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A new spin on an old superconductor means that it can be an ideal spintronic material, too

Back in the 1980s, researchers discovered that a bismuthate oxide material was a rare type of superconductor that could operate at higher temperatures. Now, a team of engineers and physicists at the University of Wisconsin-Madison has found the material, “Ba(Pb,Bi)O3,” is unique in another way: It exhibits extremely high spin orbit torque, a property useful in the emerging field of spintronics.

The combination makes this and similar materials potentially important in developing the next generation of fast, efficient memory and computing devices.

The finding was an encouraging surprise to Chang Beom-Eom, a professor of materials science and engineering, and Mark Rzchowski, a professor of physics, both at UW-Madison. “We’re looking to expand the range of materials that can be used in spintronic applications,” says Rzchowski. “We had known from previous work these oxides have a lot of interesting properties, and so were investigating the spintronic characteristics. We weren’t anticipating such a large effect. The origins of this are not theoretically understood, but we can speculate about some interesting physical mechanisms.”

The paper was published Dec. 5, 2023, in the journal Nature Electronics.

In conventional electronics, positive and negative electric charges are used to flip millions or billions of tiny transistors on semiconductor chips or in memory devices. But in spintronics, magnetic fields, and interactions with other electrons, manipulate a fundamental property of electrons called the spin state, which records information. This is much faster, more energy-efficient and more powerful than current semiconductors and will advance the development of quantum computing and low-power devices.

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Featured image caption: Chang Beom-Eom, a professor of materials science and engineering, and Mark Rzchowski, a professor of physics, in the lab. Photo: Joel Hallberg.

Ben Woods 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. Research Associate Benjamin Woods and a team including Distinguished Scientist Mark Friesen, John Bardeen Prof. of Physics Mark Eriksson, Honorary Associate Robert Joynt, and Graduate Student Emily Joseph developed 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.

Victor Brar earns NSF CAREER award

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.

Victor Brar

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.

profile photo of Robert McDermott
Robert McDermott
profile photo of Vincent Liu
Vincent Liu

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.

four panels showing the new chip architecture. The two on the left just show the two computer chips, and then the top right panel shows them "sandwiched" on top of each other. The bottom right panel is a circuit diagram of the whole setup.
The quantum-classical multichip module (MCM). (a) A micrograph of the qubit chip. (b) A micrograph of the SFQ driver chip. (c) A photograph showing the assembled MCM stack; the qubit chip is outlined in red and the SFQ chip is outlined in blue. (d) The circuit diagram for one qubit-SFQ pair. | From Liu et al, PRX Quantum.

“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.

a photograph of a room with the lights off, but the bulk of the image is taken up by a large piece of complicated equipment with many different colored laser lights visible, illuminating the shape of the equipment
The glow of red and green lasers and an array of supporting electronics fill a UW–Madison lab where physicists study the behavior of cesium atoms cooled within a fraction of a degree of absolute zero. The atoms could be used to store information in quantum computing systems. | Jacob Scott
an oddly-shaded portrait of physicist Marie Curie, which can only be viewed when a light polarizer is held in front of the portrait
Like the radiation she studied, this portrait of physicist Marie Curie is invisible until revealed by the proper equipment — in this case, a polarizer, a filter that blocks all light waves except those oscillating in a certain direction. One polarizing filter on the back layer of the portrait organizes the light shining through to the viewer. That light passes through layers of colorless cellophane, which rotate the waves a little or a lot depending on the layer’s thickness. A second polarizing filter, held by the viewer, filters the light again, selecting light at the wavelengths that correspond to the intended colors of the portrait. The image above is as the portrait appears viewed through a polarizer. | Aedan Gardill PhD ’23
an array of red-glowing images on a dark black background
Each image in this collage is of an astronomical phenomenon known as a strong gravitational lens, in which the light from a galaxy or cluster of galaxies is curved by a massive object in the foreground. The light is distorted into bright arcs, exhibiting physics theorized by Albert Einstein. Strong gravitational lenses offer a way to study dark matter, difficult to detect but considered a crucial factor in the structure, evolution and fate of the cosmos. | Jimena González and Keith Bechtol

Jimena González wins 2023 OSG David Swanson Award

Early in her thesis research, Jimena González was waiting. A lot.

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.

a woman stands in front of a screen with a research slide on the screen, she faces the audience and is gesturing with her hands.
Jimena González presents an award lecture at the 2023 Throughput Computing Conference. (provided by Jimena González)

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.”

This summer, González was selected as one of two recipients of the OSG David Swanson Award.

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

profile photo of Stas Boldyrev
Stas Boldyrev

 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

three images of low-res input data, high-res ground truth data, and super-resolution output data as heatmaps. A top left graph panell shows the power spectrum of the data
Using machine learning techniques, Kangwook Lee and his collaborators are able to produce high-resolution images from low-resolution simulations. These types of techniques could help improve large scale models, like the Illustris Simulation, shown here. In this simulation, dark matter density is overlaid with the gas velocity field. Credit: Illustris Collaboration

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.

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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...

Read the full article at: https://engineering.wisc.edu/blog/choy-leads-team-awarded-national-science-foundation-quantum-sensing-challenge-grant/