6533b851fe1ef96bd12aa1e8

RESEARCH PRODUCT

Learning-Graph-Based Quantum Algorithm for k-distinctness

Aleksandrs Belovs

subject

Average-case complexityQuantum PhysicsTheoretical computer scienceComputational complexity theoryWorst-case complexityGraph (abstract data type)FOS: Physical sciencesQuantum algorithmSimon's problemQuantum Physics (quant-ph)Time complexityMathematicsQuantum complexity theory

description

We present a quantum algorithm solving the $k$-distinctness problem in $O(n^{1-2^{k-2}/(2^k-1)})$ queries with a bounded error. This improves the previous $O(n^{k/(k+1)})$-query algorithm by Ambainis. The construction uses a modified learning graph approach. Compared to the recent paper by Belovs and Lee arXiv:1108.3022, the algorithm doesn't require any prior information on the input, and the complexity analysis is much simpler. Additionally, we introduce an $O(\sqrt{n}\alpha^{1/6})$ algorithm for the graph collision problem where $\alpha$ is the independence number of the graph.

https://dx.doi.org/10.48550/arxiv.1205.1534