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Estimating the Coherence of Noise in Quantum Control of a Solid-State Qubit

Guanru Feng, Joel J. Wallman, Brandon Buonacorsi, Franklin H. Cho, Daniel K. Park, Tao Xin, Dawei Lu, Jonathan Baugh, and Raymond Laflamme
Phys. Rev. Lett. 117, 260501 – Published 20 December 2016
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Abstract

To exploit a given physical system for quantum information processing, it is critical to understand the different types of noise affecting quantum control. Distinguishing coherent and incoherent errors is extremely useful as they can be reduced in different ways. Coherent errors are generally easier to reduce at the hardware level, e.g., by improving calibration, whereas some sources of incoherent errors, e.g., T2* processes, can be reduced by engineering robust pulses. In this work, we illustrate how purity benchmarking and randomized benchmarking can be used together to distinguish between coherent and incoherent errors and to quantify the reduction in both of them due to using optimal control pulses and accounting for the transfer function in an electron spin resonance system. We also prove that purity benchmarking provides bounds on the optimal fidelity and diamond norm that can be achieved by correcting the coherent errors through improving calibration.

  • Figure
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  • Received 30 March 2016

DOI:https://doi.org/10.1103/PhysRevLett.117.260501

© 2016 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

Guanru Feng1,2, Joel J. Wallman1,3, Brandon Buonacorsi1,2, Franklin H. Cho1,2, Daniel K. Park1,2,4, Tao Xin1,2,5, Dawei Lu1,2, Jonathan Baugh1,2,6,*, and Raymond Laflamme1,2,7,8,†

  • 1Institute for Quantum Computing, Waterloo, Ontario N2L 3G1, Canada
  • 2Department of Physics and Astronomy, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
  • 3Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
  • 4Natural Science Research Institute, Korea Advanced Institute of Science and Technology, Daejon 34141, South Korea
  • 5Department of Physics, Tsinghua University, Beijing 100084, China
  • 6Department of Chemistry, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
  • 7Perimeter Institute for Theoretical Physics, Waterloo, Ontario N2J 2W9, Canada
  • 8Canadian Institute for Advanced Research, Toronto, Ontario M5G 1Z8, Canada

  • *baugh@uwaterloo.ca
  • laflamme@iqc.ca

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Vol. 117, Iss. 26 — 23 December 2016

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  • Figure 1
    Figure 1

    Quantum circuits for (a) RB and (b) PB. The initial state ρi is σz and the measurements M are spin echo detection sequences for measuring σz for RB and σx,y,z for PB. R in (a) is the recovery gate that returns the state to ±σz. A total of 150 random sequences with Sj {I,X90,Y90} and Pj {I,X180} (and virtual z-axis rotations) are applied for each sequence length m for RB and PB. (c),(d) Spin echo detection sequences for measuring σz and σx,y, respectively. The π/2 and π pulses are 35 ns Gaussian pulses around the y axis, and τ=700ns represents a delay.

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  • Figure 2
    Figure 2

    Experimental (a) RB and (b) PB results. Each experimental data point of σz and P is an average over 150 random sequences of m Clifford gates where P is defined in Eq. (16), and the error bars indicate the standard error of the mean. The lines are least-squares fits to σz=B(12ε)m+Az and P=Bum1+A=B(12εin)2(m1)+A, respectively. Az are 0.0156±0.0005, 0.0009±0.0010, and 0.0004±0.0013, and A are 0.0004±0.0001, 0.0005±0.0001, and 0.0001±0.0001, for the three cases T=1, no SEL (green dashed line), T=Tmeas, no SEL (orange solid line), and T=Tmeas, SEL (purple dotted line), respectively. Az and A are estimated using Eq. (18). In (b), PA is plotted instead of P to show that PA has a slower decay than σz, indicating εin<ε. The ε and εin values are given in Table 1. Because of the limitation of the pulsed traveling wave tube amplifier, the largest m are 55 and 47 in the cases without and with SEL sequences, respectively. All m are chosen randomly and independently for RB and PB sequences.

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