Q-NEXT collaboration awarded National Quantum Initiative funding

Posted on August 26, 2020

The University of Wisconsin–Madison solidified its standing as a leader in the field of quantum information science when the U.S. Department of Energy (DOE) and the White House announced the Q-NEXT collaboration as a funded Quantum Information Science Research Center through the National Quantum Initiative Act. The five-year, $115 million collaboration was one of five Centers announced today.

Q-NEXT, a next-generation quantum science and engineering collaboration led by the DOE’s Argonne National Laboratory, brings together nearly 100 world-class researchers from three national laboratories, 10 universities including UW–Madison, and 10 leading U.S. technology companies to develop the science and technology to control and distribute quantum information.

“The main goals for Q-NEXT are first to deliver quantum interconnects — to find ways to quantum mechanically connect distant objects,” says Mark Eriksson, the John Bardeen Professor of Physics at UW–Madison and a Q-NEXT thrust lead. “And next, to establish a national resource to both develop and provide pristine materials for quantum science and technology.”

Mark Eriksson

Q-NEXT will focus on three core quantum technologies:

Communication for the transmission of quantum information across long distances using quantum repeaters, enabling the establishment of “unhackable” networks for information transfer
Sensors that achieve unprecedented sensitivities with transformational applications in physics, materials, and life sciences
Processing and utilizing “test beds” both for quantum simulators and future full-stack universal quantum computers with applications in quantum simulations, cryptanalysis, and logistics optimization.

Eriksson is leading the Materials and Integration thrust, one of six Q-NEXT focus areas that features researchers from across the collaboration. This thrust aims to: develop high-coherence materials, including for silicon and superconducting qubits, which is an essential component of preserving entanglement; develop a silicon-based optical quantum memory, which is important in developing a quantum repeater; and improve color-center quantum bits, which are used in both communication and sensing.

“One of the key goals in Materials and Integration is to not just improve the materials but also to improve how you integrate those materials together so that in the end, quantum devices maintain coherence and preserve entanglement,” Eriksson says. “The integration part of the name is really important. You may have a material that on its own is really good at preserving coherence, yet you only make something useful when you integrate materials together.”

Six other UW–Madison and Wisconsin Quantum Institute faculty members are Q-NEXT investigators: physics professors Victor Brar, Shimon Kolkowitz, Robert McDermott, and Mark Saffman, electrical and computer engineering professor Mikhail Kats, and chemistry professor Randall Goldsmith. UW–Madison researchers are involved in five of the six research thrusts.

“I’m excited about Q-NEXT because of the connections and collaborations it provides to national labs, other universities, and industry partners,” Eriksson says. “When you’re talking about research, it’s those connections that often lead to the breakthroughs.

The potential impacts of Q-NEXT research include the creation of a first-ever National Quantum Devices Database that will promote the development and fabrication of next generation quantum devices as well as the development of the components and systems that enable quantum communications across distances ranging from microns to kilometers.

“This funding helps ensure that the Q-NEXT collaboration will lead the way in future developments in quantum science and engineering,” says Steve Ackerman, UW–Madison vice chancellor for research and graduate education. “Q-NEXT is the epitome of the Wisconsin Idea as we work together to transfer new quantum technologies to the marketplace and support U.S. economic competitiveness in this growing field.”

infographic of all q-next partner national labs, universities, and industry — The Q-NEXT partners

New study expands types of physics, engineering problems that can be solved by quantum computers

Posted on August 25, 2020

A well-known quantum algorithm that is useful in studying and solving problems in quantum physics can be applied to problems in classical physics, according to a new study in the journal Physical Review A from University of Wisconsin–Madison assistant professor of physics Jeff Parker.

Quantum algorithms – a set of calculations that are run on a quantum computer as opposed to a classical computer – used for solving problems in physics have mainly focused on questions in quantum physics. The new applications include a range of problems common to physics and engineering, and expands on the types of questions that can be asked in those fields.

Jeff Parker

“The reason we like quantum computers is that we think there are quantum algorithms that can solve certain kinds of problems very efficiently in ways that classical computers cannot,” Parker says. “This paper presents a new idea for a type of problem that has not been addressed directly in the literature before, but it can be solved efficiently using these same quantum computer types of algorithms.”

The type of problem Parker was investigating is known as generalized eigenvalue problems, which broadly describe trying to find the fundamental frequencies or modes of a system. Solving them is crucial to understanding common physics and engineering questions, such as the stability of a bridge’s design or, more in line with Parker’s research interests, the stability and efficiency of nuclear fusion reactors.

As the system being studied becomes more and more complex — more components moving throughout three-dimensional space — so does the numerical matrix that describes the problem. A simple eigenvalue problem can be solved with a pencil and paper, but researchers have developed computer algorithms to tackle increasingly complex ones. With the supercomputers available today, more and more difficult physics problems are finding solutions.

“If you want to solve a three-dimensional problem, it can be very complex, with a very complicated geometry,” Parker says. “You can do a lot on today’s supercomputers, but there tends to be a limit. Quantum algorithms may be able to break that limit.”

The specific quantum algorithm that Parker studied in this paper, known as quantum phase estimation, had been previously applied to so-called standard eigenvalue problems. However, no one had shown that they could be applied to the generalized eigenvalue problems that are also common in physics. Generalized eigenvalue problems introduce a second matrix that ups the mathematical complexity.

Parker took the quantum algorithm and extended it to generalized eigenvalue problems. He then looked to see what types of matrices could be used in this problem. If the matrix is sparse — meaning, if most of the numerical components that make it up are zero — it means this problem could be solved efficiently on a quantum computer.

The study shows that quantum algorithms could be applied to classical physics problems, such as nuclear fusion mirror machines. | Credit: Cary Forest

“What I showed is that there are certain types of generalized eigenvalue problems that do lead to a sparse matrix and therefore could be efficiently solved on a quantum computer,” Parker says. “This type includes the very natural problems that often occur in physics and engineering, so this study provides motivation for applying these quantum algorithms more to generalized eigenvalue problems, because it hasn’t been a big focus so far.”

Parker emphasizes that quantum computers are in their infancy, and these classical physics problems are still best approached through classical computer algorithms.

“This study provides a step in showing that the application of a quantum algorithm to classical physics problems can be useful in the future, and the main advance here is it shows very clearly another type of problem to which quantum algorithms can be applied,” Parker says.

The study was completed in collaboration with Ilon Joseph at Lawrence Livermore National Laboratory. Funding support was provided by the U.S. Department of Energy to Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344 and U.S. DOE Office of Fusion Energy Sciences “Quantum Leap for Fusion Energy Sciences” (FWP SCW1680).

UW–Madison named member of new $25 million Midwest quantum science institute

Posted on July 21, 2020

As joint members of a Midwest quantum science collaboration, the University of Wisconsin–Madison, the University of Illinois at Urbana–Champaign and the University of Chicago have been named partners in a National Science Foundation Quantum Leap Challenge Institute, NSF announced Tuesday.

The five-year, $25 million NSF Quantum Leap Challenge Institute for Hybrid Quantum Architectures and Networks (HQAN) was one of three in this first round of NSF Quantum Leap funding and helps establish the region as a major hub of quantum science. HQAN’s principal investigator, Brian DeMarco, is a professor of physics at UIUC. UW–Madison professor of physics Mark Saffman and University of Chicago engineering professor Hannes Bernien are co-principal investigators.

“HQAN is very much a regional institute that will allow us to accelerate in directions in which we’ve already been headed and to start new collaborative projects between departments at UW–Madison as well as between us, the University of Illinois, and the University of Chicago.” says Saffman, who is also director of the Wisconsin Quantum Institute. “These flagship institutes are being established as part of the National Quantum Initiative Act that was funded by Congress, and it is a recognition of the strength of quantum information research at UW–Madison that we are among the first.”

Read the full story at https://news.wisc.edu/uw-madison-named-member-of-new-25-million-midwest-quantum-science-institute/