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Exploring Quantum Bootstrap Sampling for AQP Error Assessment: A Pilot Study

Quantum Physics 2025-08-26 v1 Statistics Theory Statistics Theory

Abstract

Error assessment for Approximate Query Processing (AQP) is a challenging problem. Bootstrap sampling can produce error assessment even when the population data distribution is unknown. However, bootstrap sampling needs to produce a large number of resamples with replacement, which is a computationally intensive procedure. In this paper, we introduce a quantum bootstrap sampling (QBS) framework to generate bootstrap samples on a quantum computer and produce an error assessment for AQP query estimations. The quantum circuit design is included in this framework.

Keywords

Cite

@article{arxiv.2508.17500,
  title  = {Exploring Quantum Bootstrap Sampling for AQP Error Assessment: A Pilot Study},
  author = {Feng Yu and Raya Jahan},
  journal= {arXiv preprint arXiv:2508.17500},
  year   = {2025}
}

Comments

Database and Expert Systems Applications 2025 Conference

R2 v1 2026-07-01T05:03:42.565Z