Sunday, July 22

Quantum computing will tackle optimization and machine learning in finance first

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Quantum computing has the potential to solve difficult problems we can’t solve today, and in finance that could apply to activities like portfolio optimization and machine learning, said Alejandro Perdomo-Ortiz, senior research scientist at Rigetti, a full stack quantum computing company.

Speaking on QuantMindsTV, Perdomo-Ortiz said that “it’s a completely revolutionary and new technology based on a new physics” and will be “super exciting” for a lot of applications, including finance.

Of course, that depends on overcoming formidable challenges related to the technology and algorithm development, but a “limited quantum advantage” approach may be just around the corner within the next five years.

What he means by that is an actual demonstration of some of the problems that can be solved. At the same time, he noted that “there is a lot of momentum for funding”.

“There’s going to be a lot of communication with the with the real experts from the finance sector really identifying, okay, so what are the most difficult problems that you have and trying to see how can we match that with the quantum resources that we have,” he said.

Specific to the quantitative finance community, quantum computers are good at two domains of problems, one of which is portfolio optimization.

“If you have a certain desired risk in your portfolio, you want to be able to select the assets in such a way that you maximize the profit,” said Perdomo-Ortiz. “That is a huge value, in really finding an optimal solution.”

Without a quantum computing approach, the universe of possibilities can’t be explored because it would take as long as the age of the universe, he explained.

The other domain is one in which Perdomo-Ortiz is leading research: identifying how to adopt and speed up machine learning pipelines, using what he calls a “hybrid quantum-classical approach”.

As someone developing algorithms, what gets Perdomo Ortiz excited is finding out how to use the resources unique in these technologies to accelerate developments in the real world.

“It is now actually in the last decade or so that we’re starting to study what are they, how can we use those resources that we are tapping into,” he said.


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