Mines alumni are using AI to overcome algorithm bottlenecks in quantum computing

As artificial intelligence was becoming mainstream with new tools and resources redirecting how we interact with information and process data, Sean Feeney MS ’23 and Scott Pollan MS ’23 saw an opportunity to use AI technology to advance another emerging area: quantum computing. 

Hardware for quantum computing was improving at the same time, putting the possibility of widespread quantum computing just around the corner. But first, software for quantum computing would also need to improve well beyond the current iterations that are manually developed and customized for a niche purpose. 

Feeney and Pollan’s AI-driven quantum computing company, Rigveda Inc., is looking forward to a near future where quantum computing is a mainstay in industries ranging from pharmaceutical companies to semiconductor manufacturing, and easy-to-deploy quantum algorithms drive the pioneering research discoveries of the future. 

“It became clear to me as ChatGPT and all of these AI tools started maturing that we could use some of them to accelerate how we build algorithms in quantum computing,” said Feeney, Rigveda’s chief technical officer. “Quantum hardware is maturing, and we think in the next five to 10 years, we’re going to have fully fault-tolerant quantum computers that can do really useful things. Now the race is on to find useful algorithms.” 

Rigveda’s solutions address a gap in quantum computing at the software level. In the current landscape, creating quantum algorithms requires teams of subject-matter experts working for months to handcraft an algorithm for a specific use-case in industry. Bringing a team together to customize an algorithm creates a time-intensive bottleneck in developing quantum algorithms. One-size-fits-all answers to this problem exist, but they’re “black box” algorithms: The AI works without showing how it works, making it difficult for users across industries to validate the results. Rigveda’s solution to quantum algorithms uses explainable AI, showing its work to users so they can understand why a quantum circuit isn’t working.

“The problem we’re trying to solve is the quantum architecture search problem, and it’s usually answered with a black-box solution that we can’t look into,” Feeney said. “We’re developing explainable AI architectures that help researchers open up this black box, in a way.” 

Feeney shared a core principle behind their company: Quantum computers simulate quantum physics well right now, but this can be extrapolated to simulating quantum chemistry, or quantum materials, or other industries. The possibilities are infinite, so long as researchers have a way to validate an algorithm for the problem they’re trying to solve. At the moment, though, there’s a months- or even years-long timeline for developing a useful, verifiable algorithm.

Rigveda is trying to lower the bar to entry for major research discoveries using quantum computing, said Pollan, Rigveda’s president and CEO.

“We’re very mission-driven on reducing the barrier to entry to this kind of science,” Pollan said. “Right now, it requires a master’s degree or PhD to develop a quantum algorithm, but we’d like to see people who aren’t quantum experts using this tool to dip their toes in the discovery environment.” 

“Instead of gatekeeping this, we are much more interested in having this out in the world being used,” he added. 

A few years ago, Pollan was a student in Mines’ one-of-a-kind Mineral and Energy Economics program, and Feeney was a student in the second cohort of Mines’ relatively new quantum engineering master’s program. The two met thanks to a faculty member’s introduction at a campus space designed to foster startups like Rigveda—the Beck Venture Center.

“The Beck Venture Center was instrumental in how Sean and I came together,” Pollan said. Todd McLean, former managing director of the Mines Venture Fund, introduced them. “Todd sat us down and said, ‘See if you two can find some synergy here.’ Now, Todd is on our board, and he’s been an incredible advisor to us over the last two and a half years as we try to solve one of the most pressing problems in science.”

Mines provided an environment like no other for starting their company. “I had another project I was already working on,” Pollan said. “But Sean and I had a lot of ideas, and we thought, what is a problem that only Colorado School of Mines graduates can solve? This problem is so technical, but that’s the kind of challenge we’re going after.”