Mark Saffman part of team awarded in latest round of Research Forward funding

This story was originally published by the OVCR

The Office of the Vice Chancellor for Research (OVCR) hosts the Research Forward initiative to stimulate and support highly innovative and groundbreaking research at the University of Wisconsin–Madison. The initiative is supported by the Wisconsin Alumni Research Foundation (WARF) and will provide funding for 1–2 years, depending on the needs and scope of the project.

Research Forward seeks to support collaborative, multidisciplinary, multi-investigator research projects that are high-risk, high-impact, and transformative. It seeks to fund research projects that have the potential to fundamentally transform a field of study as well as projects that require significant development prior to the submission of applications for external funding. Collaborative research proposals are welcome from within any of the four divisions (Arts & Humanities, Biological Sciences, Physical Sciences, Social Sciences), as are cross-divisional collaborations.

Physics professor Mark Saffman is part of a team awarded funding in Round 4 of the Research Forward competition for their project:

Quanta sensing for next generation quantum computing

Future quantum computers could open new scientific and engineering frontiers, impacting existential challenges like climate change. However, quantum information is delicate; it leaks with time and is prone to significant errors. These errors are exacerbated by imperfect reading and writing of quantum bits (qubits). These challenges fundamentally limit our ability to run quantum programs, and could hold back this powerful technology. Fast and accurate qubit readout, therefore, is essential for unlocking the quantum advantage. Current quantum computers use conventional cameras for reading qubits, which are inherently slow and noisy.

This research project will use quanta (single-photon) sensors for fast and accurate qubit readout. Quanta sensors detect individual photons scattered from qubits, thus enabling sensing qubits at 2-3 orders of magnitude higher speeds (few microseconds from ~10 milliseconds), thereby transforming the capabilities (speed, accuracy) of future quantum computers, and for the first time, paving the way for scalable and practical quantum computing.

Principal investigator: Mohit Gupta, associate professor of computer sciences

Co-PIs: Mark Saffman, professor of physics; Swamit Tannu, assistant professor of computer sciences; Andreas Velten, associate professor of biostatistics and medical informatics, electrical and computer engineering

Entangled neutrinos may lead to heavier element formation

Elements are the building blocks of every chemical in the universe, but how and where the different elements formed is not entirely understood. A new paper in The Astrophysical Journal by University of Wisconsin–Madison physics professor Baha Balantekin and colleagues with the Network for Neutrinos, Nuclear Astrophysics, and Symmetries (N3AS) Physics Frontier Center, shows how entangled neutrinos could be required for the formation of elements above approximately atomic number 140 via neutron capture in an intermediate-rate process, or i-process.

Profile photo of Baha Balantekin
Baha Balantekin

Why it’s important

“Where the chemical elements are made is not clear, and we do not know all the possible ways they can be made,” Balantekin says. “We believe that some are made in supernovae explosions or neutron star mergers, and many of these objects are governed by the laws of quantum mechanics, so then you can use the stars to explore aspects of quantum mechanics.”

What is already known?

  • Immediately after the Big Bang, lighter elements like hydrogen and helium were abundant. Heavier elements, up to iron (atomic number 26) continued to form through nuclear fusion in the centers of hot stars.
  • Above iron, fusion is no longer energetically favorable, and nuclear synthesis occurs via neutron capture, where neutrons glom onto atomic nuclei. At high enough concentrations, neutrons can convert into protons, increasing the atomic number of the element by one.
  • This conversion is dependent on neutrinos and antineutrinos. Neutron capture has been found to occur slowly (s-process, over years) and rapidly (r-process, within minutes); an intermediate timescale, or i-process has been proposed but little evidence exists to support it. Rapid or intermediate neutron capture can only take place in catastrophic events where a huge amount of energy is released, such as supernova collapse.
  • “When a supernova collapse occurs, you start with a big star, which is gravitationally bound, and that binding has energy,” Balantekin says. “When it collapses, that energy has to be released, and it turns out that energy is released in neutrinos.”
  • The laws of quantum mechanics state that those neutrinos can become entangled because they interact in the collapsing supernova. Entanglement is when any two or more particles interacted and then “remember” the others, no matter how far apart they might be.

A quick summary of the research

  • “One question we can ask is if these neutrinos are entangled with each other or not,” Balantekin says. “This paper shows that if the neutrinos are entangled, then there is an enhanced new process of element production, the i-process.”
a plot of mass number A (atomic number) on the x-axis and abundance as a log scale on the y-axis. a purple line shows the i-process abundance, black line shows r-process, and grey line shows s-process. Above atomic number 140 or so, there is a visible enhancement of the purple line over the other two lines (below 140 the black and grey lines are much higher abundance values than the purple line)
The abundance pattern based on calculations in this paper (ν i-process pattern; purple line), compared with the solar system s-process (gray line) and r-process (black line) abundance data (Sneden et al. 2008). The ν i abundance for A = 143 is scaled to the solar r-process data for pattern comparison. | Source: The Astrophysical Journal

The experimental and simulated evidence

  • The researchers used two known facts to set up their calculations: well-established rates of neutron capture, and catalogs of the atomic spectra of stars, which astronomers have collected over decades to identify the abundance of different elements. They also knew that a supernova collapse produces on the order of 10^58 neutrinos, a number that is far too large to use in any standard calculations.
  • Instead, they made simulations of up to eight neutrinos and calculated the abundance of elements that would be created via neutron capture if the neutrinos were entangled, or were not entangled.
  • “We have a system of, say, three neutrinos and three antineutrinos together in a region where there are protons and neutrons and see if that changes anything about element formation,” Balantekin says. “We calculate the abundances of elements that are produced in the star, and you see that the entangled or not entangled cases give you different abundances.”
  • The simulations showed that elements with atomic number greater than 140 are likely to be enhanced by i-process neutron capture — but only if the neutrinos are entangled.

Caveats and future work

  • Balantekin points out that these simulations are just “hints” based on astronomical observations. Astrophysics research requires using the cosmos as a lab, and it is difficult to conduct true experimental tests on earth.
  • “There’s something called the standard model of particle physics, which determines the interaction of particles. The neutrino-neutrino interaction is one aspect of the standard model which has not been tested in the lab, it can only be tested in astrophysical extremes,” Balantekin says. “But other aspects of the standard model have been tested in the lab, so one believes that it should all work.”
  • The researchers are currently using more astrophysical data of element abundance in extreme environments to see if those abundances continue to be explained by entangled neutrinos.

This research is supported in part by the National Science Foundation grants Nos. PHY-1630782 and PHY-2020275 (Network for Neutrinos, Nuclear Astrophysics and Symmetries). Balantekin is supported in part by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under Award No. DE-SC0019465 and in part by the National Science Foundation Grant PHY-2108339 at the University of Wisconsin-Madison. 

The paper’s co-authors include Michael Cervia, Amol Patwardhan, Rebecca Surman, and Xilu Wang, all current or former members of N3AS.

Welcome, Professor Tiancheng Song!

Photo of Tiancheng Song
Tiancheng Song

Tiancheng Song, a condensed matter experimentalist, joined the UW–Madison Physics Department as an assistant professor on May 20. His research interest lies in two-dimensional (2D) quantum materials with a focus on 2D magnetism, 2D superconductivity and 2D topology. He joins us from Princeton University where he was a Dicke Fellow and won the Lee Osheroff Richardson Science Prize. He completed his PhD at the University of Washington and his bachelor’s degree from University of Science and Technology in China. He is originally from Tianjin, China, the son of two theoretical physicists.

Please give an overview of your research.

I work on experimental condensed matter physics and am especially interested in a new family of materials called two-dimensional materials, which resemble “Quantum LEGOs” at the atomic scale. These 2D materials can be exfoliated down to the monolayer limit just using Scotch tape, and each monolayer can act like a LEGO piece. This provides us with a full LEGO set of quantum materials in two dimensions, covering a broad spectrum of emergent quantum phenomena. Within this new material platform of condensed matter physics, I’m particularly interested in three topics: magnetism, superconductivity and topology. With the new tuning knobs uniquely enabled in this new material system, we aim to study these three topics in two dimensions using those LEGOs. There will be a lot of fun because we can use them like building blocks, stack them together like LEGO toys, and uncover new physics emerging from the toys we create!

What are the first one or two research projects you’ll work on when your group is running here?

Overall, we plan to discover new 2D quantum materials, develop new measurement techniques and explore new physics in this emergent platform. We aim to combine state-of-the-art nanofabrication of 2D materials with various measurement techniques including magneto-optics, quantum transport, thermoelectrics, optoelectronics, optical spectroscopy and microscopy. Our research will explore three directions: 2D magnetism, 2D superconductivity and 2D topology.

What attracted you to Madison and the University?

The University of Wisconsin–Madison is a top public university located in a beautiful city. The Department of Physics is renowned for its exceptional research in many areas of physics. My partner also works at UW–Madison.

What is your favorite element and/or elementary particle?

I usually say Chromium or Tellurium, but this time I would say Technetium (symbol Tc and atomic number 43). This is because my name is Tiancheng, and when I was a kid, my parents called me TC just for fun. Since studying abroad, I have found my name sometimes difficult to pronounce and remember for others, because it is a bit long and complicated. So, I started using this nickname again, and I’m happy to be called TC!

What hobbies and interests do you have?

I enjoy many sports, such as badminton, tennis and swimming. For those other sports that I am not very skilled at, I enjoy watching rather than playing.

Bringing the Quantum to the Classical: A Hybrid Simulation of Supernova Neutrinos

By Daniel Heimsoth, Physics PhD student

Simulating quantum systems on classical computers is currently a near-impossible task, as memory and computation time requirements scale exponentially with the size of the system. Quantum computers promise to solve this scalability issue, but there is just one problem: they can’t reliably do that right now because of exorbitant amounts of noise. 

So when UW–Madison physics postdoc Pooja Siwach, former undergrad Katie Harrison BS ‘23, and professor Baha Balantekin wanted to simulate neutrino evolution inside a supernova, they needed to get creative.  

profile photo of Pooja Siwach
Pooja Siwach

Their focus was on a phenomenon called collective neutrino oscillations, which describes a peculiar type of interaction between neutrinos. Neutrinos are unique among elementary particles in that they change type, or flavor, as they propagate through space. These oscillations between flavors are dictated by the density of neutrinos and other matter in the medium, both of which change from the core to the outer layers of a supernova. Physicists are interested in how the flavor composition of neutrinos evolve in time; this is calculated using a time evolution simulation, one of the most popular calculations currently done on quantum computers.  

Ideally, researchers could calculate each interaction between every possible pair of neutrinos in the system. However, supernovae produce around 10^58 neutrinos, a literally astronomical number. “It’s really complex, it’s very hard to solve on classical computers,” Siwach says. “That’s why we are interested in quantum computing because quantum computers are a natural way to map such problems.” 

profile photo of Katie Harrison
Katie Harrison

This naturalness is due to the “two-level” similarities between quantum computers and neutrino flavors. Qubits are composed of two-level states, and neutrino flavor states are approximated as two levels in most physical systems including supernovae.  

In a paper published in Physical Review D in October, Siwach, Harrison, and Balantekin studied the collective oscillation problem using a quantum-assisted simulator, or QAS, which combines the benefits of the natural mapping of the system onto qubits and classical computers’ strength in solving matrix equations. 

In QAS, the interactions between particles are broken down into a linear combination of products of Pauli matrices, which are the building blocks for quantum computing operations, while the state itself is split into a sum of simpler states. The quantum portion of the problem then boils down to computing products of basis states with each Pauli term in the interaction. These products are then inputted into the oscillation equations.

a graph with 4 neutrino traces in 4 colors
Flavor composition (y-axis) of four supernova neutrinos over time due to collective oscillations, calculated using the quantum-assisted simulator. The change in flavor for each neutrino over time shows the effect of neutrino-neutrino interactions.

“Then we get the linear-algebraic equations to solve, and solving such equations on a quantum computer requires a lot of resources,” explains Siwach. “That part we do on classical computers.”  

This approach allows researchers to use the quantum computers only once before the actual time evolution simulation is done on a classical computer, avoiding common pitfalls in quantum calculations such as error accumulation over the length of the simulation due to noisy gates. The authors showed that the QAS results for a four-neutrino system match with a pure classical calculation, showcasing the power of this approach, especially compared to a purely quantum simulation which quickly deviates from the exact solution due to accumulated errors from gates controlling two qubits at the same time. 

Still, as with any current application of quantum computers, there are limitations. “There’s only so much information that we can compute in a reasonable amount of time [on quantum computers],” says Siwach. She also laments the scalability of both the QAS and full quantum simulation. “One more hurdle is scaling to a larger number of neutrinos. If we scale to five or six neutrinos, it will require more qubits and more time, because we have to reduce the time step as well.” 

Harrison, who was an undergraduate physics student at UW–Madison during this project, was supported by a fellowship from the Open Quantum Initiative, a new program to expand undergrad research experiences in quantum computing and quantum information science. She enjoyed her time in the program and thinks that it benefits students looking to get involved in research in the field: “I think it’s really good for students to see what it really means to do research and to see if it’s something that you’re capable of doing or something that you’re interested in.” 

trace of neutrino flavor composition over time comparing a quantum simulation to a full classical one
Flavor composition of a neutrino over time using a full quantum simulation (red points) compared to exact solution (black line). The points start to drift from the exact solution after only a few oscillations, highlighting how noise in the quantum computer negatively affects the calculation.

 

Tiancheng Song awarded Lee Osheroff Richardson Science Prize

This post is slightly adapted from one originally published by Oxford Instruments

profile picture of Tiancheng Song
Tiancheng Song

Oxford Instruments announced Feb 15 that Tiancheng Song, who will join the UW–Madison physics department as an assistant professor in May, has been awarded the 2024 Lee Osheroff Richardson Science Prize. He is currently an experimental physicist and Dicke Fellow at Princeton University.

Dr. Song is recognized for his efforts in developing and employing various measurement techniques at low temperatures and in magnetic fields to study 2D superconductivity and magnetism in van der Waals heterostructures. His works have uncovered a series of emergent quantum phenomena in 2D superconducting and magnetic systems.

The Lee Osheroff Richardson Science Prize promotes and recognises the novel work of young scientists working in the fields of low temperatures and/or high magnetic fields or surface science in North and South America.

“I am thrilled to be the recipient of the prestigious Lee Osheroff Richardson Science Prize this year! I feel this is a special honour because I am joining the ranks of remarkable scientists who have been awarded this prize for their famous experiments and achievements,” commented Dr. Song.

Tiancheng Song is currently a Dicke Fellow in the Department of Physics at Princeton University. Working with Prof. Sanfeng Wu, Dr. Song recently developed a new technique to investigate 2D superconductivity, strongly correlated phases and the associated unconventional quantum phase transition.

In his work at Princeton, Dr. Song successfully measured superconducting quantum fluctuations of monolayer WTe2 based on the vortex Nernst effect. The result led to the discovery of a new type of quantum critical point beyond the conventional Ginzburg-Landau theory and demonstrated a new sensitive probe to 2D superconductivity and superconducting phase transitions.

Dr. Song’s results have been well recognized by the community with his work being cited over 4,000 times. Dr. Song’s original contributions are demonstrated by the faculty offers he has subsequently received; he will join the University of Wisconsin–Madison as an assistant professor in May 2024.

As part of the prize, Dr. Song will receive $8000 as well as support to attend the APS March Meeting in Minneapolis where he will be presented his award.

The 2024 LOR Science Prize selection committee is chaired by Professor Laura Greene, NHMFL and FSU and includes: Professor Hae-Young Kee, Toronto University; Professor Collin Broholm, Johns Hopkins University; Professor Paula Giraldo-Gallo, University of the Andes; and Dr Xiaomeng Liu, Princeton (2023 winner).

About the LOR Science Prize

Oxford Instruments is aware that there is a critical and often difficult stage for many scientists between completing a PhD and gaining a permanent research position. The company is pleased to help individuals producing innovative work by offering financial assistance and suitably promoting their research work, through sponsoring the LOR Science Prize for North and South America for the past 19 years. The Prize is named in honour of Professors David M. Lee, Douglas D. Osheroff and Robert C. Richardson, joint recipients of The Nobel Prize in Physics 1996 for their discovery of ‘superfluidity in helium-3’.

The previous winners of the LOR Science Prize are Dr Xiaomeng Liu, Dr James Nakamura, Dr Matthew Yankowitz, Dr Sheng Ran, Dr Paula Giraldo-Gallo, Dr Kate Ross, Dr Brad Ramshaw, Dr Mohamad Hamidian, Dr Cory Dean, Dr Chiara Tarantini, Dr Lu Li, Dr Kenneth Burch, Dr Jing Xia, Dr Vivien Zapf, Dr Eunseong Kim, Dr Suchitra Sebastian, Dr Jason Petta, and Dr Christian Lupien.

Welcome, Professor Matthew Otten!

profile photo of Matt Otten
Matthew Otten

Atomic, molecular and optical and quantum theorist Matthew Otten will join the UW–Madison physics department as an assistant professor on January 3, 2024. He joins us most recently from HRL Laboratories. Prior to HRL, Otten earned his PhD from Cornell University, and then was the Maria Goeppert Mayer fellow at Argonne National Laboratory.

Please give an overview of your research.

Very generally, my goal is to make utility scale quantum computing a reality, and to get there faster than we would otherwise without my help. We have a lot of theoretical reasons to believe that quantum algorithms will be faster in certain areas; in practice, we need to know how expensive it’s going to be. It could be that a back of the envelope calculation says a quantum computer might be better, but because quantum computers are very expensive to build and have a lot of overhead, you could find that once you crunch the numbers really carefully, it turns out to cost more money or more energy or more time than just doing it on a supercomputer. In that case, it’s not worth the investment to build it, or at least not at this point. Part of my research is to understand and develop quantum algorithms and count how expensive they are. Once you do that, you can figure out the reason it’s so expensive is A and B. Then we go and we try to fix A and B, and then whack-a-mole all these bottlenecks down and eventually you go from, “It’ll never work,” to “Okay, it’ll work in twenty years.”

Another part of my research is looking at the physical qubits. These devices all have a lot of deep physics inside of them. If you just look at it from the quantum algorithm level, you might get so far. But if you dig down and try to understand the underlying physics, I think you can get further. You might be able to make devices cheaper, faster, or more performant in general. I do a lot of simulations of the underlying physics of these various types of qubits to understand what their properties are, what causes the noise that ruins computation, and what we can do to fix that noise. Through simulations on classical computers, sometimes very large ones, we come up with ways to tweak the system so that you get better performance, by coming up with better quantum algorithms and better qubits. Put those together and hopefully you get to a better quantum computer.

Once you arrive in Madison, what are one or two research projects you think your group will focus on first?

I’ll be bringing a few projects with me. The first is part of a DARPA program called Quantum Benchmarking, which I was part of while at HRL. We found really high-value computational tasks, not specifically quantum, that Boeing, which owns HRL, would like calculated: for instance, reducing corrosion. Corrosion causes planes to be grounded for maintenance, which is costly. Reducing corrosion will reduce maintenance costs and increase uptime. We’ve been developing ways to ask and answer the question, how close are today’s quantum computers to solving that problem? How big do quantum computers need to be to solve that problem? The specific task is understanding what it takes to solve such a large-scale problem, counting the quantum resources that are necessary and coming up with tests so that you could go to a quantum computer, run the tests, and hopefully be able to predict how much bigger or how much faster they would need to be to solve the problem.

Another one comes from the Wellcome Leap Foundation. We are trying to do the largest, most accurate calculation of biological objects — a molecule, string of carbon, something like this — possible on a real-life quantum computer. We’re trying to take techniques that have already been developed or develop new techniques to make circuits smaller, which means a less expensive quantum computer, and faster. That one is a competition, they gave us funding to do it, but if we complete the task better than other competitors, we get more funding to do more.

What attracted you to UW­–Madison?

The strength of the science that’s happening in the physics and broader Wisconsin community is very attractive. When I visited, everyone was very nice, it’s a very collegial department. And being from St. Louis, I like the Midwest. I’ve lived in Southern California for a couple of years now and I haven’t seen snow, and that’s sad. Madison is a lovely area. Great people.

What is your favorite element and/or elementary particle? 

I think it has to be silicon. Silicon is used in classical computing and potentially has use in quantum computing. And you’re carrying around silicon right now, just like everyone else.

What hobbies and interests do you have? 

I have a Siberian Husky puppy and we’ll be very happy to go to Madison and do a lot of skijoring, which is cross country skiing, but the dog pulls you. I started running recently and I was jazzed up for my first half marathon and then I got COVID and I didn’t do it, so I’m still jazzed up for my first half marathon. I play a lot of board games and have a very large board game collection. And my daughter just turned one. She’s become a new hobby.

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.

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/

New quantum sensing technique reveals magnetic connections

By Leah Hesla, Q-NEXT

A research team supported by the Q-NEXT quantum research center demonstrates a new way to use quantum sensors to tease out relationships between microscopic magnetic fields.

Say you notice a sudden drop in temperature on both your patio and kitchen thermometers. At first, you think it’s because of a cold snap, so you crank up the heat in your home. Then you realize that while the outside has indeed become colder, inside, someone left the refrigerator door open.

Initially, you thought the temperature drops were correlated. Later, you saw that they weren’t.

Recognizing when readings are correlated is important not only for your home heating bill but for all of science. It’s especially challenging when measuring properties of atoms.

Now scientists — including those from UW–Madison physics professor Shimon Kolkowitz‘s group — have developed a method, reported in Science, that enables them to see whether magnetic fields detected by a pair of atom-scale quantum sensors are correlated or not.

Read the full story

Smooth sailing for electrons in graphene

two panels in heat-map style. both panels have circles in the middle. The panel on the left has more yellow and red to the left of the circle and a bright yellow ring around the circle; the right panel has a less sharp transition of colors from left to right and no bright ring around the circles.
A heatmap of electron location in graphene shows that at the lower temperature (left panel), the electrons are more likely to bump into impurities (circles), with relatively fewer making it through the channel between impurities. At higher temperatures (right panel), electron flow shifts to being fluid-like. Fewer are stuck at the impurities and more flow through the channels. UNIVERSITY OF WISCONSIN–MADISON

 

This story was originally published by University Communications

Physicists at the University of Wisconsin–Madison directly measured, for the first time at nanometer resolution, the fluid-like flow of electrons in graphene. The results, which will appear in the journal Science on Feb. 17, have applications in developing new, low-resistance materials, where electrical transport would be more efficient.

Graphene, an atom-thick sheet of carbon arranged in a honeycomb pattern, is an especially pure electrical conductor, making it an ideal material to study electron flow with very low resistance. Here, researchers intentionally added impurities at known distances and found that electron flow changes from gas-like to fluid-like as temperatures rise.

profile picture of Zach Krebs
Zach Krebs

“All conductive materials contain impurities and imperfections that block electron flow, which causes resistance. Historically, people have taken a low-resolution approach to identifying where resistance comes from,” says Zach Krebs, a physics graduate student at UW–Madison and co-lead author of the study. “In this study, we image how charge flows around an impurity and actually see how that impurity blocks current and causes resistance, which is something that hasn’t been done before to distinguish gas-like and fluid-like electron flow. 

The researchers intentionally introduced obstacles in the graphene, spaced at controlled distances and then applied a current across the sheet. Using a technique called scanning tunneling potentiomentry (STP), they measured the voltage with nanometer resolution at all points on the graphene, producing a 2D map of the electron flow pattern.

No matter the obstacle spacing, the drop in voltage through the channel was much lower at higher temp (77 kelvins) vs lower temp (4 K), indicating lower resistance with more electrons passing through.

At temperatures near absolute zero, electrons in graphene behave like a gas: they diffuse in all directions and are more likely to hit obstacles than they are to interact with each other. Resistance is higher, and electron flow is relatively inefficient. At higher temperatures — 77 K, or minus 196 C — the fluid-like behavior of electron flow means they are interacting with each other more than they are hitting obstacles, flowing like water between two rocks in the middle of a stream. It is as if the electrons are communicating information about the obstacle to each other and diverting around the rocks.

“We did a quantitative analysis [of the voltage map] and found that at the higher temperature, the resistance is much lower in the channel. The electrons were flowing more freely and fluid-like,” Krebs says. “Graphene is so clean that we’re forcing the electrons to interact with each other before they interact with anything else, and that is crucial in getting them to behave like a fluid.”


Former UW–Madison graduate student Wyatt Behn is a co-first author on this study conducted in physics professor Victor Brar’s group. Funding was provided by the U.S. Department of Energy (DE-SC00020313), the Office of Naval Research (N00014-20-1-2356) and the National Science Foundation (DMR-1653661).