Research, teaching and outreach in Physics at UW–Madison
Mark Friesen and team named finalists in 2023 WARF Innovation Awards
Each fall the WARF Innovation Awards recognize some of the best inventions at UW–Madison. WARF receives hundreds of new invention disclosures each year. Of these disclosures, the WARF Innovation Award finalists are considered exceptional in the following criteria:
Has potential for high long-term impact
Presents an exciting solution to a known important problem
Could produce broad benefits for humankind
One of the six finalists comes from Physics. Distinguished Scientist Mark Friesen led a team that included John Bardeen Prof. of Physics Mark Eriksson, Honorary Associate Robert Joynt and Research Associate Benjamin Woods in the development of a quantum device that shows a significant increase in valley splitting, a key property needed for error-free quantum computing. The device features a novel structural composition that turns conventional wisdom on its head.
Two winners, selected from the six finalists, will be announced in WARF’s annual holiday greeting; sign up to receive the greeting here. Each of the two Innovation Award winners receive $10,000, split among UW inventors.
Kids embrace science at Hands-On Expo
Spread throughout the main floor of the Discovery Building, the event offered kids the opportunity to hold brains, make objects float with superconductivity and jump into an immersive Virtual Reality experience.
Congrats to associate professor Victor Brar on earning an NSF CAREER award! CAREER awards are NSF’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.
For this award, Brar will study the flow of electrons in 2D materials, or materials that are only around one atom thick. His group has already shown that when they applied a relatively old technique — scanning tunneling potentiometry, or STP — to 2D materials such as graphene, they could create unexpectedly high-contrast images, where they could track the movement of individual electrons when an electric current was applied. They found that electrons flow like a viscous fluid, a property that had been predicted but not observed directly.
“So now instead of applying electrical bias, we’ll apply a thermal bias, because we know things move from hot to cold, and then image how [electrons] move in that way,” Brar says. “Part of what’s driving this idea is that Professor Levchenko has predicted that if you image the way heat flows through a material, it should also behave hydrodynamically, like a liquid, rather than diffusive, which is how you might imagine it.”
One motivation for this research is to better understand the general flow of fluids, a problem that is often too complex for supercomputers to solve correctly. Because STP visualizes the fluid-like flow of electrons directly, Brar envisions this work as potentially providing a way of solving fluid mechanics problems by directly imaging flow, without the need of simulations, similar to what is done in wind tunnels.
“Also, there are these predicted phases of electrons that no one has observed before,” Brar says. “We want to be the first to observe them.”
In addition to an innovative research component, NSF proposals require that the research has broader societal impacts, such as working toward greater inclusion in STEM or increasing public understanding of science. Brar’s group is using haptic pens, devices that are commonly used in remote trainings for surgeons and in the gaming community because they give a gentle push back that mimics a realistic touch. By attaching the haptic pen to a scanning tunneling microscope (STM), people holding the pen can “feel” the individual atoms and surfaces that the STM is touching.
“We think materials science is one of those areas where feeling the forces that hold matter together may provide more intuitive than looking at equations,” Brar says. “We’re making virtual crystal lattices that you can touch with the haptic pen and feel how the atoms fix together, but we’re also making it so you can feel the different forces of the different atoms used.”
Brar plans to introduce the haptic pen and atom models into Physics 407 and develop a materials science module for the UW Alumni Association’s Grandparents University. And because the haptic pen relies almost entirely on touch, Brar plans to work with the Wisconsin Council of the Blind and Visually Impaired to improve access to materials science instruction for people with vision impairments.
“Sandwich” structure found to reduce errors caused by quasiparticles in superconducting qubits
Qubits are notoriously more prone to error than their classical counterparts. While superconducting quantum computers currently use on the order of 100 to 1000 qubits, an estimated one million qubits will be needed to track and correct errors in a quantum computer designed for real-world applications. At present, it is not known how to scale superconducting qubit circuits to this size.
In a new study published in PRX Quantum, UW–Madison physicists from Robert McDermott’s group developed and tested a new superconducting qubit architecture that is potentially more scalable than the current state of the art. Control of the qubits is achieved via “Single Flux Quantum” (SFQ) pulses that can be generated close to the qubit chip. They found that SFQ-based control fidelity improved ten-fold over their previous versions, providing a promising platform for scaling up the number of qubits in a quantum array.
The architecture involves a sandwich of two chips: one chip houses the qubits, while the other contains the SFQ control unit. The new approach suppresses the generation of quasiparticles, which are disruptions in the superconducting ground state that degrade qubit performance.
“This structure physically separates the two units, and quasiparticles on the SFQ chip cannot diffuse to the quantum chip and generate errors,” explains Chuan-Hong Liu, PhD ’23, a former UW–Madison physics graduate student and lead author of the study. “This design is totally new, and it greatly improves our gate fidelities.”
Liu and his colleagues assessed the fidelity of SFQ-based gates through randomized benchmarking. In this approach, the team established operating parameters to maximize the overall fidelity of complex control sequences. For instance, for a qubit that begins in the ground state, they performed long sequences incorporating many gates that should be equivalent to an identity operation; in the end, they measured the fraction of the population remaining in the ground state. A higher measured ground state population indicated higher gate fidelity.
Inevitably, there are residual errors, but the reduced quasiparticle poisoning was expected to lower the error rate and improve gate fidelities — and it did.
“Most of the gates had 99% fidelity,” Liu says. “That’s a one order of magnitude reduction in infidelity compared to the last generation.”
Importantly, they showed the stability of the SFQ-based gates over the course of a six-hour experimental run.
Later in the study, the researchers investigated the source of the remaining errors. They found that the SFQ unit was emitting photons with sufficient energy to create quasiparticles on the qubit chip. With the unique source of the error identified, Liu and his colleagues can develop ways to improve the design.
“We realized this quasiparticle generation is due to spurious antenna coupling between the SFQ units and the qubit units,” Liu says. “This is really interesting because we usually talk about qubits in the range of one to ten gigahertz, but this error is in the 100 to 1000 gigahertz range. This is an area people have never explored, and we provide a straightforward way to make improvements.”
This study is a collaboration between the National Institute of Standards and Technology, Syracuse University, Lawrence Livermore National Laboratory, and UW–Madison.
This work was funded in part by the National Science Foundation (DMR-1747426); the Wisconsin Alumni Research Foundation (WARF) Accelerator; Office of the Director of National Intelligence, Intelligence Advanced Research Projects Activity (IARPA-20001-D2022-2203120004); and the NIST Program on Scalable Superconducting Computing and the National Nuclear Security Administration Advanced Simulation and Computing Beyond Moore’s Law program (LLNL-ABS-795437).
Physics has three winners in the Cool Science Image contest!
The winners of the UW–Madison 13th annual Cool Science Image contest were announced, and Physics has three winners! Our winners include graduate student Jacob Scott, the graduate student-professor pairing of Jimena González and Keith Bechtol, and alum Aedan Gardill, PhD ’23. Their winning images are below.
A panel of experienced artists, scientists and science communicators chose 12 winning images based on the aesthetic, creative and scientific qualities that distinguished them from scores of entries. The winning entries showcase the research, innovation, scholarship and curiosity of the UW–Madison community through visual representations of socioeconomic strata, brain cells snuffed out in Parkinson’s disease, the tangle of technology required to equip a quantum computing lab and a bug-eyed frog that opened students’ eyes to the world.
The winning images go on display this week in an exhibit at the McPherson Eye Research Institute’s Mandelbaum and Albert Family Vision Gallery on the ninth floor of the Wisconsin Institutes for Medical Research, 111 Highland Ave. The exhibit, which runs through the end of 2023, opens with a public reception at the gallery Thursday, Sept. 28, from 4:30 to 6:30 p.m. The exhibit also includes historical images of UW science, in celebration of the 175th anniversary of the University of Wisconsin’s founding.
The Cool Science Image Contest recognizes the technical and creative skills required to capture and create images, videos and other media that reveal something about science or nature while also leaving an impression with their beauty or ability to induce wonder. The contest is sponsored by Madison’s Promega Corp., with additional support from UW–Madison’s Office of University Communications.
To better understand the nature of dark energy, she uses machine learning to search Dark Energy Survey cosmology data for evidence of strong gravitational lensing — where a heavy foreground galaxy bends the light of another galaxy, producing multiple images of it that can get so distorted that they appear as long arcs of light around the large galaxy in telescope images. She also focuses on finding very rare cases of strong gravitational lensing in which two galaxies are lensed by the same foreground galaxy, systems known as double-source-plane lenses.
First, she had to create simulations of the galaxy systems. Next, she used those simulations to train the machine learning model to identify the systems in the heaps and heaps of DES data. Lastly, she would apply the trained model to the real DES data. All told, she expected to find hundreds of “simple” strong gravitational lenses and only a few double-source-plane lenses out of 230 million images.
“But, for example, when I did the search the first time, I mostly only got spiral galaxies, so then I had to include spiral galaxies in my training,” says González, a physics graduate student in Keith Bechtol’s group.
The initial steps took around two weeks (hence the waiting) before she could even know what needed to be changed to better train the model. Once she had the model trained and would be ready to apply it to the entire dataset, she estimated it would take five to six years just to find the images of interest — and then she would finally be able to study the systems found.
Then, the email from the Open Science Grid (OSG) Consortium came. The OSG Consortium operates a fabric of distributed High Throughput Computing (dHTC) services, allowing users to take advantage of massive amounts of computing power. Researchers can apply to the OSG User School, an annual workshop for scientists who want to learn and use dHTC methods.
“[dHTC] is parallelizing things. It’s like if you had 500 exams to grade, you can distribute them among different people and it would take less time,” González says. “It sounded perfect for me.”
González applied and was accepted into the 2021 program, which was run virtually that year. At the OSG User School, she learned methods that would allow her to take advantage of dHTC and apply them to her work. Her multi-year processing time was cut down to mere days.
“Because it was so fast, there were many new things that I could implement in my research,” González says. “A lot of the methodology I implemented would not have been possible without OSG.”
David Swanson was a longtime champion of and contributor to OSG, who passed away in 2016. In his memory, the award is bestowed annually upon one or more former students of the OSG User School who have subsequently achieved significant dHTC-enabled research outcomes.
She accepted the award at the Throughput Computing 2023 conference, where she presented her research and discussed how she used her training from the OSG User School to successfully comb through the DES data and find the systems of interest.
“When I got the award, I didn’t know anything about [Swanson],” González says. “But once I attended this event, I heard so many people talking about him, and I understood why it was created. It is such an honor to receive this award in his name.”
Stas Boldyrev earns DOE funding to investigate turbulence in relativistic plasmas
This post was adapted from a U.S. Department of Energy announcement
The U.S. Department of Energy (DOE) announced August 23 that it is funding $9.96M to support research in basic plasma science and engineering as well as frontier plasma science experiments at several midscale DOE Collaborative Research Facilities (CRFs) across the nation. The funding will go to 20 universities — including to UW–Madison physics professor Stas Boldyrev — four private companies, and one national laboratory.
The funding will cover 30 awards aimed at supporting basic plasma science research as well as increasing research productivity and participation of U.S. researchers in the CRFs. The awards include three-year single investigator or small group projects as well as short-term, one-time seed funding projects.
“Basic and low temperature plasma science is an important area with many scientific and technological impacts,” said Jean Paul Allain, DOE Associate Director of Science for Fusion Energy Sciences. “The research funded under this FOA will enable the U.S research community to address many fundamental and technological science challenges helping to ensure continued American leadership in this critical field.”
Boldyrev’s award will investigate turbulence in relativistic plasmas, which is more poorly understood compared to its non-relativistic counterpart. Relativistic plasma turbulence exists in extremely hot and energetic natural systems, where plasma and/or particle flow rates approach the speed of light, and it is required to explain radiation spectra of space phenomena such as solar flares or galactic nuclei jets.
“This project intends to develop analytical, phenomenological, and numerical models of turbulent energy cascades, and describe how such turbulence interacts with magnetic fields,” Boldyrev says. “We will concentrate on universal statistical properties of relativistic turbulence, which makes the results applicable to various lab, space, and astronomy environments, where such turbulence is present.”
Vadim Roytershteyn of the Space Science Institute is a co-investigator.
Through machine learning maps, cosmic history comes into focus
By Jason Daley, UW–Madison College of Engineering
For millennia, humans have used optical telescopes, radio telescopes and space telescopes to get a better view of the heavens.
Today, however, one of the most powerful tools for understanding the cosmos is the computer chip: Cosmologists rely on processing power to analyze astronomical data and create detailed simulations of cosmic evolution, galaxy formation and other far-out phenomena. These powerful simulations are starting to answer fundamental questions of how the universe began, what it is made of and where it’s likely headed.
“It is extremely expensive to run these simulations and basically takes forever,” says Kangwook Lee, an assistant professor of electrical and computer engineering at the University of Wisconsin-Madison. “So they cannot run them for large-scale simulations or for high-resolution at that same time. There are a lot of issues coming from that.”
Instead, machine learning expert Lee and physics colleagues Moritz Münchmeyer and Gary Shiu are using emerging artificial intelligence techniques to speed up the process and get a clearer view of the cosmos.
Choy leads team awarded National Science Foundation Quantum Sensing Challenge Grant
The National Science Foundation has selected a proposal “Compact and robust quantum atomic sensors for timekeeping and inertial sensing” by an interdisciplinary team led by University of Wisconsin-Madison researchers for...
Ke Fang, Ellen Zweibel earn Simons Foundation funding to study electrodynamics in extreme environments
Much of what we understand about fundamental physics is based on experiments done in the convenient “lab” of earth. But our planet is just one location, with its own relatively mild electromagnetic field. Do forces and energies work the same on earth as they do in all corners of the universe?
“It’s never guaranteed, as we see many theories break down at extreme environments,” says University of Wisconsin–Madison physics professor Ke Fang. “For example, a neutron star offers a magnetic field that is trillions of times stronger than on the Earth, and magnetars offer a field that is hundreds of trillions of time stronger. They are natural places to test many fundamental physics theories.”
SCEECS has six main research questions, three centered on understanding electrodynamics in neutron stars and three centered in black holes. Each question pairs at least one senior-level investigator with an early-career co-investigator. Zweibel serves as the lead investigator on her black hole question, and she is paired with Richard Anantua at UT-San Antonio. Fang is co-investigator on a neutron star question, and she is paired with Anatoly Spitkovsky at Princeton.
The neutron star “labs” that Fang is using are amongst the most dense stars in the universe — as small as 10 kilometers in diameter and with densities a million billion times that of water. High energy particles streaming from neutron stars are detectable on Earth, but they tend to be significantly altered by the time they make it here.
“How do those particles survive, in the sense that these extreme energy particles would interact with the surrounding media and produce secondary particles, and how do these interactions play a role in converting what you see on Earth?” Fang’s research asks. “There are also several major questions revealed by recent observations, such as extended TeV gamma-ray halos around neutron stars that are completely new phenomena. We would like to go from first principle physics to understand these phenomena.”
Zweibel’s research will use the extreme environment of spinning black holes, where the electromagnetic field has recently been identified as a major factor in accretion flows, or the movement of gases into the dense center. Her question asks how these accretion flows contribute to magnetizing black holes to form relativistic jets, or powerful emissions of radiation and high-energy particles.
“Accretion disks, their magnetic fields, and their magnetized jets are found throughout the Universe. They play essential roles in star formation, in the evolution of double, or binary stars, and in many other astrophysical settings,” Zweibel says. “The magnetized accretion disks surrounding black holes are by far the most extreme, and test our theories to the limits. Remarkably, we can circle back to laboratory plasma experiments, including some right here at UW, to study magnetized disks and jets as well.”
SCEECS is housed at Stanford University and includes researchers from 14 other US and international universities. UW–Madison and Columbia University are the only universities that have more than one investigator in the collaboration. Most of the funding will be used to support investigators, postdoctoral fellows, and graduate students.
The collaboration plans to host an in-person kick-off in October at Stanford with regular virtual meetings throughout the year. Those meetings will be a place where everyone involved in the research, including students, postdocs, and faculty, can provide updates and seek feedback. Larger-scale collaborations such as this one are nothing new to physicists, but those groups are almost always made up of experimental physicists.
“It’s rare for theorists to be in a larger collaboration because we’re usually working alone or in a small group,” Fang says. “This program is exciting because it collects leading theorists in the field from many different institutions and provides a network for us to collaborate with each other.”
The Simons Foundation’s mission is to advance the frontiers of research in mathematics and the basic sciences. The Foundation makes grants in four areas, including Mathematics and Physical Sciences, through which this collaboration is supported.