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)
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Authors
- 1. Manish Kesarwani (IBM; Indian Institute of Science)
- 2. Jayant R. Haritsa (Indian Institute of Science)
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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