A survey on HHL algorithm: From theory to application in quantum machine learning |
| |
Affiliation: | 1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;2. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330032, China;3. Tencent Quantum Laboratory, Shenzhen 518000, China |
| |
Abstract: | The Harrow-Hassidim-Lloyd (HHL) algorithm is a method to solve the quantum linear system of equations that may be found at the core of various scientific applications and quantum machine learning models including the linear regression, support vector machines and recommender systems etc. After reviewing the necessary background on elementary quantum algorithms, we provide detailed account of how HHL is exploited in different quantum machine learning (QML) models, and how it provides the desired quantum speedup in all these models. At the end, we briefly discuss some of the remaining challenges ahead for HHL-based QML models and related methods. |
| |
Keywords: | Quantum computation HHL algorithm Quantum machine learning Quantum circuit |
本文献已被 ScienceDirect 等数据库收录! |
|