Partway through writing a research paper, a graduate student in the group of André Schleife, a professor of materials science and engineering, went back to rerun a few simulations on the quantum computer the team had used. It was gone. By the time they returned to it, IBM had retired that machine and replaced it with a newer, better one. Each generation of quantum hardware has different levels of "noise," random errors that make results vary from run to run, and the new machine behaved differently enough that the old results could not simply be extended. The team had to run everything again.
"On the timescale of a paper, of a research project, the quantum hardware itself has experienced changes," Schleife said. He is co-lead of the thrust on quantum-centric supercomputing at the IBM-Illinois Discovery Accelerator Institute (IIDAI). For a researcher who spent years on classical supercomputers like Blue Waters, where a new machine meant the same code running faster, that pace of development is new, and it is a big part of what makes the work exciting.
Exact quantum equations cannot be solved directly, so scientists rely on many approximations, each suited to a different kind of material. Schleife is the principal investigator on a project that uses one such approach, dynamical mean field theory, with IBM quantum computers. The method is designed for correlated materials, those with d and f electrons, which are hard to describe with classical methods like density functional theory. "By trying [the method] on a quantum computer, the idea is to see if we can get either more accurate solutions or solve more complicated problems we need, to describe these correlated materials," Schleife said.
Illinois and IBM recently renewed their partnership for another five years. Schleife said the biggest change is access to cutting-edge IBM machines with more qubits. "Having access to these machines and being able to ask such exciting questions — that is new in our community," he said.
"With quantum computers making progress, we now have machines with more qubits, more quantum power," Schleife said. "So IBM now wants to see how these more sophisticated, more recently developed computers can be used to solve problems." For Schleife, those are materials science problems. Colleagues are using the same machines to tackle problems in physics.
"Quantum researchers were more confined to simpler models," Schleife said. "Now, by working with IBM and their scientists, we can try out more complicated problems on the actual hardware."
IBM's investment in the partnership reaches students as well as researchers. The company wants to train the next generation of people who will use these machines, and this semester Schleife is bringing that effort into his own classroom.
For years, Schleife has taught a senior-level computational lab in materials science. This fall, he replaced one part of the course with a quantum computing module. Through IBM, the class gets free access to a small amount of time on the company's quantum machines, so students can also run quantum simulations on real hardware as part of their coursework.
The problem at the center of the module is simple to describe. Students place two protons a certain distance apart, calculate the total energy of that arrangement, then move them farther apart and closer together, point by point. The result is a potential energy surface, a quantity scientists can also measure in experiments. In past years, students solved this problem with density functional theory and molecular dynamics. This year they will solve it a third way, on a quantum computer, and compare the three sets of results.
"It's a real, applied problem that we can show them on a quantum computer," Schleife said.
The quantum portion of the module begins in October, and Schleife is excited to see how it goes. Most of his students came to the university without expecting quantum computers to be part of their education. To prepare them, he is adapting a learning module that IBM publishes online and adding more detailed quantum mechanics than materials science students usually see.
He knows the added material could be a challenge, but he is ready to try it. "Maybe that's my German skepticism," he said, "but we have to see if it works." For now, he describes himself as “carefully optimistic”.