arXiv Analytics

Sign in

arXiv:1801.06316 [quant-ph]AbstractReferencesReviewsResources

Demonstration of Topological Data Analysis on a Quantum Processor

He-Liang Huang, Xi-Lin Wang, Peter P. Rohde, Yi-Han Luo, You-Wei Zhao, Chang Liu, Li Li, Nai-Le Liu, Chao-Yang Lu, Jian-Wei Pan

Published 2018-01-19Version 1

Topological data analysis offers a robust way to extract useful information from noisy, unstructured data by identifying its underlying structure. Recently, an efficient quantum algorithm was proposed [Lloyd, Garnerone, Zanardi, Nat. Commun. 7, 10138 (2016)] for calculating Betti numbers of data points -- topological features that count the number of topological holes of various dimensions in a scatterplot. Here, we implement a proof-of-principle demonstration of this quantum algorithm by employing a six-photon quantum processor to successfully analyze the topological features of Betti numbers of a network including three data points, providing new insights into data analysis in the era of quantum computing.

Related articles: Most relevant | Search more
arXiv:1708.05753 [quant-ph] (Published 2017-08-18)
Quantum Annealing for Combinatorial Clustering
arXiv:0907.5552 [quant-ph] (Published 2009-07-31, updated 2009-11-24)
Demonstration of a neutral atom controlled-NOT quantum gate
L. Isenhower et al.
arXiv:quant-ph/0610094 (Published 2006-10-12, updated 2007-04-05)
Demonstration of optically modulated dispersion forces