System Characterization of Dispersive Readout in Superconducting Qubits

  1. Daniel Sank,
  2. Alex Opremcak,
  3. Andreas Bengtsson,
  4. Mostafa Khezri,
  5. Zijun Chen,
  6. Ofer Naaman,
  7. and Alexander Korotkov
Designing quantum systems with the measurement speed and accuracy needed for quantum error correction using superconducting qubits requires iterative design and test informed by accurate
models and characterization tools. We introduce a single protocol, with few prerequisite calibrations, which measures the dispersive shift, resonator linewidth, and drive power used in the dispersive readout of superconducting qubits. We find that the resonator linewidth is poorly controlled with a factor of 2 between the maximum and minimum measured values, and is likely to require focused attention in future quantum error correction experiments. We also introduce a protocol for measuring the readout system efficiency using the same power levels as are used in typical qubit readout, and without the need to measure the qubit coherence. We routinely run these protocols on chips with tens of qubits, driven by automation software with little human interaction. Using the extracted system parameters, we find that a model based on those parameters predicts the readout signal to noise ratio to within 10% over a device with 54 qubits.

Readout of a quantum processor with high dynamic range Josephson parametric amplifiers

  1. T. C. White,
  2. Alex Opremcak,
  3. George Sterling,
  4. Alexander Korotkov,
  5. Daniel Sank,
  6. Rajeev Acharya,
  7. Markus Ansmann,
  8. Frank Arute,
  9. Kunal Arya,
  10. Joseph C Bardin,
  11. Andreas Bengtsson,
  12. Alexandre Bourassa,
  13. Jenna Bovaird,
  14. Leon Brill,
  15. Bob B. Buckley,
  16. David A. Buell,
  17. Tim Burger,
  18. Brian Burkett,
  19. Nicholas Bushnell,
  20. Zijun Chen,
  21. Ben Chiaro,
  22. Josh Cogan,
  23. Roberto Collins,
  24. Alexander L. Crook,
  25. Ben Curtin,
  26. Sean Demura,
  27. Andrew Dunsworth,
  28. Catherine Erickson,
  29. Reza Fatemi,
  30. Leslie Flores-Burgos,
  31. Ebrahim Forati,
  32. Brooks Foxen,
  33. William Giang,
  34. Marissa Giustina,
  35. Alejandro Grajales Dau,
  36. Michael C. Hamilton,
  37. Sean D. Harrington,
  38. Jeremy Hilton,
  39. Markus Hoffmann,
  40. Sabrina Hong,
  41. Trent Huang,
  42. Ashley Huff,
  43. Justin Iveland,
  44. Evan Jeffrey,
  45. Mária Kieferová,
  46. Seon Kim,
  47. Paul V. Klimov,
  48. Fedor Kostritsa,
  49. John Mark Kreikebaum,
  50. David Landhuis,
  51. Pavel Laptev,
  52. Lily Laws,
  53. Kenny Lee,
  54. Brian J. Lester,
  55. Alexander Lill,
  56. Wayne Liu,
  57. Aditya Locharla,
  58. Erik Lucero,
  59. Trevor McCourt,
  60. Matt McEwen,
  61. Xiao Mi,
  62. Kevin C. Miao,
  63. Shirin Montazeri,
  64. Alexis Morvan,
  65. Matthew Neeley,
  66. Charles Neill,
  67. Ani Nersisyan,
  68. Jiun How Ng,
  69. Anthony Nguyen,
  70. Murray Nguyen,
  71. Rebecca Potter,
  72. Chris Quintana,
  73. Pedram Roushan,
  74. Kannan Sankaragomathi,
  75. Kevin J. Satzinger,
  76. Christopher Schuster,
  77. Michael J. Shearn,
  78. Aaron Shorter,
  79. Vladimir Shvarts,
  80. Jindra Skruzny,
  81. W. Clarke Smith,
  82. Marco Szalay,
  83. Alfredo Torres,
  84. Bryan Woo,
  85. Z. Jamie Yao,
  86. Ping Yeh,
  87. Juhwan Yoo,
  88. Grayson Young,
  89. Ningfeng Zhu,
  90. Nicholas Zobrist,
  91. Yu Chen,
  92. Anthony Megrant,
  93. Julian Kelly,
  94. and Ofer Naaman
We demonstrate a high dynamic range Josephson parametric amplifier (JPA) in which the active nonlinear element is implemented using an array of rf-SQUIDs. The device is matched to the
50 Ω environment with a Klopfenstein-taper impedance transformer and achieves a bandwidth of 250-300 MHz, with input saturation powers up to -95 dBm at 20 dB gain. A 54-qubit Sycamore processor was used to benchmark these devices, providing a calibration for readout power, an estimate of amplifier added noise, and a platform for comparison against standard impedance matched parametric amplifiers with a single dc-SQUID. We find that the high power rf-SQUID array design has no adverse effect on system noise, readout fidelity, or qubit dephasing, and we estimate an upper bound on amplifier added noise at 1.6 times the quantum limit. Lastly, amplifiers with this design show no degradation in readout fidelity due to gain compression, which can occur in multi-tone multiplexed readout with traditional JPAs.

Characterizing low-frequency qubit noise

  1. Filip Wudarski,
  2. Yaxing Zhang,
  3. Alexander Korotkov,
  4. A. G. Petukhov,
  5. and M. I. Dykman
Fluctuations of the qubit frequencies are one of the major problems to overcome on the way to scalable quantum computers. Of particular importance are fluctuations with the correlation
time that exceeds the decoherence time due to decay and dephasing by fast processes. The statistics of the fluctuations can be characterized by measuring the correlators of the outcomes of periodically repeated Ramsey measurements. This work suggests a method that allows describing qubit dynamics during repeated measurements in the presence of evolving noise. It made it possible, in particular, to evaluate the two-time correlator for the noise from two-level systems and obtain two- and three-time correlators for a Gaussian noise. The explicit expressions for the correlators are compared with simulations. A significant difference of the three-time correlators for the noise from two-level systems and for a Gaussian noise is demonstrated. Strong broadening of the distribution of the outcomes of Ramsey measurements, with a possible fine structure, is found for the data acquisition time comparable to the noise correlation time.