Nature Paper Expands on Using Quantum Computing in Financial Services

By John Russell

January 18, 2024

Financial services (FS) has long been expected to be an earlier and heavy user of quantum computing. Now, a paper in Nature Review Physics provides an expansive resource for non-quantum experts in FS that lays groundwork for future applications.

The Chicago Quantum Exchange (CQE), which facilitated development of the paper, calls it “a one-stop resource on the use of quantum computers to accelerate solutions for the finance sector” and has posted a brief account on its web site. “The paper discusses challenges in three categories at the intersection of finance and computing: optimization, machine learning, and stochastic modeling.”

The team developing the paper included a diverse group of scientists from the US Department of Energy’s (DOE) Argonne National Laboratory, JPMorgan Chase, Fujitsu Research of America, Menten AI, the University of Chicago’s Pritzker School of Molecular Engineering, and the University of Delaware.

Marco Pistoia

“We got together as a group of researchers from different institutions to better understand the state of the art of quantum computing for financial applications,” said Marco Pistoia, head of Global Technology Applied Research at JPMorgan Chase. “We wanted this to be appreciated by a larger audience. Our paper can be the starting point for researchers to better understand the landscape and then dive deeper in the areas that they’re interested in.”

“The upside of quantum computing is absolutely humongous. We’re talking about a potential speedup of millions of times for solving certain problems,” said Yuri Alexeev, senior scientist, Argonne National Laboratory.

Here’s the abstract for the paper (Quantum computing for finance):

“Quantum computers are expected to surpass the computational capabilities of classical computers and have a transformative impact on numerous industry sectors. We present a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modelling, optimization and machine learning. This Review is aimed at physicists, so it outlines the classical techniques used by the financial industry and discusses the potential advantages and limitations of quantum techniques. Finally, we look at the challenges that physicists could help tackle.”

Key points in the paper include:

  • Quantum algorithms for stochastic modelling, optimization and machine learning are applicable to various financial problems.
  • Quantum Monte Carlo integration and gradient estimation can provide quadratic speedup over classical methods, but more work is required to reduce the amount of quantum resources for early fault-tolerant feasibility and achieving an actual speedup.
  • Financial optimization problems can be continuous (convex or non-convex), discrete or mixed, and thus quantum algorithms for these problems can be applied.
  • The advantages and challenges of quantum machine learning for classical problems are also apparent in finance.

As noted in the CQE article, “Convening different sectors in applying quantum technology solutions to industry challenges has been a major focus of the CQE’s work, including through The Bloch, a CQE-led coalition of academic, government, industry, and nonprofit partners that won Chicagoland a designation as a US Regional Technology and Innovation Hub for quantum technologies late last year. The Bloch (pronounced “block”), which is vying for up to $70 million in project funding through the second phase of the Tech Hubs program, will build capacity for quantum companies, create pathways for quantum jobs, and establish end-to-end quantum industry solutions, including in the finance sector.”

As the Nature Reviews Physics report makes clear, there is no shortage of finance challenges for quantum computers to tackle.

“We’ve heard many times that finance will benefit greatly from quantum computing,” Pistoia said. “All the work we examined confirms that quantum computing for finance is a vibrant field.”

(Note: Pistoia is an HPCwire 2023 Person to Watch, see article. Also, Tabor Communications, HPCwire’s parent organization, holds an annual HPC-and-AI on Wall St Conference in the fall which also spotlights quantum’s potential in FS. At the conference two years ago, Pistoia provided an excellent overview of quantum computing progress and power, see HPCwire article, JPMorgan Chase Bets Big on Quantum Computing.)

The research for the paper was facilitated by CQE, “an intellectual hub that brings together academia, government, and industry to advance quantum research, train the future quantum workforce, and drive the quantum economy. Argonne and UChicago are founding members of the CQE, which is also anchored by DOE’s Fermi National Accelerator Laboratory, the University of Illinois Urbana-Champaign, the University of Wisconsin­–Madison, and Northwestern University. JPMorgan Chase is a CQE corporate partner.”

Link to Nature Review Physics, https://www.nature.com/articles/s42254-023-00603-1

Link to CQE article, https://chicagoquantum.org/news/university-government-and-industry-researchers-join-forces-explore-how-quantum-computing-could

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