WATERLOO - What are the chances that an administrative error in high school would set Anna Golubeva on the path to becoming a nationally recognized theoretical physicist at one of the world's leading research institutes?

Even the 29-year-old PhD candidate has a tough time figuring that one out.

"Probability is really hard to determine when you have to estimate a human's mistake," she said with a laugh.

During her senior year of high school, she was focusing on biology and chemistry when she was accidentally placed in the most advanced physics class in her school, rather than the introductory level she'd requested.

When the mistake was realized a few weeks later, Golubeva had already discovered her passion for the subject and stayed with it.

Now a researcher at the Perimeter Institute for Theoretical Physics in Waterloo, the German-born physicist was recently named the recipient of the Natural Sciences and Engineering Research Council of Canada (NSERC) Gilles Brassard Doctoral Prize for Interdisciplinary Research.

The prize was established in 2012 and is awarded annually to an outstanding recipient of an NSERC Vanier Canada Graduate Scholarship who best exemplifies interdisciplinary research. Golubeva is the first University of Waterloo researcher to win the award, which includes a $10,000 cash prize.

After high school she received her undergraduate degree in biophysics and a master's degree in physics at university in Frankfurt, Germany, before arriving at the Perimeter Institute in 2016 for the institute's one-year masters program.

She is currently working toward her PhD with Roger Melko, Canada research chair in computational many-body physics, as her adviser.

Golubeva said her research is focused on determining how to use quantum computing, artificial intelligence and machine learning to aid theoretical physicists in their computational work.

Currently, machine learning is primarily driven by private industry for commercial applications and there isn't much concern with the ways the underlying programming works - it just needs to work.

But for physicists like Golubeva, those underlying properties need to be understood to fully apply machine learning to their research. "We need to know what the reliability is of the result," she said.

Machine learning can be a powerful tool for physicists to tackle overwhelming data sets that could take thousands of years to process using traditional computing techniques, she said.

"We're looking at the interaction of particles and electrons . and the problem is we're dealing with a lot of particles and a lot of equations, so we would need something like 10,000 years of computing time," said Golubeva.

Machine learning has demonstrated it can solve large data sets in a fraction of the time, but that process needs to be fully understood before physicists and other researchers can make full use of it, she said.

"We hope once it is fully understood scientifically, that it will be useful for us to step beyond these limitations that we are facing."

She was awarded the research prize last week at Rideau Hall in Ottawa and had the opportunity to meet the 27 other NSERC prize winners and discuss her research with Prime Minister Justin Trudeau and Kirsty Duncan, Minister of Science and Sport.

In a release, Duncan said the 28 researchers recognized last week are "some of Canada's best and brightest," and "are exactly why Canada has a reputation for being a world-leader in science and discovery."

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jjackson@therecord.com

Twitter: @JamesDEJ