Computers Math

A precision diagnostic developed at the Department of Energy’s Sandia National Laboratories is emerging as a gold standard for detecting and describing problems inside quantum computing hardware.
Two papers published today in the scientific journal Nature describe how separate research teams — one including Sandia researchers — used a Sandia technique called gate set tomography to develop and validate highly reliable quantum processors. Sandia has been developing gate set tomography since 2012, with funding from the DOE Office of Science through the Advanced Scientific Computing Research program.
Sandia scientists collaborated with Australian researchers at the University of New South Wales in Sydney, led by Professor Andrea Morello, to publish one of today’s papers. Together, they used GST to show that a sophisticated, three-qubit system comprising two atomic nuclei and one electron in a silicon chip could be manipulated reliably with 99%-plus accuracy.
In another Nature article appearing today, a group led by Professor Lieven Vandersypen at Delft University of Technology in the Netherlands used gate set tomography, implemented using Sandia software, to demonstrate the important milestone of 99%-plus accuracy but with a different approach, controlling electrons trapped within quantum dots instead of isolated atomic nuclei.
“We want researchers everywhere to know they have access to a powerful, cutting-edge tool that will help them make their breakthroughs,” said Sandia scientist Robin Blume-Kohout.
Future quantum processors with many more qubits, or quantum bits, could enable users working in national security, science and industry to perform some tasks faster than they ever could with a conventional computer. But flaws in current system controls cause computational errors. A quantum computer can correct some errors, but the more errors it must correct, the larger and more expensive that computer becomes to build. More

Crystals reveal the hidden geometry of molecules to the naked eye. Scientists use crystals to figure out the atomic structure of new materials, but many can’t be grown large enough. Now, a team of researchers report a new technique in the January 19 issue of Nature that can discover the crystalline structure of any material.
To truly understand a chemical, a scientist needs to know how its atoms are arranged. Sometimes that’s easy: for example, both diamond and gold are made of a single kind of atom (carbon or gold, respectively) arranged in a cubic grid. But often it’s harder to figure out more complicated ones.
“Every single one of these is a special snowflake — growing them is really difficult,” says UConn chemical physicist Nate Hohman. Hohman studies metal organic chacogenolates. They’re made of a metal combined with an organic polymer and an element from column 16 of the periodic table (sulfur, selenium, tellurium or polonium.) Some are brightly colored pigments; others become more electrically conductive when light is shined on them; others make good solid lubricants that don’t burn up in the high temperatures of oil refineries or mines.
It’s a large, useful family of chemicals. But the ones Hohman studies — hybrid chalcogenolates — are really difficult to crystallize. Hohman’s lab couldn’t solve the atomic structures, because they couldn’t grow large perfect crystals. Even the tiny powdered crystals they could get were imperfect and messy.
X-ray crystallography is the standard way to figure out the atomic arrangements of more complicated materials. A famous, early example was how Rosalind Franklin used it to figure out the structure of DNA. She isolated large, perfect pieces of DNA in crystalline form, and then illuminated them with x-rays. X-rays are so small they diffract through the spaces between atoms, the same way visible light diffracts through slots in metal. By doing the math on the diffraction pattern, you can figure out the spacing of the slots — or atoms — that made it.
Once you know the atomic structure of a material, a whole new world opens up. Materials scientists use that information to design specific materials to do special things. For example, maybe you have a material that bends light in cool ways, so that it becomes invisible under ultraviolet light. If you understand the atomic structure, you might be able to tweak it — substitute a similar element of a different size in a specific spot, say — and make it do the same thing in visible light. Voila, an invisibility cloak! More

Daylight passing through smart windows results in almost complete disinfection of surfaces within 24 hours while still blocking harmful ultraviolet (UV) light, according to new research from UBC’s Okanagan campus.
Dr. Sepideh Pakpour is an Assistant Professor at UBC Okanagan’s School of Engineering. For this research, she tested four strains of hazardous bacteria — methicillin-resistance Staphylococcus aureus, Klebsiella pneumoniae, E. coli and Pseudomonas aeruginosa — using a mini-living lab set-up. The lab had smart windows, which tint dynamically based on outdoor conditions, and traditional windows with blinds. The researchers found that, compared to windows with blinds, the smart windows significantly reduce bacterial growth rate and their viability.
In their darkest tint state, Dr. Pakpour says smart windows blocked more than 99.9 per cent of UV light, but still let in short-wavelength, high-energy daylight which acts as a disinfectant. This shorter wavelength light effectively eliminated contamination on glass, plastic and fabric surfaces.
In contrast, traditional window blinds blocked almost all daylight, preventing surfaces from being disinfected. Blinds also collect dust and germs that get resuspended into the air whenever adjusted, with Dr. Pakpour noting previous research has shown 92 per cent of hospital curtains can get contaminated within a week of being cleaned.
“We know that daylight kills bacteria and fungi,” she says. “But the question is, are there ways to harness that benefit in buildings, while still protecting us from glare and UV radiation? Our findings demonstrate the benefits of smart windows for disinfection, and have implications for infectious disease transmission in laboratories, health-care facilities and the buildings in which we live and work.”
The pandemic has elevated concerns about how buildings might influence the health of the people inside. While particular attention has been paid to ventilation, cleaning and filtration, the importance of daylight has been ignored. According to research shared in a recent Harvard Business Review, office workers are pushing for “healthy buildings” as part of the return to work and consistently rank access to daylight and views among their most desired amenities. More

LMU researchers have developed a new strategy for manufacturing nanoscale structures in a time- and resource-efficient manner.
Macromolecules such as cellular structures or virus capsids can emerge from small building blocks without external control to form complex spatial structures. This self-organization is a central feature of biological systems. But such self-organized processes are also becoming increasingly important for the building of complex nanoparticles in nanotechnological applications. In DNA origami, for instance, larger structures are created out of individual bases.
But how can these reactions be optimized? This is the question that LMU physicist Prof. Erwin Frey and his team are investigating. The researchers have now developed an approach based on the concept of time complexity, which allows new strategies to be created for the more efficient synthesizing of complex structures, as they report in the journal PNAS.
A concept from the computer sciences
Time complexity originally describes problems from the field of informatics. It involves investigating how the amount of time needed by an algorithm increases when there is more data to process. When the volume of data doubles, for example, the time required could double, quadruple, or increase to an even higher power. In the worst case, the running time of the algorithm increases so much that a result can no longer be output within a reasonable timeframe.
“We applied this concept to self-organization,” explains Frey. “Our approach was: How does the time required to build large structures change when the number of individual building blocks increases?” If we assume — analogously to the case in computing — that the requisite period of time increases by a very high power as the number of components increases, this would practically render syntheses of large structures impossible. “As such, people want to develop methods in which the time depends as little as possible on the number of components,” explains Frey.
The LMU researchers have now carried out such time complexity analyses using computer simulations and mathematical analysis and developed a new method for manufacturing complex structures. Their theory shows that different strategies for building complex molecules have completely different time complexities — and thus also different efficiencies. Some methods are more, and others less, suitable for synthesizing complex structures in nanotechnology. “Our time complexity analysis leads to a simple but informative description of self-assembly processes in order to precisely predict how the parameters of a system must be controlled to achieve optimum efficiency,” explains Florian Gartner, a member of Frey’s group and lead author of the paper.
The team demonstrated the practicability of the new approach using a well-known example from the field of nanotechnology: The scientists analyzed how to efficiently manufacture a highly symmetrical viral envelope. Computer simulations showed that two different assembly protocols led to high yields in a short window of time.
A new strategy for self-organization
When carrying out such experiments before now, scientists have relied on an experimentally complicated method that involves modifying the bond strengths between individual building blocks. “By contrast, our model is based exclusively on controlling the availability of the individual building blocks, thus offering a simpler and more effective option for regulating artificial self-organization processes,” explains Gartner. With regard to its time efficiency, the new technique is comparable, and in some cases better, than established methods. “Most of all, this schema promises to be more versatile and practical than conventional assembly strategies,” reports the physicist.
“Our work presents a new conceptual approach to self-organization, which we are convinced will be of great interest for physics, chemistry, and biology,” summarizes Frey. “In addition, it puts forward concrete practical suggestions for new experimental protocols in nanotechnology and synthetic and molecular biology.” More

Steel-reinforced concrete columns that support many of the world’s bridges are designed to withstand earthquakes, but always require inspection and often repair once the shaking is over.
These repairs usually involve replacing loose concrete and fractured steel bars and adding extra materials around the damaged area to further strengthen it against future loads.
Engineers at Rice University’s George R. Brown School of Engineering and Texas A&M University have developed an innovative computational modeling strategy to make planning these repairs more effective.
The study by Rice postdoctoral research associate Mohammad Salehi and civil and environmental engineers Reginald DesRoches of Rice and Petros Sideris of Texas A&M appears in the journal Engineering Structures. DesRoches is also the current provost and the incoming president of Rice.
“When we design bridges and other structures for earthquakes, the goal is collapse prevention,” DesRoches said. “But particularly in larger earthquakes, we fully expect them to be damaged. In this study, we show analytically that those damages can be repaired in a way that the original, or close to the original, performance can be achieved.”
Their models simulate how columns are likely to respond globally (in terms of base shear and lateral displacement) and locally (with stress and strain) in future earthquakes when using various repair methods. More

Researchers at the University of Surrey have successfully demonstrated proof-of-concept of using their multimodal transistor (MMT) in artificial neural networks, which mimic the human brain. This is an important step towards using thin-film transistors as artificial intelligence hardware and moves edge computing forward, with the prospect of reducing power needs and improving efficiency, rather than relying solely on computer chips.
The MMT, first reported by Surrey researchers in 2020, overcomes long-standing challenges associated with transistors and can perform the same operations as more complex circuits. This latest research, published in the peer-reviewed journal Scientific Reports, uses mathematical modelling to prove the concept of using MMTs in artificial intelligence systems, which is a vital step towards manufacturing.
Using measured and simulated transistor data, the researchers show that well-designed multimodal transistors could operate robustly as rectified linear unit-type (ReLU) activations in artificial neural networks, achieving practically identical classification accuracy as pure ReLU implementations. They used both measured and simulated MMT data to train an artificial neural network to identify handwritten numbers and compared the results with the built-in ReLU of the software. The results confirmed the potential of MMT devices for thin-film decision and classification circuits. The same approach could be used in more complex AI systems.
Unusually, the research was led by Surrey undergraduate Isin Pesch, who worked on the project during the final year research module of her BEng (Hons) in Electronic Engineering with Nanotechnology. Covid meant she had to study remotely from her home in Turkey, but she still managed to spearhead the development, complemented by an international research team, which also included collaborators in the University of Rennes, France and UCL, London.
Isin Pesch, lead author of the paper, which was written before she graduated in July 2021, said:
“There is a great need for technological improvements to support the growth of low cost, large area electronics which were shown to be used in artificial intelligence applications. Thin-film transistors have a role to play in enabling high processing power with low resource use. We can now see that MMTs, a unique type of thin-film transistor, invented at the University of Surrey, have the reliability and uniformity needed to fulfil this role.”
Dr Radu Sporea, Senior Lecturer at the University of Surrey’s Advanced Technology Institute, said:
“These findings are a reminder of how Surrey is a leader in AI research. Many of my colleagues focus on people-centred AI and how best to maximise the benefits for humans, including how to apply these new concepts ethically. Our research at the Advanced Technology Institute takes forward the physical implementation, as a stepping stone towards powerful yet affordable next-generation hardware. It’s fantastic that collaboration is resulting in such successes with researchers involved at all levels, from undergraduates like Isin when she led this research, to seasoned experts.”
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Materials provided by University of Surrey. Note: Content may be edited for style and length. More

Decoding letters into sound is a key point in learning to read but is not enough to master it. “Reading calls upon several other essential mechanisms that we don’t necessarily think about, such as knowing how to move our eyes on the page or how to use our working memory to link words together in a coherent sentence,” points out Daphné Bavelier, a professor in the Psychology Section of the Faculty of Psychology and Educational Sciences (FPSE) at the UNIGE. “These other skills, such as vision, the deployment of attention, working memory, and cognitive flexibility, are known to be improved by action video games,” explains Angela Pasqualotto, first author of this study, which is based on her PhD thesis at the Department of Psychology and Cognitive Science of the University of Trento under the direction of Professors Venuti and De Angeli.
A child-friendly action video game to support learning
With this in mind, a video game was designed that combines action video games with mini games that train different executive functions, such as working memory, inhibition and cognitive flexibility, functions that are called upon during reading. “The universe of this game is an alternative world in which the child, accompanied by his Raku, a flying creature, must carry out different missions to save planets and progress in the game,” Angela Pasqualotto adds. The idea is to reproduce the components of an action game, without incorporating violence, so that it is suitable for young children. “For example, the Raku flies through a meteor shower, moving around to avoid those or aiming at them to weaken their impact, while collecting useful resources for the rest of the game, a bit like what you find in action video games.”
The scientists then worked with 150 Italian schoolchildren aged 8 to 12, divided into two groups: the first one played the video game developed by the team, and the second one played Scratch, a game that teaches children how to code. Both games require attentional control and executive functions, but in different manners. The action video game requires children to perform tasks within a time limit such as remembering a sequence of symbols or responding only when the Raku makes a specific sound while increasing the difficulty of these tasks according to the child’s performance. Scratch, the control game, requires planning, reasoning and problem solving. Children must manipulate objects and logical structures to establish the desired programming sequence.
“First, we tested the children’s ability to read words, non-words and paragraphs, and also we conducted an attention test that measures the child’s attentional control, a capacity we know is trained by action video games,” explains Daphne Bavelier. The children then followed the training with either the action video game or the control game, for six weeks, two hours a week under supervision at school. Children were tested at school by clinicians of the Laboratory of Observation Diagnosis and Education (UNITN).
Long-term improvement in reading skills
Shortly after the end of the training, the scientists repeated the tests on both groups of children. “We found a 7-fold improvement in attentional control in the children who played the action video game compared to the control group,” says Angela Pasqualotto. Even more remarkably, the research team observed a clear enhancement in reading, not only in terms of reading speed, but also in accuracy, whereas no improvement was noted for the control group. This improvement in literacy occurs even though the action video game does not require any reading activity.
“What is particularly interesting about this study is that we carried out three further assessment tests at 6 months, 12 months and 18 months after training. On each occasion, the trained children performed better than the control group, which proves that these improvements were sustained,” Angela Pasqualotto says. Moreover, the grades in Italian of the trained children became significantly better over time, showing a virtuous improvement in learning ability. “The effects are thus long-term, in line with the action video game strengthening the ability to learn how to learn,” says Daphne Bavelier.
Within the framework of the NCCR Evolving Language and in collaboration with Irene Altarelli (co-author of the article and researcher at LaPsyDE, University of Paris), the game will be adapted into German, French and English. “When reading, decoding is more or less difficult depending on the language. Italian, for example, is very transparent — each letter is pronounced — whereas French and English are quite opaque, resulting in rather different learning challenges. Reading in opaque languages requires the ability to learn exceptions, to learn how a variety of contexts impacts pronunciation and demands greater reliance on memorization,” comments Irene Altarelli. Will the benefits of action video games on reading acquisition extend to such complex learning environments as reading in French or English? This is the question that this study will help answer. In addition, the video game will be available entirely at home, remotely, as will the administration of reading and attention tests, in order to complement school lessons, rather than taking time out of school hours. More

Ecologists need to understand wild animal behaviours in order to conserve species, but following animals around can be expensive, dangerous, or sometimes impossible in the case of animals that move underwater or into areas we can’t reach easily.
Scientists turned to the next best thing: bio-logging devices that can be attached to animals and capture information about movement, breathing rate, heart rate, and more.
However, retrieving an accurate picture of what a tagged animal does as it journeys through its environment requires statistical analysis, especially when it comes to animal movement, and the methods statisticians use are always evolving to make full use of the large and complex data sets that are available.
A recent study by researchers at the Institute for the Oceans and Fisheries (IOF) and the UBC department of statistics has taken us a step closer to understanding the behaviours of northern resident killer whales by improving statistical tools useful for identifying animal behaviours that can’t be observed directly.
“The thing we really tackled with this paper was trying to get at some of those fine-scale behaviours that aren’t that easy to model,” said Evan Sidrow, a doctoral student in the department of statistics and the study’s lead author. “It’s a matter of finding behaviours on the order of seconds — maybe 10 to 15 seconds. Usually, it’s a matter of a whale looking around, and then actively swimming for a second to get over to a new location. We are trying to observe fleeting behaviours, like a whale catching a fish.”
The research team improved a statistical tool that is based on what is called a hidden Markov model, which is helpful for unlocking the mysteries hidden inside animal movement datasets. More