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.
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