Preston Huft wins Wiki Science Photo Contest

Preston Huft, a graduate student in Mark Saffman’s group, was notified this week that he won the SmartElectron prize in the 2021 Wiki Science Photo Contest. Congratulations Preston!

An array of colored dots is shown.
Cesium atom array by Preston Huft. Fluorescence emitted by individual cesium-133 atoms, which have been laser cooled from a vapor in a vacuum chamber and confined in a grid of 1225 optical traps formed by laser light.

Eom receives Vannevar Bush faculty fellowship to study new class of thin films

WQI member and materials science and engineering professor Chang-Beom Eom has received a 2020 Vannevar Bush faculty fellowship from the Department of Defense. He’ll use the $3 million in funding to investigate “a new family of quantum materials.” 

Read the full story.

Mark Eriksson earns WARF named professorship

Mark Eriksson has been named the John Bardeen Professor of Physics, through the Wisconsin Alumni Research Foundation (WARF) named professorship program.

The WARF named professorship program provides recognition for distinguished research contributions of the UW–Madison faculty. The awards are intended to honor those faculty who have made major contributions to the advancement of knowledge, primarily through their research endeavors, but also as a result of their teaching and service activities.

To learn more about Eriksson’s research, and why he chose fellow UW–Madison alum John Bardeen as the namesake for his professorship, please read the original story.

 

WQI researchers part of team awarded DARPA grant to apply quantum computers to real-world problems

Wisconsin Quantum Institute director Mark Saffman and his research group are part of a team that will attempt to make quantum computing hardware more applicable to real-world problems.

The up to $7.4 million Defense Advanced Research Projects Agency (DARPA) funding is through the ONISQ program — Optimization with Noisy Intermediate-Scale Quantum devices. ColdQuanta is the primary recipient of the funding, and Saffman’s group at the University of Wisconsin–Madison, along with a national lab and other universities, are partners.

“We’re in this era of development of quantum computing hardware that has been termed NISQ, and that’s because we don’t have error correction running on our quantum hardware,” says Saffman, who is also a UW–Madison professor of physics and chief scientist for quantum information at ColdQuanta. “The question is, can we do anything useful with this? Because the outlook for having a real error-corrected quantum computer that you could run very long calculations still seems to be a long way away, but we have these NISQ machines today, and they’re getting better all the time.”

Mark Saffman standing in his lab
Mark Saffman

Saffman’s lab specializes in the development of one type of quantum computer known as a neutral atom quantum computer, in which individual atoms can serve as qubits, or quantum bits. The ONISQ program is looking to apply NISQ-era hardware to complex optimization problems that would be too difficult or time-consuming for a classical computer to solve. In this case, Saffman’s group is taking on a combinatorial optimization problem, known as Max-Cut.

“Very briefly, the problem is, if I gave you a graph with a bunch of locations in the graph that are connected by lines, and I wanted to divide the graph into two sets of locations such that there’s the maximum possible number of connections between locations in one group and locations in the other group,” Saffman explains. “It sounds like a totally abstract mathematician’s problem, but it turns out there are all kinds of practical applications, including logistics deployment, self-organized pattern recognition, scheduling problems — it actually comes up in a lot of everyday things.”

The project is divided into two phases, and the team needs to reach benchmarks in phase one, set by DARPA, in order to continue into the second phase. The most important metric, Saffman says, is one that takes into account the number of qubits on the processor (N) and the number of iterations that underlie how the computed algorithm works (P), or N x P.

“We’re going to be solving this Max-Cut problem using something called QAOA, quantum approximate optimization algorithm. The QAOA involves running a sequence of quantum gates, and so the metric for DARPA for phase one is to reach N times P equals 100, and N times P equals 10,000 for phase two,” Saffman says. “No one has specifically demonstrated N times P equals 100 to my knowledge, so it is an advance, but one that is within striking distance.”

Other partners in this grant include Raytheon Technologies, Argonne National Laboratory, University of Chicago, NIST Gaithersburg, University of Colorado Boulder, University of Innsbruck, and Tufts University.