%0 Journal Article
%A Qiang, Xiaogang
%A Wang, Yizhi
%A Xue, Shichuan
%A Ge, Renyou
%A Chen, Lifeng
%A Liu, Yingwen
%A Huang, Anqi
%A Fu, Xiang
%A Xu, Ping
%A Yi, Teng
%A Xu, Fufang
%A Deng, Mingtang
%A Wang, Jingbo B.
%A Meinecke, Jasmin D. A.
%A Matthews, Jonathan C. F.
%A Cai, Xinlun
%A Yang, Xuejun
%A Wu, Junjie
%T Implementing graph-theoretic quantum algorithms on a silicon photonic quantum walk processor
%D 2021
%R 10.1126/sciadv.abb8375
%J Science Advances
%P eabb8375
%V 7
%N 9
%X Applications of quantum walks can depend on the number, exchange symmetry and indistinguishability of the particles involved, and the underlying graph structures where they move. Here, we show that silicon photonics, by exploiting an entanglement-driven scheme, can realize quantum walks with full control over all these properties in one device. The device we realize implements entangled two-photon quantum walks on any five-vertex graph, with continuously tunable particle exchange symmetry and indistinguishability. We show how this simulates single-particle walks on larger graphs, with size and geometry controlled by tuning the properties of the composite quantum walkers. We apply the device to quantum walk algorithms for searching vertices in graphs and testing for graph isomorphisms. In doing so, we implement up to 100 sampled time steps of quantum walk evolution on each of 292 different graphs. This opens the way to large-scale, programmable quantum walk processors for classically intractable applications.
%U https://advances.sciencemag.org/content/advances/7/9/eabb8375.full.pdf