Quantum machine learning for finance

作     者：Pistoia, Marco Ahmad, Syed Farhan Ajagekar, Akshay Buts, Alexander Chakrabarti, Shouvanik Herman, Dylan Hu, Shaohan Jena, Andrew Minssen, Pierre Niroula, Pradeep Rattew, Arthur Sun, Yue Yalovetzky, Romina 

作者机构：Future Lab for Applied Research and Engineering JPMorgan Chase Bank N.A. United States 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2021年

核心收录：

主　　题：Finance 

摘      要：Quantum computers are expected to surpass the computational capabilities of classical computers during this decade, and achieve disruptive impact on numerous industry sectors, particularly finance. In fact, finance is estimated to be the first industry sector to benefit from Quantum Computing not only in the medium and long terms, but even in the short term. This review paper presents the state of the art of quantum algorithms for financial applications, with particular focus to those use cases that can be solved via Machine Learning. © 2021, CC BY.