Feb. 27 — University of Chicago computer scientists will lead a $10 million “expedition” into the burgeoning field of quantum computing, bringing applications of the nascent technology for computer science, physics, chemistry and other fields at least a decade closer to practical use.

Quantum computers harness the unique properties of quantum physics in machines that scientists hope will eventually perform complex calculations that are prohibitively slow or even impossible for today’s computers. In recent months, companies such as IBM, Intel and Google have unveiled new quantum computing prototypes approaching 50 quantum bits—or “qubits”—a new milestone in the race for machines capable of producing unprecedented discoveries.

Yet despite these advances, there remains a wide gap between the quantum designs currently in use and the algorithms necessary to make full use of their power. The new, multi-institutional Enabling Practical-Scale Quantum Computing project, funded by the National Science Foundation’s Expeditions in Computing program, will bridge this gap through the co-design of hardware and software that helps scientists realize the potential of quantum computing more rapidly. Expeditions are the largest single-project investments made by the NSF and represent the most visionary and high-impact research in computer science.

“We want to close the gap enough that we can do something promising with these machines,” said Fred Chong, the Seymour Goodman Professor in the Department of Computer Science at the University of Chicago and lead investigator on the project. “What we aim to do is to make quantum algorithms and machines meet, in a useful way, 10 or more years earlier than they would otherwise—five years from now instead of 15 years from now.”

Uniting experts in algorithms, software, computer architecture and education from UChicago, MIT, Princeton, Georgia Tech and the University of California, Santa Barbara, EPiQC will develop these elements in tandem to take full advantage of new quantum machines. The collaboration will also establish a community of academic and industry partners and create new educational programs for students from elementary school to graduate school, training the next generation of quantum computer scientists.

“Without a coordinated effort such as EPiQC, what’s going to happen is these computers will come out and no one will be able to program them, and they’ll need a much larger machine in order to do the computation that they want to do,” said Diana Franklin, director of computer science education at UChicago STEM Education and a research associate professor at UChicago. “It makes it so that practical quantum computers can be released so much earlier than they would be otherwise.”

Missing pieces in quantum computing

The promise of quantum computing lies in the ability of qubits to occupy a “superposition” of states, rather than the binary 1 or 0 of classical computing bits. Due to this difference, each additional qubit doubles the computing power of a machine, producing exponential gains that could eventually push quantum computers past the capabilities of today’s largest supercomputers. Scientists could then use these machines to run simulations and solve equations too complex for classical computers, leading to new discoveries in drug and material design, agriculture, cryptography and transportation optimization.

However, many of the algorithms designed thus far to exploit these quantum advantages require the use of much more powerful machines than will be available in the near future. Scientists also lack the software needed to adapt these algorithms for practical use on actual machines, as well as the infrastructure tools necessary for programming these new technologies.

“The big missing piece in quantum computing is what can we do with it that’s useful,” Chong said. “We want to think about it in very practical terms. What happens when you have a small number of devices, you can only run them for a short amount of time, and you have noise and errors—will the algorithms work then, and how can we change them to make them work better? And how can we change the machine to make the algorithms work better?”

The project’s education and outreach efforts will focus on exposing students of all ages to quantum concepts and principles, preparing them for the new approaches needed to program and use quantum computers. The collaboration also will engage partners from industry and other universities to form a consortium that can share research ideas and new tools as they are developed.

“EPiQC will play an essential role in researching efficient co-design of algorithms, software and devices, as well as creating tools to put quantum in front of a wider audience for even greater quantum programming creativity, and eventual breakthrough quantum applications,” said Jay Gambetta, manager of quantum information and computation at IBM Research. “EPiQC will also develop curricula to help train a much-needed workforce to drive quantum computing forward.”

The EPiQC project will leverage substantial investments by the University of Chicago in computer science, including a major faculty hiring initiative and new facilities for computer and data science. The project also will coordinate with UChicago STEM Education and the Chicago Quantum Exchange, a partnership of UChicago, Argonne National Laboratory and Fermi National Laboratory for advancing academic and industrial efforts in the science and engineering of quantum information. Additional UChicago faculty on the project include John Reppy, professor in the Department of Computer Science; and David Schuster, assistant professor in the Department of Physics.

“Part of what we want to do is not only produce tools and educate people and help the community grow, but also help people appreciate that there are some really important problems to be solved here, and inspire people to work on them,” Chong said. “It’s really one of our core missions to build a research community with enough critical mass to spur innovation and realize the potential of this incredibly promising computing technology.”

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Source: Rob Mitchum, University of Chicago