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Symmetries, graph properties, and quantum speedups

Authors :
Ben-David, Shalev
Childs, Andrew M.
Gilyén, András
Kretschmer, William
Podder, Supartha
Wang, Daochen
Source :
Proceedings of the 61st IEEE Symposium on Foundations of Computer Science (FOCS 2020), pp. 649-660 (2020)
Publication Year :
2020

Abstract

Aaronson and Ambainis (2009) and Chailloux (2018) showed that fully symmetric (partial) functions do not admit exponential quantum query speedups. This raises a natural question: how symmetric must a function be before it cannot exhibit a large quantum speedup? In this work, we prove that hypergraph symmetries in the adjacency matrix model allow at most a polynomial separation between randomized and quantum query complexities. We also show that, remarkably, permutation groups constructed out of these symmetries are essentially the only permutation groups that prevent super-polynomial quantum speedups. We prove this by fully characterizing the primitive permutation groups that allow super-polynomial quantum speedups. In contrast, in the adjacency list model for bounded-degree graphs (where graph symmetry is manifested differently), we exhibit a property testing problem that shows an exponential quantum speedup. These results resolve open questions posed by Ambainis, Childs, and Liu (2010) and Montanaro and de Wolf (2013).<br />Comment: 46 pages. Subsumes arXiv:2001.09642 and arXiv:2001.10520; adds a characterization of permutation groups with speedup and an exponential speedup for adjacency-list graph property testing

Details

Database :
arXiv
Journal :
Proceedings of the 61st IEEE Symposium on Foundations of Computer Science (FOCS 2020), pp. 649-660 (2020)
Publication Type :
Report
Accession number :
edsarx.2006.12760
Document Type :
Working Paper
Full Text :
https://doi.org/10.1109/FOCS46700.2020.00066