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Index Advisors on Quantum Platforms

Summary: Hybrid quantum-classical index advisor: (1) model index selection as a QUBO solved by QAOA to produce higher-quality approximate configurations with O(log L) computations; (2) model exhaustive search solved by Grover using a novel phase-encoded oracle in standard gates achieving O(√L) queries. Qiskit-based simulation and hardware proofs show 1.5–2× quality gains over commercial greedy advisors, approach optimality, and have quantum resource requirements that scale linearly with problem size. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13757
Venue
VLDB
Year
2024
Pagerank
5.093636e-05
Overall Rank
11,277 | 22.63%
DOI
10.14778/3681954.3682025

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BibTeX Citation

@article{kesarwani_vldb24,
        title = {{Index Advisors on Quantum Platforms}},
        author = {Kesarwani, Manish and Haritsa, Jayant R.},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {11},
        pages = {3615--3628},
        doi = {10.14778/3681954.3682025},
        url = {https://doi.org/10.14778/3681954.3682025},
        year = {2024}
}

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