Probing Environmental Spin Polarization with Superconducting Flux Qubits

  1. T. Lanting,
  2. M.H. Amin,
  3. C. Baron,
  4. M. Babcock,
  5. J. Boschee,
  6. S. Boixo,
  7. V. N. Smelyanskiy,
  8. M. Foygel,
  9. and A. G. Petukhov
We present measurements of the dynamics of a polarized magnetic environment coupled to the We present measurements of the dynamics of a polarized magnetic environment coupled to the
flux degree of freedom of rf-SQUID flux qubits. The qubits are used as both sources of polarizing field and detectors of the environmental polarization. We probe dynamics at timescales from 5\,μs to 5\,ms and at temperatures between 12.5 and 22 mK. The measured polarization versus temperature provides strong evidence for a phase transition at a temperature of 5.7±0.3 mK. Furthermore, the environmental polarization grows initially as t√, consistent with spin diffusion dynamics. However, spin diffusion model deviates from data at long timescales, suggesting that a different phenomenon is responsible for the low-frequency behavior. A simple 1/f model can fit the data at all time scales but it requires empirical low- and high-frequency cutoffs. We argue that these results are consistent with an environment comprised of random clusters of spins, with fast spin diffusion dynamics within the clusters and slow fluctuations of the total moments of the clusters.

Diabatic gates for frequency-tunable superconducting qubits

  1. R. Barends,
  2. C. M. Quintana,
  3. A. G. Petukhov,
  4. Yu Chen,
  5. D. Kafri,
  6. K. Kechedzhi,
  7. R. Collins,
  8. O. Naaman,
  9. S. Boixo,
  10. F. Arute,
  11. K. Arya,
  12. D. Buell,
  13. B. Burkett,
  14. Z. Chen,
  15. B. Chiaro,
  16. A. Dunsworth,
  17. B. Foxen,
  18. A. Fowler,
  19. C. Gidney,
  20. M. Giustina,
  21. R. Graff,
  22. T. Huang,
  23. E. Jeffrey,
  24. J. Kelly,
  25. P. V. Klimov,
  26. F. Kostritsa,
  27. D. Landhuis,
  28. E. Lucero,
  29. M. McEwen,
  30. A. Megrant,
  31. X. Mi,
  32. J. Mutus,
  33. M. Neeley,
  34. C. Neill,
  35. E. Ostby,
  36. P. Roushan,
  37. D. Sank,
  38. K. J. Satzinger,
  39. A. Vainsencher,
  40. T. White,
  41. J. Yao,
  42. P. Yeh,
  43. A. Zalcman,
  44. H. Neven,
  45. V. N. Smelyanskiy,
  46. and John M. Martinis
We demonstrate diabatic two-qubit gates with Pauli error rates down to 4.3(2)⋅10−3 in as fast as 18 ns using frequency-tunable superconducting qubits. This is achieved by synchronizing
the entangling parameters with minima in the leakage channel. The synchronization shows a landscape in gate parameter space that agrees with model predictions and facilitates robust tune-up. We test both iSWAP-like and CPHASE gates with cross-entropy benchmarking. The presented approach can be extended to multibody operations as well.

Fluctuations of Energy-Relaxation Times in Superconducting Qubits

  1. P. V. Klimov,
  2. J. Kelly,
  3. Z. Chen,
  4. M. Neeley,
  5. A. Megrant,
  6. B. Burkett,
  7. R. Barends,
  8. K. Arya,
  9. B. Chiaro,
  10. Yu Chen,
  11. A. Dunsworth,
  12. A. Fowler,
  13. B. Foxen,
  14. C. Gidney,
  15. M. Giustina,
  16. R. Graff,
  17. T. Huang,
  18. E. Jeffrey,
  19. Erik Lucero,
  20. J. Y. Mutus,
  21. O. Naaman,
  22. C. Neill,
  23. C. Quintana,
  24. P. Roushan,
  25. Daniel Sank,
  26. A. Vainsencher,
  27. J. Wenner,
  28. T. C. White,
  29. S. Boixo,
  30. R. Babbush,
  31. V. N. Smelyanskiy,
  32. H. Neven,
  33. and John M. Martinis
Superconducting qubits are an attractive platform for quantum computing since they have demonstrated high-fidelity quantum gates and extensibility to modest system sizes. Nonetheless,
an outstanding challenge is stabilizing their energy-relaxation times, which can fluctuate unpredictably in frequency and time. Here, we use qubits as spectral and temporal probes of individual two-level-system defects to provide direct evidence that they are responsible for the largest fluctuations. This research lays the foundation for stabilizing qubit performance through calibration, design, and fabrication.

A blueprint for demonstrating quantum supremacy with superconducting qubits

  1. C. Neill,
  2. P. Roushan,
  3. K. Kechedzhi,
  4. S. Boixo,
  5. S. V. Isakov,
  6. V. Smelyanskiy,
  7. R. Barends,
  8. B. Burkett,
  9. Y. Chen,
  10. Z. Chen,
  11. B. Chiaro,
  12. A. Dunsworth,
  13. A. Fowler,
  14. B. Foxen,
  15. R. Graff,
  16. E. Jeffrey,
  17. J. Kelly,
  18. E. Lucero,
  19. A. Megrant,
  20. J. Mutus,
  21. M. Neeley,
  22. C. Quintana,
  23. D. Sank,
  24. A. Vainsencher,
  25. J. Wenner,
  26. T. C. White,
  27. H. Neven,
  28. and J.M. Martinis
Fundamental questions in chemistry and physics may never be answered due to the exponential complexity of the underlying quantum phenomena. A desire to overcome this challenge has sparked
a new industry of quantum technologies with the promise that engineered quantum systems can address these hard problems. A key step towards demonstrating such a system will be performing a computation beyond the capabilities of any classical computer, achieving so-called quantum supremacy. Here, using 9 superconducting qubits, we demonstrate an immediate path towards quantum supremacy. By individually tuning the qubit parameters, we are able to generate thousands of unique Hamiltonian evolutions and probe the output probabilities. The measured probabilities obey a universal distribution, consistent with uniformly sampling the full Hilbert-space. As the number of qubits in the algorithm is varied, the system continues to explore the exponentially growing number of states. Combining these large datasets with techniques from machine learning allows us to construct a model which accurately predicts the measured probabilities. We demonstrate an application of these algorithms by systematically increasing the disorder and observing a transition from delocalized states to localized states. By extending these results to a system of 50 qubits, we hope to address scientific questions that are beyond the capabilities of any classical computer.

Entanglement in a quantum annealing processor

  1. T. Lanting,
  2. A.J. Przybysz,
  3. A. Yu. Smirnov,
  4. F.M. Spedalieri,
  5. M.H. Amin,
  6. A.J. Berkley,
  7. R. Harris,
  8. F. Altomare,
  9. S. Boixo,
  10. P. Bunyk,
  11. N. Dickson,
  12. C. Enderud,
  13. J.P. Hilton,
  14. E. Hoskinson,
  15. M.W. Johnson,
  16. E. Ladizinsky,
  17. N. Ladizinsky,
  18. R. Neufeld,
  19. T. Oh,
  20. I. Perminov,
  21. C. Rich,
  22. M.C. Thom,
  23. E. Tolkacheva,
  24. S. Uchaikin,
  25. A.B. Wilson,
  26. and G. Rose
Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable by classical approaches. One such algorithm, quantum annealing (QA), provides a promising
path to a practical quantum processor. We have built a series of scalable QA processors consisting of networks of manufactured interacting spins (qubits). Here, we use qubit tunneling spectroscopy to measure the energy eigenspectrum of two- and eight-qubit systems within one such processor, demonstrating quantum coherence in these systems. We present experimental evidence that, during a critical portion of QA, the qubits become entangled and that entanglement persists even as these systems reach equilibrium with a thermal environment. Our results provide an encouraging sign that QA is a viable technology for large-scale quantum computing.