Maryland Quantum Alliance Launched

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Category: Department News

Published: Wednesday, January 29 2020 05:56

Catching New Patterns of Swirling Light Mid-flight

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Category: Research News

Published: Tuesday, January 21 2020 05:56

In many situations, it’s fair to say that light travels in a straight line without much happening along the way. But light can also hide complex patterns and behaviors that only a careful observer can uncover.

This is possible because light behaves like a wave, with properties that play a role in several interesting phenomena. One such property is phase, which measures where you are on an undulating wave—whether you sit at a peak, a trough or somewhere in between. When two (otherwise identical) light waves meet and are out of phase, they can interfere with one another, combining to create intricate patterns. Phase is integral to how light waves interact with each other and how energy flows in a beam or pulse of light.

Researchers at the University of Maryland, led by UMD Physics Professor Howard Milchberg, have discovered novel ways that the phase of light can form optical whorls—patterns known as spatiotemporal optical vortices (STOVs). In a paper published in the journal Optica on Dec. 18, 2019, the researchers captured the first view into these phase vortices situated in space and time, developing a new method to observe ultra-fast pulses of light.

Each STOV is a pulse of light with a particular pattern of intensity—a measure of where the energy is concentrated—and phase. In the STOVs prepared by Milchberg and his collaborators, the intensity forms a loop in space and time that the researchers describe as an edge-first flying donut: If you could see the pulse flying toward you, you would see only the edge of the donut and not the hole. (See leftmost image below, where negative times are earlier.) In the same region of space and time, the phase of the light pulse forms a swirling pattern, creating a vortex centered on the donut hole (rightmost image).Processed data showing the intensity forming a ring (left) and the phase forming the vortex (right) in a spatiotemporal optical vortex. The green arrow indicates the increase of the phase around the vortex. (Credit: Scott Hancock/University of Maryland)

Milchberg and colleagues discovered STOVs in 2016 when they found structures akin to “optical smoke rings” forming around intense laser beams. These rings have a phase that varies around their edge, like the air currents swirling around a smoke ring. The vortices made in the new study are a similar but simpler structure: If you think of the original smoke ring as a bracelet made of beads, the new STOVs are like the individual beads.

The prior work showed that STOVs provide an elegant framework for understanding a well-known high-intensity laser effect—self-guiding. At high intensity, this effect occurs when a laser pulse, interacting with the medium it’s traveling through, compresses itself into a tight beam. The researchers showed that in this process, STOVs are responsible for directing the flow of energy and reshaping the laser, pushing energy together at its front and apart at its back.

That initial discovery looked at how these rings formed around a beam of light in two dimensions. But the researchers couldn’t explore the internal working of the vortices because each pulse is too short and fast for previously established techniques to capture. Each pulse passes by in just femtoseconds—about a 100 trillion times quicker than the blink of an eye.

“These are not microsecond or even nanosecond pulses that you just use electronics to capture,” says Sina Zahedpour, a co-author of the paper and UMD physics postdoctoral associate. “These are extremely short pulses that you need to use optical tricks to image.”

To capture both the intensity and phase of the new STOVs, researchers needed to prepare three additional pulses. The first pulse met with the STOV inside a thin glass window, producing an interference pattern encoded with the STOV intensity and phase. That pattern was read out using two longer pulses, producing data like that shown in the image above.

“The tools we had previously only looked at the amplitude of the light,” says Scott Hancock, a UMD physics graduate student and first author of the paper. “Now, we can get the full picture with phase, and this is proof that the principle works for studying ultrafast phenomena.”

STOVs may have a resilience that is useful for practical applications because their twisting, screw-like phase makes them robust against small obstacles. For example, as a STOV travels through the air, parts of the pulse might be blocked by water droplets and other small particles. But as they continue on, the STOVs tend to fill in the small sections that got knocked out, repairing minor damage in a way that could help preserve any information recorded in the pulse. Also, because a STOV pulse is so short and fast, it is indifferent to normal fluctuations in the air that are comparatively slow.

“Controlled generation of spatiotemporal optical vortices may lead to applications such as the resilient propagation of information or beam power through turbulence or fog,” says Milchberg. “These are important for applications such as free-space optical communications using lasers or for supplying power from ground stations to aerial vehicles.”

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In addition to Milchberg, Zahedpour and Hancock, graduate student Andrew Goffin was a co-author.

This research was supported by the National Science Foundation (NSF) (Award No. 1619582), the Air Force Office of Scientific Research (Award Nos. FA9550-16-10121 and FA9550-16-10284) and the Office of Naval Research (Award Nos. N00014-17-1-2705 and N00014-17-12778). The content of this article does not necessarily reflect the views of the NSF, the Air Force Office of Scientific Research or the Office of Naval Research.

The paper “Free-space propagation of spatiotemporal optical vortices,” S. W. Hancock, S. Zahedpour, A. Goffin, and H. M. Milchberg was published in Optica on December 18, 2019.

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Faculty, Staff, Student and Alumni Awards & Notes

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Category: Department News

Published: Friday, January 17 2020 05:56

We proudly recognize members of our community who recently garnered major honors, authored books, began new positions and more.

Faculty and Staff Awards

• Steve Anlage – Graduate Advising Award 

• Maissam Barkeshli – Richard A. Ferrell Fellowship

• Mark Conners – Chair's Award 

• Janet Das Sarma – Chair's Certificate of Excellence 

• Sankar Das Sarma – Clarivate Analytics’ Highly Cited Researcher

• Zohreh Davoudi – DOE Early Career Research Funding and 2019 Sloan Research Fellowship

• Dennis Drew – American Physical Society Outstanding Referee

• Alexey Gorshkov – Presidential Early Career Award for Scientists and Engineers (PECASE).

• Mohammad Hafezi – Blavatnik Award Finalist

• Donna Hammer – Chair's Certificate of Excellence 

• Daniel Lathrop – Distinguished Scholar-Teacher 

• Vlad Manucharyan – Google Faculty Research Award and DOE Early Career Research Funding

• Howard Milchberg – American Physical Society Outstanding Referee

• Chris Monroe – Willis Lamb Award and Clarivate Analytics’ Highly Cited Researcher

• Jay Deep Sau – American Physical Society Outstanding Referee

• Peter Shawhan – American Physical Society Fellow

• Ian Spielman – Clarivate Analytics’ Highly Cited Researcher

• Kristin Stenson – Chair's Certificate of Excellence 

• Samantha Suplee – Sibylle Sampson Award 

• Ellen Williams – Fellow of the American Association for the Advancement of Science and Michigan State Distinguished Alumni Award

 Student Awards

• Batoul Banihashemi – Ralph Myers Award

• Dawid Brzeminski – Ralph Myers Award

• Leonard Campanello – Monroe H. Martin Graduate Research Fellowship

• Daniel Campbell – Ann G. Wylie Semester Dissertation Fellowship 

• Liz Friedman – Leon A. Herreid Science Fellowship

• Hong Nhung Nguyen – Ruth M. Davis Fellowship

• Pranava Jayanti – Kulkarni Fellowship

• Soubhik Kumar – Monroe H. Martin Graduate Research Fellowship

• Jillian Kunze – Merrill Presidential Scholarship

• Kungang Li – Ralph Myers Award

• Fangli Liu - Ann G. Wylie Semester Dissertation Fellowship

• Dalia Ornelas Huerta – Monroe H. Martin Graduate Research Fellowship

• Spandan Pathak – Ralph Myers Award

• Abu Saleh Musa Patoary – Ralph Myers Award

• Nicholas Poniatowski – Barry Goldwater Scholarship, Merrill Presidential Scholarship and Ralph Myers Award

• Andrew Shaw – Joseph and Dorothy Sucher Graduate Prize in Relativistic Theoretical Physics

• Ana Valdes-Curiel – Ruth M. Davis Fellowship

• Yidan Wang – Ruth M. Davis Fellowship

• Zhiyu Yin – Leon A. Herreid Science Fellowship and Thomas G. Mason Interdisciplinary Physics Fund

• Mark Zic – Barry Goldwater Scholarship

 Group Efforts

• LHCb’s discovery of CP violation was named a Physics World Breakthrough of the Year finalist. More

• The European Physical Society High Energy and Particle Physics Prize went to the DØ and CDF collaborations, which include Nick Hadley, Sarah Eno, Drew Baden, Greg Sullivan, and Kara Hoffman. More

• The Society of Physics Students won an Outstanding Chapter Award from the SPS National Office. More

• A team led by Chris Monroe won the overall Invention of the Year Award at Innovate Maryland 2019 for “Cryogenic Ion Trapping and Storage System for Quantum Information.” Monroe’s early-stage quantum computing company IonQ also took home the prize for Startup of the Year. More

Alumni Notes

• Damian Blazy (B.S. ’02) was named a principal in the Los Angeles office of OpenGate Capital.

• Joel Dahlin (Ph.D. ’15) received the AIP Publishing Ronald Davidson Award.

• Alexei Fedotov (Ph.D. ’97) received the Science & Technology Award of Brookhaven National Lab.

• Mark Harley (B.S. ’07) joined the faculty of Watchung Hills Regional High School in Warren, N.J., as a physics teacher. 

• Ruth Kastner (B.S. ’82, M.S. ’92) published Corralling quantum cats: from Cheshire cat to Schrodinger's cat, World Scientific Publishing Company, 2019.

• James P. Lavine (Ph.D. ’71) published Time-Dependent Quantum Mechanics of Two-Level Systems, World Scientific Publishing Company, 2019.

• John Martyn (B.S. ’19) received the Barry Goldwater Scholarship and Ralph Myers Award.

• Thomas Mason (B.S. ’89) was named Fellow of the American Association for the Advancement of Science.

• Ana Maria Rey (Ph.D. ’04) was named Blavatnik National Laureate in Physical Sciences & Engineering.

• Gareth Roberg-Clark (Ph.D. ’19) received a NERSC Early Career HPC Achievement Award.

A Physics Career Along the Path Less Traveled

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Category: Department News

Published: Friday, January 17 2020 05:56

Michelle Girvan’s career defies easy categorization. Currently a professor of physics at the University of Maryland, very little of her research would be immediately recognizable to a physics traditionalist. Instead, she applies her physics training to tackle discipline-spanning scientific questions that range from social relationships and cancer genetics to artificial intelligence (AI). 

When asked how she identifies herself to new colleagues, a thoughtful smile crossed her face as she pondered a reply.Michelle Girvan

“That’s a very interesting question. I often say I’m a physics professor who does applied mathematics. It’s a broader umbrella that allows me to work on nearly any problem, as long as I focus on the math that underlies it,” explained Girvan, who also has joint appointments in UMD’s Institute for Physical Science and Technology and Institute for Research in Electronics and Applied Physics. “But I still think of myself as a physicist, because physicists seek simple, cohesive explanations for complex phenomena. I’m still looking for those overarching organizing principles, even if I’m applying them to biological or social problems.”

Girvan is quick to point out that, while her approach may be nontraditional, she’s far from alone. She notes a recent meeting of the American Physical Society that featured sessions on neural networks, gene regulation and econophysics—a relatively new field that applies physical theories and methodologies to the study of economics. The common thread among these scientists, Girvan said, is that they tackle their research by first asking, “How would a physicist solve this problem?”

“I think we need more of that,” Girvan added. “A physicist’s perspective might help identify patterns and phenomena that can go unnoticed by others who focus on fine-scale details.”

Girvan’s unorthodox path began during her undergraduate studies in physics and math at the Massachusetts Institute of Technology, where a course in the Department of Earth, Atmospheric and Planetary Sciences first introduced her to the concepts of chaos, nonlinear dynamics and complexity. From there, she went to Cornell University to pursue her Ph.D. with applied mathematician Steven Strogatz, then on to a postdoctoral fellowship at the Santa Fe Institute, where she now holds an external faculty position. 

During her first stint at the Santa Fe Institute, she co-developed the well-known Girvan-Newman algorithm in collaboration with Mark Newman, now at the University of Michigan. They published their work in the Proceedings of the National Academy of Sciences in 2002. Broadly stated, the algorithm helps to identify relationships, connections and groupings in networks that might not be readily apparent. 

“If you were to apply the algorithm to a social media network, for example, you might logically expect to find people divided into strong social or professional groups. Among scientists, you’d expect physicists to be grouped with other physicists, biologists with biologists, and so on,” Girvan said. “Our algorithm can also help identify interesting deviations from these expected norms.”  

The Girvan-Newman algorithm can also be applied to the recommendation systems used by online retailers and streaming entertainment services like Netflix and Spotify, Girvan noted. 

“If you link two movies together, in terms of the frequency they’re watched by the same person, the algorithm can uncover groupings that might not be obvious,” Girvan said. “Action movie fans interested in science fiction might also like a third kind of movie you wouldn’t expect.”

Girvan joined UMD in 2007, drawn in no small part by the university’s strong tradition in nonlinear dynamics. She has collaborated frequently with many researchers across campus, including two world-renowned experts: Distinguished University Professors Edward Ott and James Yorke, both well known for their landmark publications in chaos theory and other aspects of nonlinear dynamics. 

Here at UMD, Girvan has applied the tools and philosophical framework of physics to investigate questions in ecology, genetics, development, cancer biology, neuroscience, social networks, machine learning and more. At the moment, she is highly interested in the interface between the human brain and artificial neural networks. 

“Living in this age of rapid advancements in AI, I want to know how our understanding of the human brain, at an abstract level, can help us develop more effective AI methodologies,” Girvan said. 

Girvan is also pursuing approaches for integrating knowledge-based models derived from physics with knowledge-free AI models. 

“So many successes in AI and machine learning have come from ‘black box’ approaches—you throw a lot of data at an AI system and it learns how to make predictions. But these black-box models don’t help us understand the natural world any better,” Girvan said. “By incorporating what we already know about the underlying physics, we can build hybrid systems that combine knowledge-based approaches and knowledge-free approaches, enabling more accurate predictions that also give us new insights into how the world works.” 

Girvan also has a strong interest in training the next generation of discipline-defying researchers. She currently serves as the principal investigator for COMBINE: Computation and Mathematics for Biological Networks, UMD’s National Science Foundation (NSF)-funded Research Traineeship (NRT) program in network biology. The program immerses graduate students in research and training that integrates tools from physics, mathematics and computer science to gain deeper insights into the principles that govern living systems. 

“We’re interested in students who want to solve life science problems where network structure matters, from neurological to ecological networks,” Girvan said. “We brought in a diverse group of faculty from a wide range of disciplines to help with the effort. We have about two and a half years of NSF funding left, so we’re looking into other ways to keep it going.”

While her career path as a physicist may play fast and loose with tradition, Girvan isn’t opposed to all time-honored conventions. In her free time, she participates in one of the oldest sporting endeavors known: equestrian competition. 

“I have some of my best thoughts after I’m done riding,” Girvan mused. “I feel like it takes me out of the local landscape where I’m stuck on the small problems and clears any blockages I might have in my head.”

Written by Matthew Wright

Listen to Michelle Girvan discuss how artificial intelligence can help predict chaotic behavior.