@inproceedings{3c7186835cee40a19bf84bf45dadab47,
title = "Optimal dimensionality reduced quantum walk and noise characterization",
abstract = "In a recent work by Novo et al. (Sci. Rep. 5, 13304, 2015), the invariant subspace method was applied to the study of continuous-time quantum walk (CTQW). In this work, we adopt the aforementioned method to investigate the optimality of a perturbed quantum walk search of a marked element in a noisy environment on various graphs. We formulate the necessary condition of the noise distribution in the system such that the invariant subspace method remains effective and efficient. Based on the noise, we further formulate how to set the appropriate coupling factor to preserve the optimality of the quantum walker. Thus, a quantum walker based on an N by N Hamiltonian can be efficiently implemented using the near-term quantum technology.",
keywords = "Dimensionality reduction, Graph, Optimization, Quantum walk",
author = "Chiang, \{Chen Fu\}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; Future Technologies Conference, FTC 2018 ; Conference date: 15-11-2018 Through 16-11-2018",
year = "2019",
doi = "10.1007/978-3-030-02686-8\_68",
language = "English",
isbn = "9783030026851",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "914--929",
editor = "Rahul Bhatia and Kohei Arai and Supriya Kapoor",
booktitle = "Proceedings of the Future Technologies Conference (FTC) 2018 - Volume 1",
}