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New Measurements Reveal Evidence of Elusive Particles in a Newly Discovered Superconductor

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Category: Research News
Published: Friday, April 03 2020 11:31
Particle chasing—it’s a game that so many physicists play. Sometimes the hunt takes place inside large supercolliders, where spectacular collisions reveal hidden particles and new physics. For physicists studying solids, the game occurs in a much different environment, and the sought-after particles don’t come from furious collisions. Instead, particle-like entities, called quasiparticles, emerge from complicated electronic interactions that happen deep within a material. Sometimes the quasiparticles are easy to spot, but others are more difficult to find, lurking just out of reach.

New measurements show evidence for the presence of exotic Majorana particles on the surface of an unconventional superconductor, Uranium ditelluride. Graphic provided by Dr. E. Edwards, Managing Director of Illinois Quantum Information Science and Technology Center (IQUIST).New measurements show evidence for the presence of exotic Majorana particles on the surface of an unconventional superconductor, Uranium ditelluride. Graphic provided by Dr. E. Edwards, Managing Director of Illinois Quantum Information Science and Technology Center (IQUIST).

Now a team of researchers at the University of Illinois, led by physicist Vidya Madhavan, in collaboration with researchers from the National Institute of Standards and Technology (NIST), the University of Maryland (UMD), Boston College, and ETH Zurich, have used high-resolution microscopy tools to peer into the inner-workings of an unusual type of superconductor, uranium ditelluride (UTe2). Their measurements reveal strong evidence that this material may be a natural home to an exotic quasiparticle that’s been hiding from physicists for decades. The study was published March 26, 2020 in the journal Nature.

The particles in question were theorized back in 1937 by an Italian physicist named Ettore Majorana. Since then, physicists have been trying to prove that they exist. Scientists think a particular class of materials called chiral unconventional superconductors may naturally host Majoranas. UTe2 may have all of the right properties to spawn these elusive quasiparticles.

“We know the physics of conventional superconductors and understand how they can conduct electricity or transport electrons from one end of a wire to the other with no resistance,” said Madhavan. “Chiral unconventional superconductors are much rarer, and the physics is less well known. Understanding them is important for fundamental physics and has potential applications in quantum computing.”

Inside of a normal superconductor, the electrons pair up in a way that enables lossless and persistent currents. This is in contrast to a normal conductor, like copper wire, which heats up as current passes through it. Part of the theory behind superconductivity was formulated decades ago by three scientists at the University of Illinois who earned a Nobel prize in physics for their work. For this conventional kind of superconductivity, magnetic fields are the enemy and break up the pairs, returning the material back to normal. Over the last year, researchers showed that uranium ditelluride behaves differently.

In 2019, Sheng Ran and Nicholas Butch (both co-authors on this study affiliated with the UMD Quantum Materials Center and NIST) and their collaborators announced that UTe2 remains superconducting in the presence of magnetic fields up to 65 Tesla, which is about 10,000 times stronger than a refrigerator magnet. This unconventional behavior, combined with other measurements, led the authors of that paper to surmise that the electrons were pairing up in an unusual way that enabled them to resist break-ups. The pairing is important because superconductors with this property could very likely have Majorana particles on the surface. The new study from Madhavan and collaborators now strengthens the case that UTe2 is one of these superconductors.

The team used a high-resolution scanning tunneling microscope to look for evidence of the unusual electron pairing and Majorana particles. This microscope not only maps out the surface of uranium ditelluride down to the level of atoms but also probes what’s happening with the electrons. The material itself is silvery, with steps jutting up from the surface. These step features are where evidence for Majorana quasiparticles is best seen. They provide a clean edge that, if predictions are correct, should show signatures of a continuous current that moves in one direction, even without the application of a voltage. The team scanned opposite sides of the step and saw a signal with a peak. But the peak was different, depending on which side of the step was scanned.

“Looking at both sides of the step, you see a signal that is a mirror image of each other. In a normal superconductor, you cannot find that,” said Madhavan. “The best explanation for seeing the mirror images is that we are directly measuring the presence of moving Majorana particles.” The team says that the measurements indicate that free-moving Majorana quasiparticles are circulating together in one direction, giving rise to mirrored, or chiral, signals.

Madhavan says the next step is to make measurements that would confirm that the material has broken time-reversal symmetry. This means that the particles should move differently if the arrow of time were theoretically reversed. Such a study would provide additional evidence for the chiral nature of UTe2.

If confirmed, uranium ditelluride would be the only material, other than superfluid He-3, proven to be a chiral unconventional superconductor. “This is a huge discovery that will allow us to understand this rare kind of superconductivity, and maybe, in time, we could even manipulate Majorana quasiparticles in a useful way for quantum information science,” Madhavan said.

This story was originally published by the Grainger College of Engineering at the University of Illinois. It has been adapted with minor changes here.

To Tune Up Your Quantum Computer, Better Call an AI Mechanic

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Category: Research News
Published: Friday, April 03 2020 09:31

A high-end race car engine needs all its components tuned and working together precisely to deliver top-quality performance. The same can be said about the processor inside a quantum computer, whose delicate bits must be adjusted in just the right way before it can perform a calculation. Who’s the right mechanic for this quantum tuneup job? According to a team that includes scientists at JQI and the National Institute of Standards and Technology (NIST), it’s an artificial intelligence, that’s who.

The team’s paper in the journal Physical Review Applied outlines a way to teach an AI to make an interconnected set of adjustments to tiny quantum dots, which are among the many promising devices for creating the quantum bits, or “qubits,” that would form the switches in a quantum computer’s processor.This artist's conception shows how the research team used artificial intelligence (AI) and other computational techniques to tune a quantum dot device for use as a qubit. The dot's electrons are corralled by electrical gates, whose adjustable voltages raise and lower the "peaks" and "valleys" in the large circles. As the gates push the electrons around, sensitive measurement of the moving electrons creates telltale lines in the black and white images, which the AI uses to judge the state of the dot and then make successive adjustments to the gate voltages. Eventually the AI converts a single dot (leftmost large circle) to a double dot (rightmost), a process that takes tedious hours for a human operator. (Credit: B. Hayes/NIST)This artist's conception shows how the research team used artificial intelligence (AI) and other computational techniques to tune a quantum dot device for use as a qubit. The dot's electrons are corralled by electrical gates, whose adjustable voltages raise and lower the "peaks" and "valleys" in the large circles. As the gates push the electrons around, sensitive measurement of the moving electrons creates telltale lines in the black and white images, which the AI uses to judge the state of the dot and then make successive adjustments to the gate voltages. Eventually the AI converts a single dot (leftmost large circle) to a double dot (rightmost), a process that takes tedious hours for a human operator. (Credit: B. Hayes/NIST)

Precisely tweaking the dots is crucial for transforming them into properly functioning qubits, and until now the job had to be done painstakingly by human operators, requiring hours of work to create even a small handful of qubits for a single calculation. 

A practical quantum computer with many interacting qubits would require far more dots — and adjustments — than a human could manage, so the team’s accomplishment might bring quantum dot-based processing closer from the realm of theory to engineered reality.

“Quantum computer theorists imagine what they could do with hundreds or thousands of qubits, but the elephant in the room is that we can actually make only a handful of them work at a time,” said Justyna Zwolak, a NIST mathematician. “Now we have a path forward to making this real.”

A quantum dot typically contains electrons that are confined to a tight boxlike space in a semiconductor material. Forming the box’s walls are several metallic electrodes (so-called gates) above the semiconductor surface that have electric voltage applied to them, influencing the quantum dot’s position and number of electrons. Depending on their position relative to the dot, the gates control the electrons in different ways.

To make the dots do what you want — act as one sort of qubit logic switch or another, for example — the gate voltages must be tuned to just the right values. This tuning is done manually, by measuring currents flowing through the quantum dot system, then changing the gate voltages a bit, then checking the current again. And the more dots (and gates) you involve, the harder it is to tune them all simultaneously so that you get qubits that work together properly.

In short, this isn’t a gig that any human mechanic would feel bad about losing to a machine. 

“It’s usually a job done by a graduate student,” said graduate student Tom McJunkin of the University of Wisconsin-Madison’s physics department and a co-author on the paper. “I could tune one dot in a few hours, and two might take a day of twiddling knobs. I could do four, but not if I need to go home and sleep. As this field grows, we can’t spend weeks getting the system ready — we need to take the human out of the picture.”

Pictures, though, are just what McJunkin was used to looking at while tuning the dots: The data he worked with came in the form of visual images, which the team realized that AI is good at recognizing. AI algorithms called convolutional neural networks have become the go-to technique for automated image classification, as long as they are exposed to lots of examples of what they need to recognize. So the team’s Sandesh Kalantre, under supervision from Jake Taylor, a Fellow of JQI and the Joint Center for Quantum Information and Computer Science (QuICS), created a simulator that would generate thousands of images of quantum dot measurements they could feed to the AI as a training exercise.

"The simulator allows us to create a large dataset of artificial devices, which can model the real devices one might encounter in the lab," said Kalantre, a Lanczos Graduate Fellow at QuICS.

The team started small, using a setup of two quantum dots, and they verified that within certain constraints their trained AI could auto-tune the system to the setup they desired. It wasn’t perfect — they identified several areas they need to work on to improve the approach’s reliability — and they can’t use it to tune thousands of interconnected quantum dots as yet. But even at this early stage its practical power is undeniable, allowing a skilled researcher to spend valuable time elsewhere.

"This concept — using physical modeling to improve automated systems with machine learning — opens up new vistas for a wide range of experimental systems," said Taylor. "And not just in physics."

This story was originally published by NIST News. It has been adapted with minor changes here.

Reference Publication
"Autotuning of Double-Dot Devices In Situ with Machine Learning," Justyna P. Zwolak, Thomas McJunkin, Sandesh S. Kalantre, J.P. Dodson, E.R. MacQuarrie, D.E. Savage, M.G. Lagally, S.N. Coppersmith, Mark A. Eriksson, Jacob M. Taylor, Phys. Rev. Applied, 13, 034075 (2020)
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Physics Students Receive NSF Graduate Research Fellowships

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Category: Department News
Published: Thursday, April 02 2020 05:56

Five current students and a recent alumnus of the Department of Physics received prestigious National Science Foundation (NSF) Graduate Research Fellowships, which recognize outstanding graduate students in science, technology, engineering, and mathematics.

NSF Graduate Research Fellowship Program logo

“I’m so happy to see our students honored with prestigious NSF Graduate Research Fellowships that acknowledge their hard work in their research endeavors and in the classroom,” said  Amitabh Varshney, dean of the College of Computer, Mathematical, and Natural Sciences (CMNS).

Across the university, 29 undergraduates and recent alumni were among the fellowship winners announced by the NSF. As a result, UMD ranks ninth in the nation and second in the Big Ten for the number of fellows who received their bachelor’s degrees at the university.

The college’s 17 awardees include eight current undergraduates with CMNS majors, three recent alumni who received bachelor’s degrees in CMNS majors, and six current graduate students enrolled in CMNS programs (one of whom is also a recent graduate).

Undergraduate student fellowship recipients:

Alumni fellowship recipients:

NSF fellows receive three years of support, including a $34,000 annual stipend, a $12,000 cost-of-education allowance to the graduate degree-granting institution, international research and professional development opportunities, and access to a supercomputer.

The NSF Graduate Research Fellowship Program helps ensure the vitality of the human resource base of science and engineering in the United States and reinforces its diversity. The program recognizes and supports outstanding graduate students in NSF-supported science, technology, engineering, and mathematics disciplines who are pursuing research-based master’s and doctoral degrees at accredited U.S. institutions.

Since 1952, NSF has funded more than 50,000 Graduate Research Fellowships out of more than 500,000 applicants. Currently, 42 fellows have gone on to become Nobel laureates, and more than 450 have become members of the National Academy of Sciences.

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Read about the other CMNS recipients here.
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HAWC’s Measurement of the Highest Energy Photons Sets Limits on Violations of Relativity

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Category: Research News
Published: Tuesday, March 31 2020 14:31

New measurements confirm, to the highest energies yet explored, that the laws of physics hold no matter where you are or how fast you're moving. Observations of record-breaking gamma rays prove the robustness of Lorentz Invariance—a piece of Einstein's theory of relativity that predicts the speed of light is constant everywhere in the universe. The High Altitude Water Cherenkov observatory in Puebla, Mexico detected the gamma rays coming from distant galactic sources. UMD authors on the paper were Jordan Goodman, Andy Smith, Bob Ellsworth, Kristi Engel, Israel Martinez-Castellanos, Michael Schneider and Elijah Tabachnick.

This compound graphic shows a view of the sky in ultra-high energy gamma rays. The arrows indicate the four sources of gamma rays with energies over 100 TeV from within our galaxy (courtesy of the HAWC collaboration) imposed over a photo of the HAWC Observatory’s 300 large water tanks. The tanks contain sensitive light detectors that measure showers of particles produced by the gamma rays striking the atmosphere more than 10 miles overhead. Credit: Jordan GoodmanThis compound graphic shows a view of the sky in ultra-high energy gamma rays. The arrows indicate the four sources of gamma rays with energies over 100 TeV from within our galaxy (courtesy of the HAWC collaboration) imposed over a photo of the HAWC Observatory’s 300 large water tanks. The tanks contain sensitive light detectors that measure showers of particles produced by the gamma rays striking the atmosphere more than 10 miles overhead. Credit: Jordan Goodman

"How relativity behaves at very high energies has real consequences for the world around us," said Pat Harding, an astrophysicist in the Neutron Science and Technology group at Los Alamos National Laboratory and a member of the HAWC scientific collaboration. "Most quantum gravity models say the behavior of relativity will break down at very high energies. Our observation of such high-energy photons at all raises the energy scale where relativity holds by more than a factor of a hundred."

Lorentz Invariance is a key part of the Standard Model of physics. However, a number of theories about physics beyond the Standard Model suggest that Lorentz Invariance may not hold at the highest energies. If Lorentz Invariance is violated, a number of exotic phenomena become possibilities. For example, gamma rays might travel faster or slower than the conventional speed of light. If faster, those high-energy photons would decay into lower-energy particles and thus never reach Earth.

The HAWC Gamma Ray Observatory has recently detected a number of astrophysical sources which produce photons above 100 TeV (a trillion times the energy of visible light), much higher energy than is available from any earthly accelerator. Because HAWC sees these gamma rays, it extends the range that Lorentz Invariance holds by a factor of 100 times.

"Detections of even higher-energy gamma rays from astronomical distances will allow more stringent the checks on relativity. As HAWC continues to take more data in the coming years and incorporate Los Alamos-led improvements to the detector and analysis techniques at the highest energies, we will be able to study this physics even further," said Harding.

Story courtesy of Los Alamos National Laboratory. Article: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.124.131101

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