WQI Director and professor of physics, Mark Saffman, won a 2019 WARF Innovation Award.
Saffman has developed simplified optical hardware for quantum computing. His technology, recently licensed to ColdQuanta Inc., improves an apparatus for particle trapping, which will reduce the cost and complexity of next-generation quantum computing devices.
An independent panel of judges selected the Innovation Award winners from a field of six finalists drawn from among approximately 350 invention disclosures submitted to WARF over the past 12 months. The winning inventions each receive an award of $10,000, with the funds going to the UW–Madison inventors named on the breakthroughs.
The fellowship, awarded to early-career scientists from across the U.S., provides $875,000 of funding over five years. Kolkowitz will use the funds to develop his research program in ultra-precise atomic clocks, which he will use to investigate such fundamental aspects of physics as the relationship between quantum mechanics and gravity and the nature of dark matter.
Chicago Quantum Summit to gather international experts
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Top experts in quantum technology from around the globe — including experts from the Wisconsin Quantum Institute — will gather at the University of Chicago on Oct. 25 to discuss the future of quantum information science and strategies to build a quantum workforce.
The second annual Chicago Quantum Summit, hosted by the Chicago Quantum Exchange, will engage scientific and government leaders and the industries that will drive the applications of emerging quantum information science.
Response of a quantum disordered spin system to a local periodic drive
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A new publication from the Vavilov group, from A. Barış Özgüler, Canran Xu, is on arXiv! Read the full paper on the arXiv site.
WQI’s Wu awarded grant to advance quantum computing machine learning
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The US Department of Energy recently announced the funding of another set of quantum science-driven research proposals, including that of Sau Lan Wu, Enrico Fermi professor of physics and Vilas Professor at the University of Wisconsin–Madison. With the funding, Wu and her collaborators seek to tap into the power of quantum computing to analyze the wealth of data generated by high energy physics experiments.
The title of Wu’s DOE approved project is: “Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware”.
Wu, a member of the Chicago Quantum Exchange (CQE) and Wisconsin Quantum Institute at UW–Madison who conducts her research at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland, was one of only six university-based investigators – those outside of National Labs – to be awarded the DOE quantum funds for particle physicists.
“The ambitious HL-LHC program will require enormous computing resources in the next two decades,” says Wu. “A burning question is whether quantum computers can solve the ever-growing demand for computing resources, and our goal here is to explore and to demonstrate that quantum computing can be the new paradigm.”
Wu’s research program has one major goal: to discover new physics. This goal requires the identification of rare signals in immense backgrounds. Wu’s group has pioneered the use of machine learning algorithms on standard computers to move quickly and accurately to extract the physics signal. Sifting through the data to find meaningful and incredibly rare signals takes inordinate computing power at LHC.
“However, because of the rapidly increasing volume of data in the future HL- LHC program, our current machine learning algorithms just don’t have enough computing power to conduct complex analyses,” Wu says. “We believe that applying quantum machine learning methods may well be a new direction to go.”
For her DOE-funded project, Wu works with collaborators in quantum information science, including Miron Livny, professor of computer sciences with the Wisconsin Institute for Discovery at UW–Madison, and OpenLab of the CERN IT division. Importantly, she is also collaborating with scientists at IBM Zürich Research. Through them she has access to their quantum computer simulators and quantum computer hardware.
With IBM’s innovative quantum technologies, Wu and her team plan to overcome the challenges imposed by the large, complex datasets generated from the HL-LHC experiments. They will work on quantum feature map with entangling qubits – quantum bits used in quantum computers – to be able to encode the large datasets into the limited number of qubits. They will also work on improving quantum algorithms to advance machine learning, which they expect will lead to advances that have wide-ranging benefits outside of high energy physics.
“Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to high energy physics with IBM’s resources,” Wu says. “The US government, as well as US industrial counterparts, are planning to invest heavily in quantum computing in order to lead the international competition in the area of quantum information science technology, and we are excited to be able to apply these technologies to discoveries in high energy physics.”
Wu’s DOE grant marks the second to be earned by WQI members this summer. In July, Shimon Kolowitz and collaborators were awarded a grant to identify and mitigate the sources of noise that currently limit qubit performance.
American Family Insurance and UW–Madison: Queuing up quantum computing research
Aedan Gardill, pictured left, and Megan Tabbutt, both second-year students in the Kolkowitz group, will receive up to three years of funding to pursue their research projects. Below, Tabbutt and Gardill summarize their research projects.
Megan Tabbutt
Optical atomic clocks are now the most precise time keepers in the world, keeping time to better than one second over the age of the universe. With support from the NDSEG, I will work with my collaborators to build a new “multiplexed” strontium optical lattice atomic clock, which will consist of two clocks in one vacuum vessel. We will use this new kind of clock to perform tests of Einstein’s theory of relativity, such as measuring the relativistic effects of gravity on the passage of time at the millimeter scale, which may one day have applications ranging from the prediction of volcanic eruptions to water resource management and flood prevention. We will also engineer strong interactions between the atoms that make up the clock to generate entangled states for quantum enhanced clock performance, among other pursuits.
Aedan Gardill
Superconducting qubits are a promising system for quantum computing, but external sources of “noise” currently limit their usefulness. A better understanding of the sources of this noise in the qubits should help advance quantum computing efforts. With the NDSEG fellowship, my research will focus on using nitrogen vacancy centers in diamond as sensors with nanometer-scale resolution. We will develop and apply novel sensing techniques to study interesting solid state systems, such as investigating the origins of noise that currently limit superconducting qubit performance.
Progress in neutral atom quantum computing with a 2D array of qubits
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WQI Director Mark Saffman’s group recently published their manuscript, “Rydberg mediated entanglement in a two-dimensional neutral atom qubit array,” on arXiv.
The three-year, $4 million funding will allow the researchers to apply emerging tools to identify new materials and fabrication methods that can improve the performance of these systems.
“All of physics is quantum on some level, and quantum systems let you understand how physics works when you get to the cleanest, smallest, most isolated systems,” says Shimon Kolkowitz, assistant professor of physics at the University of Wisconsin–Madison and lead investigator of the grant. “We think that quantum computing, and quantum technologies more generally, are a really promising area of technological development and research.”
Quantum systems — which make use of single atoms or electrons and the quantum mechanical properties that govern them — have the potential to push boundaries in such areas as computing, precision sensing, and secure communications.
Quantum computers, for example, allow scientists to simulate quantum mechanics in ways that classical computers cannot. But, the computing power of quantum computers has not yet exceeded classical ones.
A scanning electron microscope image of a gate-defined double quantum dot qubit fabricated by the Eriksson group.
A limiting factor in quantum computing power is the number of qubits, or quantum bits, that can be strung together. Like bits in a classic computer, the more qubits in a quantum computer, the more the computing power. And the limiting factor in how many qubits can be connected with each other while remaining in the fragile quantum states required to perform a computation — called “coherence” in quantum lingo — is their resistance to external environmental factors, or “noise” that may cause them to “decohere.”
However, researchers have found that the materials used to make the qubits themselves generate a lot of this noise.
“People for quite a while have seen this noise, treated it as a fact of nature, and tried to design around it. But no one really knows what it is or how to get rid of it,” Kolkowitz says. “Even more fundamentally than just understanding or reducing this noise, we think that if you can reduce or ultimately eliminate this noise, it actually opens up the design space for the kinds of qubits you can build, and that will make it much easier to wire qubits together.”
With the DOE funding, Kolkowitz, along with colleagues at WQI and the Livermore National Laboratory, seeks to first identify the nature of the noise and how specific materials contribute to it, and then to develop ways to reduce it.
Atom-size quantum defects in a diamond, imaged using a confocal microscope in the Kolkowitz lab.
Work in Kolkowitz’s group, as well as that of Victor Brar, assistant professor of physics and co-investigator on the grant, has led to the development of quantum sensors that allow the researchers to characterize things like magnetic fields at the nanometer scale, or to see how single atoms are arranged in various materials. Part of the DOE funding will be used to continue improving these sensors.
Kolkowitz and Brar then want to use their sensors to identify the noise affecting qubits designed by UW quantum computing researchers Mark Eriksson and Robert McDermott.
“And then we can work in a feedback loop, where, for example, Robert McDermott makes samples and characterizes their performance, then we study the noise limiting that performance with these quantum and nanoscale probes to figure out what’s happening on the microscopic scale,” Kolkowitz says. “Then, we give that information to our theory collaborators here and at Livermore who build models and simulations based on what we’ve measured. And then Robert can use what we’ve learned to design and make new samples to see if we’ve improved on these issues.”
An image taken with a scanning tunneling microscope of a single atomic defect in graphene
Trying to identify sources of this noise is nothing new, but what Kolkowitz finds most promising about the work funded through this grant is the development and application of new sensing technologies.
“These emerging tools that use quantum states and quantum systems themselves should give us access to the origins and behavior of noise in quantum platforms on scales that haven’t been accessible before,” Kolkowitz says.
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