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Locating Buggy Segments in Quantum Program Debugging

Naoto Sato, Ryota Katsube

TL;DR

The paper addresses locating buggy segments in quantum programs, where testing a segment requires executing preceding segments, making test cost depend on location. It identifies four characteristics of quantum program testing relevant to bug locating and introduces a bug-locating method built from cost-based binary search plus strategies: early determination, finalization, and looking back. Through simulations using chi-square tests on Z-basis measurements, the authors show the method reduces the total gate cost and often improves the success probability compared to naive approaches. The work provides practical guidance for efficient quantum debugging and discusses extensions to real hardware and broader measurement bases.

Abstract

When a bug is detected by testing a quantum program on a quantum computer, we want to determine its location to fix it. To locate the bug, the quantum program is divided into several segments, and each segment is tested. However, to prepare a quantum state that is input to a segment, it is necessary to execute all the segments ahead of that segment in a quantum computer. This means that the cost of testing each segment depends on its location. We can also locate a buggy segment only if it is confirmed that there are no bugs in all segments ahead of that buggy segment. Since a quantum program is tested statistically on the basis of measurement results, there is a tradeoff between testing accuracy and cost. Although these characteristics are unique to quantum programs and complicate locating bugs, they have not been investigated. We suggest for the first time that these characteristics should be considered to efficiently locate bugs. We are also the first to propose a bug-locating method that takes these characteristics into account. The results from experiments indicate that the bug-locating cost, represented as the number of executed quantum gates, can be reduced with the proposed method compared with naive methods.

Locating Buggy Segments in Quantum Program Debugging

TL;DR

The paper addresses locating buggy segments in quantum programs, where testing a segment requires executing preceding segments, making test cost depend on location. It identifies four characteristics of quantum program testing relevant to bug locating and introduces a bug-locating method built from cost-based binary search plus strategies: early determination, finalization, and looking back. Through simulations using chi-square tests on Z-basis measurements, the authors show the method reduces the total gate cost and often improves the success probability compared to naive approaches. The work provides practical guidance for efficient quantum debugging and discusses extensions to real hardware and broader measurement bases.

Abstract

When a bug is detected by testing a quantum program on a quantum computer, we want to determine its location to fix it. To locate the bug, the quantum program is divided into several segments, and each segment is tested. However, to prepare a quantum state that is input to a segment, it is necessary to execute all the segments ahead of that segment in a quantum computer. This means that the cost of testing each segment depends on its location. We can also locate a buggy segment only if it is confirmed that there are no bugs in all segments ahead of that buggy segment. Since a quantum program is tested statistically on the basis of measurement results, there is a tradeoff between testing accuracy and cost. Although these characteristics are unique to quantum programs and complicate locating bugs, they have not been investigated. We suggest for the first time that these characteristics should be considered to efficiently locate bugs. We are also the first to propose a bug-locating method that takes these characteristics into account. The results from experiments indicate that the bug-locating cost, represented as the number of executed quantum gates, can be reduced with the proposed method compared with naive methods.
Paper Structure (14 sections, 2 equations, 2 figures, 1 table)

This paper contains 14 sections, 2 equations, 2 figures, 1 table.

Table of Contents

  1. Introduction
  2. Background
  3. Quantum Program Testing
  4. Related Work
  5. Characteristics of Quantum Program Testing for Bug Locating
  6. Proposed Method
  7. Cost-based Binary Search
  8. Search Strategies
  9. Early Determination
  10. Finalization
  11. Looking Back
  12. Experiments
  13. Discussion
  14. Conclusion and Future Plans

Figures (2)

  • Figure 1: Quantum program divided into segments
  • Figure 2: Example of cost-based binary search tree