Quantum Machine Learning for Finance
- URL: http://arxiv.org/abs/2109.04298v1
- Date: Thu, 9 Sep 2021 14:20:10 GMT
- Title: Quantum Machine Learning for Finance
- Authors: Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, Alexander Buts,
Shouvanik Chakrabarti, Dylan Herman, Shaohan Hu, Andrew Jena, Pierre Minssen,
Pradeep Niroula, Arthur Rattew, Yue Sun, Romina Yalovetzky
- Abstract summary: Finance is estimated to be the first industry sector to benefit from Quantum Computing.
This review paper presents the state of the art of quantum algorithms for financial applications.
- Score: 52.97198108304122
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
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