Title
Improved Quantum Query Algorithms for Triangle Detection and Associativity Testing
Abstract
We show that the quantum query complexity of detecting if an -vertex graph contains a triangle is . This improves the previous best algorithm of Belovs (Proceedings of 44th symposium on theory of computing conference, pp 77–84, ) making queries. For the problem of determining if an operation is associative, we give an algorithm making queries, the first improvement to the trivial application of Grover search. Our algorithms are designed using the learning graph framework of Belovs. We give a family of algorithms for detecting constant-sized subgraphs, which can possibly be directed and colored. These algorithms are designed in a simple high-level language; our main theorem shows how this high-level language can be compiled as a learning graph and gives the resulting complexity. The key idea to our improvements is to allow more freedom in the parameters of the database kept by the algorithm.
Year
DOI
Venue
2017
10.1007/s00453-015-0084-9
Algorithmica
Keywords
Field
DocType
Quantum algorithms,Query complexity,Learning graphs,Triangle testing,Associativity testing
Discrete mathematics,Comparability graph,Combinatorics,Line graph,Bipartite graph,Algorithm,Implicit graph,Clique-width,Planar graph,Mathematics,Voltage graph,Complement graph
Journal
Volume
Issue
ISSN
77
2
0178-4617
Citations 
PageRank 
References 
7
0.45
12
Authors
3
Name
Order
Citations
PageRank
Troy Lee127628.96
Frédéric Magniez257044.33
Miklos Santha372892.42