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QFusion: A Demonstration of Boundary-Aware Fusion Planning and Execution for Large-Scale QUBO Optimization

Summary: QFusion is a DBMS-inspired, cost-based framework that plans boundary-aware fusion of decomposed QUBOs on an actual quantum annealer. Its interactive demonstration covers join ordering, multiple-query optimization, and index selection, exposing decomposition–fusion tradeoffs. (summarized by gpt-5.6-luna on Aug 28 2026)

Paper ID
hc520688775fa743f
Venue
VLDB
Year
2026
Pagerank
4.9793485e-05
Overall Rank
11,017 | 25.93%
DOI
10.14778/3827998.3828132

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Authors

BibTeX Citation

@article{liu_vldb26,
        title = {{QFusion: A Demonstration of Boundary-Aware Fusion Planning and Execution for Large-Scale QUBO Optimization}},
        author = {Liu, Hanwen and Sabek, Ibrahim},
        journal = {PVLDB},
        series = {{VLDB} '26},
        volume = {19},
        number = {12},
        pages = {4826--4829},
        doi = {10.14778/3827998.3828132},
        url = {https://doi.org/10.14778/3827998.3828132},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,883 QDBO: A Real-time Quantum-augmented Database System Optimizer 2026 VLDB 4.9793485e-05
11,030 How Can Quantum Computing and Databases Meet "in Practice"? From Algorithms to Systems 2026 VLDB 4.9793485e-05
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Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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