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Going beyond the exascale

Fermilab physicists explain how quantum computers could help physicists tackle questions even the most powerful computers cannot handle in Symmetry Magazine

Written by Emily Ayshford

After years of speculation, quantum computing is here—sort of. 

Physicists are beginning to consider how quantum computing could provide answers to the deepest questions in the field. But most aren’t getting caught up in the hype. Instead, they are taking what for them is a familiar tack—planning for a future that is still decades out, while making room for pivots, turns and potential breakthroughs along the way.

“When we’re working on building a new particle collider, that sort of project can take 40 years,” says Hank Lamm, an associate scientist at the US Department of Energy’s Fermi National Accelerator Laboratory. “This is on the same timeline. I hope to start seeing quantum computing provide big answers for particle physics before I die. But that doesn’t mean there isn’t interesting physics to do along the way.”  

Equations that overpower even supercomputers

Classical computers have been central to physics research for decades, and simulations that run on classical computers have guided many breakthroughs. Fermilab, for example, has used classical computing to simulate lattice quantum chromodynamics. Lattice QCD is a set of equations that describe the interactions of quarks and gluons via the strong force. 

Quantum computers have already proved useful in basic research.

Theorists developed lattice QCD in the 1970s. But applying its equations proved extremely difficult. “Even back in the 1980s, many people said that even if they had an exascale computer [a computer that can perform a billion billion calculations per second], they still couldn’t calculate lattice QCD,” Lamm says.

But that turned out not to be true.

Within the past 10 to 15 years, researchers have discovered the algorithms needed to make their calculations more manageable, while learning to understand theoretical errors and how to ameliorate them.

Read more in Symmetry