Exploring Quantum Bootstrap Sampling for AQP Error Assessment: A Pilot Study
arXiv:2508.17500 · doi:10.1007/978-3-032-02049-9_14
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.
Database and Expert Systems Applications 2025 Conference
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