Award from JPMorgan Chase supports quantum algorithms research

The work of CQT Principal Investigator Patrick Rebentrost has caught the attention of global financial institution JPMorgan Chase.

In 2023, Patrick received a grant from the company’s Applied Research division to support his research “into novel quantum algorithms specifically in the area of quantum optimization.”

One of Patrick’s interests is the potential impact of quantum computing for finance, a field which involves many heavy computations. He has for example worked on quantum algorithms for derivative pricing and portfolio optimisation.

“I expect applications of quantum computing in finance will come after hardware reaches a state we call ‘fault-tolerant’. This means that they are more far-term, but we can already get the insights now and then we know where to look later,” says Patrick.

In-house experts

JPMorgan Chase has in-house experts in quantum computing and communications within its Global Technology Applied Research department and branches out globally including a team based in Singapore. That global division extends its work through academic engagements, awarding grants to a handful of researchers around the world.

The team’s stated goals are “to design and conduct research across multiple frontier technologies and to inform and develop next-generation solutions for the firm’s clients and businesses.”

Marco Pistoia, Head of Global Technology Applied Research at JPMorgan Chase, proposed the Research Award to Patrick after the workshop on “Quantum Algorithms for Financial Applications” in September 2022 during the IEEE International Conference on Quantum Computing and Engineering (informally known as IEEE Quantum Week). At that event, Patrick presented a keynote talk titled “Quantum algorithms for American options and portfolio optimization.” The Research Award was conferred in 2023 in conjunction with the 2023/24 academic year.

Patrick plans further research with this Award in new quantum methods for optimisation problems such as hedging and making these methods more near-term quantum computing friendly.

The opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of JPMorgan Chase & Co. or its affiliates.