3 years ago

Demonstration of Topological Data Analysis on a Quantum Processor.

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

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.

Publisher URL: http://arxiv.org/abs/1801.06316

DOI: arXiv:1801.06316v1

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