. Finally, a similarly disordered and rough interface is observed between Nb and the Si substrate. We propose that this interface can also degrade the overall superconducting properties.