Quantum advantage and lower bounds in parallel query complexity
Joseph Carolan, Amin Shiraz Gilani, Mahathi Vempati

TL;DR
This paper demonstrates that quantum parallel query complexity can significantly outperform classical methods, revealing new separations and bounds, and challenging previous assumptions about the limitations of quantum advantage in total boolean functions.
Contribution
It introduces novel techniques and constructions showing unbounded quantum advantage in parallel query models, including for total functions, and establishes new lower bounds.
Findings
Unbounded quantum advantage over randomized for a total function.
Quantum advantage can occur solely due to parallelism, even without sequential advantage.
Polynomial separation between 2-round quantum and randomized complexities.
Abstract
It is well known that quantum, randomized and deterministic (sequential) query complexities are polynomially related for total boolean functions. We find that significantly larger separations between the parallel generalizations of these measures are possible. In particular, (1) We employ the cheatsheet framework to obtain an unbounded parallel quantum query advantage over its randomized analogue for a total function, falsifying a conjecture of Jeffery et al. 2017 (arXiv:1309.6116). (2) We strengthen (1) by constructing a total function which exhibits an unbounded parallel quantum query advantage despite having no sequential advantage, suggesting that genuine quantum advantage could occur entirely due to parallelism. (3) We construct a total function that exhibits a polynomial separation between 2-round quantum and randomized query complexities, contrasting a result of Montanaro…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
