Samira Barmaki develops numerical experiments to investigate the effect of intense and ultrashort laser pulses on matter.
“We are currently witnessing significant experimental progress in laser pulses,” says Barmaki, a physics professor at the Université de Moncton’s Shippagan campus. “The durations of these pulses are becoming increasingly short, with some on the order of 100s of attoseconds or less [an attosecond is equal to one quintillionth of a second.] These shortened pulses are excellent tools to help us probe and control the movement of electrons in atoms and molecules — the properties of matter.”
Barmaki and her team at the computational and photonic physics laboratory create simulations to help find ways to control the way electrons leave atoms and the amount of energy they will share. Her work uses numerical methods to accurately describe the energy spectrum of simple atomic and ionic systems, and her group has recently been studying “doubly excited” electronic states that form in the atomic energy spectrum following an excitation by an XUV laser pulse.
“This investigation has made it possible to detect and characterize new doubly excited states [DES] never observed to date,” Barmaki says. “The results of the simulations we are developing will also serve as support for future experimental studies, whether for calibrating laser parameters, proposing new investigation techniques or helping to analyze and explain the resonant features that manifest themselves in the recorded ionization signal due to the involvement of the DES.”
Barmaki says she couldn’t do her work without high-performance computing, which she uses to develop complex algorithms “capable of describing with very high resolution the interaction of the targeted atom with the laser pulse.
“The high-performance computing used in our experiments is based on developed theories using quantum physics, atomic and molecular physics and photonics,” she adds.
Developing these algorithms requires powerful computing and technical resources such as those provided by ACENET and the Digital Research Alliance of Canada.
“Such data processing powers allow us to carry out numerous large-scale projects at our lab and an essential part of that work involves the training and supervision of students at all levels,” she says. “Whether undergraduates for summer internships, master’s students or doctoral students, they are all trained in computational physics and the exploitation of existing algorithms, and they develop their own algorithms by having access to ACENET and the Alliance’s supercomputers.”
Photo byClarisse CrosetonUnsplash > When one thinks about computer science’s role in tackling COVID-19, it’s hard to imagine what it might be. Yet James Hughes is working on that very thing. The assistant professor at St. Francis Xavier University has been spending the summer of 2020 trying to figure out how authorities can most effectively deliver what is bound to start as a finite number of vaccines to have the best chance of slowing the virus. “Vaxing a population is perhaps more a programming problem than people might think,” Hughes says. “When the vaccines become available, we won’t have enough for everyone.” The World Health Organization and the Centers for Disease Control have guidelines on who to vaccinate, which they establish after considering a number of factors, including risk economics and ethics. But, Hughes is working on a more dispassionate model that represents a community as a network of connected people. “Imagine a remarkably simple network with three people,” he explains. “The middle person is connected to the other two, but the people at each end aren’t connected to each other. So if a person on the end gets COVID-19, we vaccinate the middle person, thereby saving them and the person at the other end. If that person is connected to a million other people, we just protected a million people with one vaccine.” Lots of great minds have ideas on how to curb COVID once the vaccine is available but working out the math on them will become extremely labour intensive very quickly, he says. That’s where computers come in. “We’re using artificial intelligence and machine learning to find strategies,” he says. “We’re doing simulations and the AI is generating a system of programs that tell us who to vaccinate.” “The AI isn’t biased by pre-conceived notions,” he says. After they have the strategies, humans can then apply their ethical standards and tweak the answers if necessary. He’s working with other teams —one in Guelph and one at Brock University — and is hoping to get a larger research community involved. Hughes pivoted to COVID when it hit, but his research has always used machine learning to solve real-world problems for which answers aren’t otherwise readily available. The problems can come from kinematics, geology, music, finance and the human brain. He was recently, for example, doing some modelling on people with Parkinson’s, while they were using treadmills. “We were using Compute Canada resources to come up with mathematical functions on how people walk,” he says. “I was also working towards coming up with a predictive model that will tell you what a traumatic brain-injury patient’s intercranial pressure is. The best way to test that is a dangerous neural surgery. We’re working to see if we could find another way that’s safer.” His work also always requires intensive computer resources. In 2018 alone, he used “hundreds and hundreds” of core years. If he’d done the same work on a typical desktop computer, he would have had to hit “run” and return in 200 years for any findings, he jokes.
Have you ever wondered why foods contain trans fats, or why dough needs so much salt, or why cheese tastes so good? Dr. David Pink at St. Francis Xavier University is a theoretical physicist working on edible oils, with the intent of making them healthier for people to eat. Food companies will have to replace certain trans fats in their products and the big question is “by what can they be replaced?” The problem arises from the fact that (solid) trans fats help create liquid oil-binding structures in products such as shortenings. Without their “Oil Binding Capacity”, shortenings and similar products just won’t work. But, industrially-manufactured trans fats created via hydrogenation have been shown to damage human health and the US Food & Drug Administration (USFDA) will require producers to cease using them. Accordingly, to replace them, we need alternatives that are inexpensive, edible and behave the same way as trans fats so that consumers won’t be able to tell the difference. Working in collaboration with Dr. Alejandro Marangoni, Professor of Food Science at the University of Guelph, the process begins with trying to understand what solid fats structures arise in edible oils and why they trap the oil so as to exhibit the desired Oil Binding Capacity. Without understanding those fundamental things, researchers can only make, at best, educated guesses as to what ingredient can be used to successfully replace them – an inefficient way to try to solve a multimillion dollar problem. Instead, Pink began by modelling crystalline nanoplatelets, the most stable small solid fats in the oils, then simulated their interactions to study them. Because of the models’ complexity – edible oils involve many components – he had to make use of computer simulations, working with his Research Associate, Bonnie Quinn, and using ACENET. The goal was to predict what structures develop in edible oils. Pink says, “If it wasn’t for ACENET, I wouldn’t even be able to begin.”. Pink predicted the experimental structures which arise in systems using ultra-small angle X-ray scattering (USAXS). He also predicted the existence of stacks of crystalline nanoplatelets, called TAGwoods. His predictions were all confirmed by his PhD student. He then made predictions about solid fats which become coated with semi-liquid oil components. He, Dr. Shajahan Razul of ACENET and Pink’s undergraduate student carried out atomic scale molecular dynamics simulations and showed that Pink’s assumptions about coated solid fats were justified and that they will indeed bind oil. Subsequent projects will address how larger structures get formed, so that he can begin searching for replacements for trans fats. One such project will probe the dynamics of edible oils using dissipative particle dynamics, a simulation technique that can study larger scale systems over longer timescales. In recent months, Pink has branched out. With Dr. Marangoni’s leadership and an industry collaboration, he is modelling cheeses to discover the essential aspects of their structures. Pink is also modelling dough. Bread makers will be required to reduce the amount of salt and this can make the dough sticky. Working with Dr. Erzsebet Papp-Szabo, who provides input about the chemistry of dough, he has just finished developing models and has some preliminary results. Now in his 70s, by most people’s standards, David Pink should be retired. “But,” he said, “I’m simply having too much fun working with Alejandro, with my other colleagues and with my students.” And he is pleased that his work has been recognized by the 2015 Distinguished Service/Outstanding Achievement Award from the Edible Applications Technology division of the American Oil Chemists’ Society.
About 500 GB of data are created around the world every second, with the total amount of data doubling every two years. Approximately 600 million hard drives were sold last year to contain this data, creating $32 billion in revenue for the industry, with all of that information stored on a disc smaller than a compact disc through the marvels of nano-magnets. But don’t expect this to continue. The laws of physics are being pushed to their limit in the quest for ever decreasing bit size. The industry is looking to fundamental research to provide a roadmap to guide the development of the next generation of magnetic hard drives. At the leading edge of this research are Profs. Martin Plumer and John Whitehead in the Department of Physics and Physical Oceanography, currently in their fourth year of a collaborative research agreement with Western Digital Corporation, near San Francisco, Calif., in a project that uses numerical simulations to study the stability of data stored with ever-smaller bits. “The driver of all this cheap storage is called areal density (AD), which is how many bits you can store on a square inch of a disc,” said Dr. Plumer. “AD has increased 100 million times over the past 50 years, and for a few years in the early 2000s, the annual growth rate in AD was 100 per cent. Today it is down to about 20 per cent. To sustain even a modest growth in AD over the next decade, manufacturers will need to bring new technologies to market in a relatively short time frame, and cheaply.” He explains that while the capacity of a typical disc drive has increased exponentially with time, its price has remained relatively constant because of the fierce competition between manufacturers. However, these price wars have taken their toll. “Fifteen years ago there were eight or so such companies in the U.S.,” he said. “Today, only arch rivals Western Digital and Seagate remain and neither company can afford to let the other take the technology lead. The blistering pace of the time-to-market for these new technologies is therefore critical to staying competitive. Keeping ahead in fundamental research is essential.” The main problem with increasing AD is that it affects the stability of the stored information and limits the increases in AD. The stability problem arises because to form a bit, all the tiny nano-magnets must be aligned in the same direction. “Unfortunately, the nano-magnets would rather align in opposite directions,” said Dr. Whitehead. “Just try holding two refrigerator magnets next to each other the wrong way. Fluctuations of the nano-magnets due to thermal agitation can cause random flips that degrade the bit pattern. Even at room temperature there is enough thermal energy to potentially flip a nano-magnet in a bit. “Over time, more and more nano-magnets flip their direction and the stored information is non-recoverable. For higher AD, you need smaller bits and smaller nano-magnets, which are easier to flip — that’s called superparamagnetism. Ten years ago, hard drives had a typical warranty period of five years. Now you are lucky to get a commitment that your thesis — or photos, or music — stored on your hard drive will still be there three years later, and it’s all because of superparamagnetism.” The researchers’ computer simulations relate the stability of the nano-magnets in a bit pattern to the basic material properties of the thin magnetic films that make up a hard disc. Together with their postdoctoral scholar, Dr. Tim Fal, their part-time research assistant and PhD student Jason Mercer and Dr. Johannes van Ek, their principal collaborator at Western Digital, the professors solve time-dependent equations for interacting nano-magnets or “micromagnetics” that include the effects of thermal fluctuations. “This is not an easy problem and we need the full power of the hundreds of processors available from the Atlantic Computational Excellence Network to get meaningful results,” said Dr. Plumer. “Both Western Digital and Seagate recognize the importance of fundamental research and of funding university collaborations. Our collaborative research agreement with Western Digital supports the development of numerical models that can be used to guide targeted research in materials science to sustain the continued increase in AD over the next decade. It has also brought over US$180,000 into the local economy by providing salaries for post-doctoral scholars and students.” Dr. Plumer adds the collaboration has been a lot of fun. “We get to do the type of research that we love with the added benefit that industry is interested enough to help pay for it,” he said. “It is also a way for our students and post-docs to get exposure to real-world problems and to see first-hand how fundamental science makes an impact. They get to present their results at applied magnetism conferences, interact with industry researchers, and also visit the research and manufacturing sites of Western Digital. In fact, the training in our group has even led to one of our former post-docs landing a permanent position at Seagate in Minneapolis.”
Sheldon Opps recalls watching a large silver fox from the window of his Prince Edward Island home last winter. The fox in question was navigating the urban sidewalk, maneuvering around high snowbanks, even pausing to check for traffic before crossing the street. “He was tracing a path just like a human would,” Opps says. “He was very comfortable in his urban environment.” Opps spends a lot of time thinking about urban foxes. The University of Prince Edward Island physics professor has been conducting an ongoing study of fox movement patterns within highly fragmented habitats such as urban Charlottetown. But Opps is not a biologist. He’s an expert in the field of soft condensed matter physics, where he applies the tools of statistical physics to study a variety of biologically relevant physical systems, including liquids, colloids, foams, gels and biological tissues. The interest in fox behaviour came via his wife Marina Silva-Opps, a biologist at UPEI, and from his interest in applying the methods of computational and statistical physics to study other complex systems – such as animal movement. The life of a fox in Charlottetown is fraught with challenges. Along with the typical dangers that a city presents – traffic, hostile dogs and homeowners, a lack of natural food sources – the animals must deal with ever increasing habitat fragmentation that breaks up their traditional hunting grounds. Opps is studying what that fragmentation means for both foxes and humans. Habitat fragmentation is having some unusual effects on the highly adaptive fox population. For one thing, the animals are quickly becoming semi-domesticated as homeowners feed them and even give them names in many cases. “We’re seeing the same patterns happening that we believe led to the domestication of dogs thousands of years ago,” says Opps. According to the current theory, wild wolves began living in close proximity to humans in the Palaeolithic age to take advantage of their hunting leftovers, eventually becoming domesticated by the process. “The conjecture is that in 50 or 100 years, if this continues, foxes could become domesticated here in Charlottetown as they have in other areas in the world, such as Russia”. Patrick Strongman is a physics undergraduate student at UPEI and an ACENET fellowship holder who is working with Opps on the fox project. As part of his research project, Strongman developed the algorithm used to track fox movements and identify cluster points where animals gathered. The algorithm compiled hundreds of data points including individual fox movements, distances travelled, velocity and GPS information, and used the data to run simulations of fox movements based on changing urban conditions. Strongman says the ACENET computer network was key to the project. “It cut down to a few hours what would have normally taken weeks to complete,” he says. Opps admits that fox habitat is an unusual subject for a physicist to be studying – particularly one trained in theoretical disciplines such as quantum mechanics and statistical physics. But he says it’s not really such a big stretch. “Like any physicist I’m a problem solver,” he says. “Physicists are usually busy looking across time and space or peering down into the realm of quantum mechanics. But just as a telescope looks back into time to study the beginnings of the universe, a study like this can unlock the secrets of how life evolved over time. Everything is interconnected. Humans and foxes are all a part of an evolving universe.”
