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Fast Virtual Gate Extraction For Silicon Quantum Dot Devices

Shize Che, Seong W Oh, Haoyun Qin, Yuhao Liu, Anthony Sigillito, Gushu Li

Abstract

Silicon quantum dot devices stand as promising candidates for large-scale quantum computing due to their extended coherence times, compact size, and recent experimental demonstrations of sizable qubit arrays. Despite the great potential, controlling these arrays remains a significant challenge. This paper introduces a new virtual gate extraction method to quickly establish orthogonal control on the potentials for individual quantum dots. Leveraging insights from the device physics, the proposed approach significantly reduces the experimental overhead by focusing on crucial regions around charge state transition. Furthermore, by employing an efficient voltage sweeping method, we can efficiently pinpoint these charge state transition lines and filter out erroneous points. Experimental evaluation using real quantum dot chip datasets demonstrates a substantial 5.84x to 19.34x speedup over conventional methods, thereby showcasing promising prospects for accelerating the scaling of silicon spin qubit devices.

Fast Virtual Gate Extraction For Silicon Quantum Dot Devices

Abstract

Silicon quantum dot devices stand as promising candidates for large-scale quantum computing due to their extended coherence times, compact size, and recent experimental demonstrations of sizable qubit arrays. Despite the great potential, controlling these arrays remains a significant challenge. This paper introduces a new virtual gate extraction method to quickly establish orthogonal control on the potentials for individual quantum dots. Leveraging insights from the device physics, the proposed approach significantly reduces the experimental overhead by focusing on crucial regions around charge state transition. Furthermore, by employing an efficient voltage sweeping method, we can efficiently pinpoint these charge state transition lines and filter out erroneous points. Experimental evaluation using real quantum dot chip datasets demonstrates a substantial 5.84x to 19.34x speedup over conventional methods, thereby showcasing promising prospects for accelerating the scaling of silicon spin qubit devices.
Paper Structure (17 sections, 3 equations, 7 figures, 1 table, 3 algorithms)

This paper contains 17 sections, 3 equations, 7 figures, 1 table, 3 algorithms.

Table of Contents

  1. Introduction
  2. Background
  3. Quantum Dot
  4. Charge Stability Diagram
  5. Virtual Gate
  6. Previous Work
  7. Fast Virtual Gate Extraction
  8. Redundancy in Full CSD Data
  9. Locating Critical Region
  10. Searching in the Critical Region
  11. Gradient-Based Feature
  12. Search for Transition Lines
  13. Slope Extraction
  14. Preprocessing for Anchor Points
  15. Evaluation
  16. ...and 2 more sections

Figures (7)

  • Figure 1: (a) Top-view scanning electron microscopy of a qua-druple-dot device, (b) Lateral-view of the device's dot-side
  • Figure 2: Example charge stability diagram of a double quantum dot device
  • Figure 3: Virtual gate example
  • Figure 4: The highlighted area confines both transition lines. Points on the transition lines have a larger gradient in the positively tilted direction
  • Figure 5: (a) Row-major sweep, (b) Column-major sweep
  • ...and 2 more figures