# Quantum computing for finance

**Authors:** Dylan Herman, Cody Googin, Xiaoyuan Liu, Yue Sun, Alexey Galda, Ilya Safro, Marco Pistoia, Yuri Alexeev  
**arXiv:** [2307.11230](https://arxiv.org/abs/2307.11230)  
**Date:** 2023-07-20  
**Summary page:** https://www.summarizepaper.com/en/paper/2307.11230v1/

## Key points

- Quantum computers are set to revolutionize various industries by surpassing classical computers in computational capabilities.
- The article titled "Quantum computing for finance" provides an overview of the current state of quantum computing in financial applications.
- The authors focus on three key areas: stochastic modeling, optimization, and machine learning, highlighting how quantum techniques can enhance these practices.
- The review is primarily aimed at physicists but also provides insights into classical techniques used in the financial industry.
- Quantum computing's unique properties such as superposition and entanglement can be leveraged to solve complex financial problems more efficiently.
- Physicists can help address challenges in advancing quantum computing for finance, including developing tailored algorithms and designing error-correction mechanisms.
- Collaboration between physicists and industry experts is crucial to unlocking the full potential of quantum computing in the financial sector.

## Summary

Quantum computers are poised to revolutionize various industries by surpassing the computational capabilities of classical computers. In this article titled "Quantum computing for finance," authors Dylan Herman, Cody Googin, Xiaoyuan Liu, Yue Sun, Alexey Galda, Ilya Safro, Marco Pistoia and Yuri Alexeev provide a comprehensive overview of the current state of quantum computing in financial applications. The authors focus on three key areas: stochastic modeling, optimization and machine learning; highlighting how quantum techniques can enhance these traditional financial practices. The review is primarily aimed at physicists but also provides insights into the classical techniques employed by the financial industry. The article delves into the potential advantages and limitations of quantum techniques in finance; leveraging quantum computing's unique properties such as superposition and entanglement to explore new avenues for solving complex financial problems more efficiently. Furthermore, the authors discuss the challenges that physicists could help address in advancing quantum computing for finance; including developing robust algorithms tailored to financial applications and designing error-correction mechanisms to mitigate noise-induced errors inherent in current quantum systems. Overall, this detailed summary highlights the transformative impact that quantum computing can have on the financial sector; underscoring the importance of collaboration between physicists and industry experts to unlock its full potential.