Aurelia Butler

Scientists from SANKEN at Osaka University demonstrated the readout of spin-polarized multielectron states composed of three or four electrons on a semiconductor quantum dot. By making use of the spin filtering caused by the quantum Hall effect, the researchers were able to improve upon previous methods that could only easily resolve two electrons. This work may lead to quantum computers based on the multielectron high-spin states.
Despite the almost unimaginable increase in the power of computers over the last 75 years, even the fastest machines available today run on the same basic principle as the original room-sized collection of vacuum tubes: information is still processed by herding electrons through circuits based on their electric charge. However, computer manufacturers are rapidly reaching the limit of how much they can readily achieve with charge alone, and new methods, such as quantum computing, are not ready yet to take their place. One promising approach is to utilize the intrinsic magnetic moment of electrons, called “spin,” but controlling and measuring these values has proven to be very challenging.
Now, a team of researchers led by Osaka University showed how to read out the spin state of multiple electrons confined to a tiny quantum dot fabricated from gallium and arsenic. Quantum dots act like artificial atoms with properties that can be tuned by scientists by changing their size or composition. However, the gaps in energy levels generally becomes smaller and harder to resolve as the number of trapped electrons increases.
To overcome this, the team took advantage of a phenomenon called the quantum Hall effect. When electrons are confined to two dimensions and subjected to a strong magnetic field, their states become quantized, so their energy levels can only take on certain specific values. “Previous spin readout methods could only handle one or two electrons, but using the quantum Hall effect, we were able to resolve up to four spin-polarized electrons,” first author Haruki Kiyama says. To prevent disturbances from thermal fluctuations, the experiments were performed at extremely low temperatures, around 80 millikelvin. “This readout technique may pave the way toward faster and higher-capacity spin-based quantum information processing devices with multielectron spin states,” senior author Akira Oiwa says.
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Whether a robot or a person delivers your package, the carbon footprint would essentially be the same, according to a University of Michigan study that could help inform the future of automated delivery as the pandemic fuels a dramatic rise in online shopping.
The researchers examined the environmental impacts of advanced residential package delivery scenarios that use electric and gas-powered autonomous vehicles and two-legged robots to ferry goods from delivery hubs to neighborhoods, and then to front doors. They compared those impacts with the traditional approach of a human driver who hand-delivers parcels.
They found that while robots and automation contribute less than 20% of a package’s footprint, most of the greenhouse gas emissions come from the vehicle. Vehicle powertrain and fuel economy are the key factors determining the package’s footprint. Switching to electric vehicles and reducing the carbon intensity of the electricity they run on could have the biggest impacts in sustainable parcel delivery, the researchers say.
Their study is a life cycle analysis of the cradle-to-grave greenhouse gas emissions for 12 suburban delivery scenarios. It’s unique in that it doesn’t just tally emissions from the delivery process. It also counts greenhouse gases from manufacturing the vehicles and robots, as well as disposing of them or recycling them at the end of their lives.
“We found that the energy and carbon footprints of this automated parcel delivery in suburban areas was similar to that of conventional human driven vehicles. The advantages of better fuel economy through vehicle automation were offset by greater electricity loads from automated vehicle power requirements,” said Gregory Keoleian, the Peter M. Wege Endowed Professor of Sustainable Systems at the U-M School for Environment and Sustainability and a professor of civil and environmental engineering.
“For all delivery systems studied, the vehicle-use phase is the single largest contributor to greenhouse gas emissions, highlighting the need for low-carbon fuels for sustainable parcel delivery. It is critically important to decarbonize grids while deploying electrified vehicles.”
Optimizing ‘the last mile’ in a surging package delivery market More

An international study led by the University of Bonn has found evidence of a long-sought effect in accelerator data. The so-called “triangle singularity” describes how particles can change their identities by exchanging quarks, thereby mimicking a new particle. The mechanism also provides new insights into a mystery that has long puzzled particle physicists: Protons, neutrons and many other particles are much heavier than one would expect. This is due to peculiarities of the strong interaction that holds the quarks together. The triangle singularity could help to better understand these properties. The publication is now available in Physical Review Letters.
In their study, the researchers analyzed data from the COMPASS experiment at the European Organization for Nuclear Research CERN in Geneva. There, certain particles called pions are brought to extremely high velocities and shot at hydrogen atoms.
Pions consist of two building blocks, a quark and an anti-quark. These are held together by the strong interaction, much like two magnets whose poles attract each other. When magnets are moved away from each other, the attraction between them decreases successively. With the strong interaction it is different: It increases in line with the distance, similar to the tensile force of a stretching rubber band.
However, the impact of the pion on the hydrogen nucleus is so strong that this rubber band breaks. The “stretching energy” stored in it is released all at once. “This is converted into matter, which creates new particles,” explains Prof. Dr. Bernhard Ketzer of the Helmholtz Institute for Radiation and Nuclear Physics at the University of Bonn. “Experiments like these therefore provide us with important information about the strong interaction.”
Unusual signal
In 2015, COMPASS detectors registered an unusual signal after such a crash test. It seemed to indicate that the collision had created an exotic new particle for a few fractions of a second. “Particles normally consist either of three quarks — this includes the protons and neutrons, for example — or, like the pions, of one quark and one antiquark,” says Ketzer. “This new short-lived intermediate state, however, appeared to consist of four quarks.”
Together with his research group and colleagues at the Technical University of Munich, the physicist has now put the data through a new analysis. “We were able to show that the signal can also be explained in a different way, that is, by the aforementioned triangle singularity,” he stresses. This mechanism was postulated as early as the 1950s by the Russian physicist Lev Davidovich Landau, but has not yet been proven directly.
According to this, the particle collision did not produce a tetraquark at all, but a completely normal quark-antiquark intermediate. This, however, disintegrated again straight away, but in an unusual manner: “The particles involved exchanged quarks and changed their identities in the process,” says Ketzer, who is also a member of the Transdisciplinary Research Area “Building Blocks of Matter and Fundamental Interactions” (TRA Matter). “The resulting signal then looks exactly like that from a tetraquark with a different mass.” This is the first time such a triangle singularity has been detected directly mimicking a new particle in this mass range. The result is also interesting because it allows new insights into the nature of the strong interaction.
Only a small fraction of the proton mass can be explained by Higgs mechanism
Protons, neutrons, pions and other particles (called hadrons) have mass. They get this from the so-called Higgs mechanism, but obviously not exclusively: A proton has about 20 times more mass than can be explained by the Higgs mechanism alone. “The much bigger part of the mass of hadrons is due to the strong interaction,” Ketzer explains. “Exactly how the masses of hadrons come about, however, is not yet clear. Our data help us to better understand the properties of the strong interaction, and perhaps the ways in which it contributes to the mass of particles.”
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Research led by a Wayne State University Department of Mathematics professor is aiding researchers in Wayne State’s Department of Psychiatry and Behavioral Neurosciences in analyzing fMRI data. fMRI is the preeminent class of signals collected from the brain in vivo and is irreplaceable in the study of brain dysfunction in many medical fields, including psychiatry, neurology and pediatrics.
Andrew Salch, Ph.D., associate professor of mathematics in Wayne State’s College of Liberal Arts and Sciences, is leading the multidisciplinary team that is investigating how concepts of topological data analysis, a subfield of mathematics, can be applied to recovering “hidden” structure in fMRI data.
“We hypothesized that aspects of the fMRI signal are not easily discoverable using many of the standard tools used for fMRI data analysis, which strategically reduce the number of dimensions in the data to be considered. Consequently, these aspects might be uncovered using concepts from the mathematical field of topological data analysis, also called TDA, which is intended for use on high-dimensional data sets,” said Salch. “The high dimensionality that characterizes fMRI data includes the three dimensions of space — that is, where in the brain the signal is being acquired — time — or how the signal varies as brain states change in time — and signal intensity — or how the strength of the fMRI signal changes in response to the task. When related to task-induced changes, the results reflect biologically meaningful aspects of brain function and dysfunction. This is a unique collaborative work focused on the complexities of both TDA and fMRI respectively, show how TDA can be applied to real fMRI data collected, and provide open access computational software we have developed for implementing the analyses.”
The research article, “From mathematics to medicine: A practical primer on topological data analysis and the development of related analytic tools for the functional discovery of latent structure in fMRI data,” appears in the Aug. 12 issue of PLOS ONE.
In it, the team used TDA to discover data structures in the anterior cingulate cortex, a critical control region in the brain. These structures — called non-contractible loops in TDA — appeared in specific conditions of the experiment, and were not identified using conventional techniques for fMRI analyses.
“We expect this work to become a citation classic,” said Vaibhav Diwadkar, Ph.D., professor of psychiatry and behavioral neurosciences and research collaborator. “Instead of merely applying TDA to fMRI, we provide a lucid argument for why medical researchers who use fMRI should consider using TDA, and why topologists should turn their attention to the study of complex fMRI data. Moreover, this important work provides readers with empirical demonstrations of such applications, and we provide potential users with the tools we used so they can in turn apply it to their own data.”
“Our ongoing research utilizing TDA with fMRI will provide a unique and complementary method for assessing brain function, and will give medical researchers greater flexibility in tackling complex properties in their data,” said Salch. “In particular, our work will help fMRI researchers become aware of the significant power of TDA that is designed to address complexity in data, and will enhance the value of using fMRI in neuroscience and medicine.”
In addition to Salch and Diwadkar, co-authors on the paper include Adam Regalski, Wayne State mathematics graduate student; Hassan Abdallah, Wayne State mathematics department alumni and current graduate student at the University of Michigan; and Michael Catanzaro, assistant professor of mathematics at Iowa State University and Wayne State mathematics department alumni.
This work is supported by the National Institutes of Health (MH111177 and MH059299), the Jack Dorsey Endowment, the Cohen Neuroscience Endowment, and the Lycaki-Young Funds from the State of Michigan. More

Wearable health technologies are vastly popular with people wanting to improve their physical and mental health. Everything from exercise, sleep patterns, calories consumed and heart rhythms can be tracked by a wearable device.
But timely and accurate data is also especially valuable for doctors treating patients with complicated health conditions using virtual care.
A new study from the Southern Medical Program (SMP), based at UBC Okanagan, has examined the use of wearable health technology and telehealth to treat patients with Parkinson’s disease.
Dr. Daryl Wile, a movement disorder specialist and SMP clinical assistant professor, routinely uses telehealth to connect with Parkinson’s patients across the vast and rugged landscape of BC’s Interior.
“Even prior to the pandemic, telehealth helped deliver specialized care to patients living in remote and rural settings,” says Wile, a clinical investigator with the Centre for Chronic Disease Prevention and Management. “But with the complex nature of Parkinson’s, we wanted to enhance these appointments to better understand how movements vary throughout a patient’s entire day.”
To add a new layer of health information, Wile and the research team added wearable technology to the equation.
“We recruited Parkinson’s patients with either tremors or involuntary movements,” says Joshua Yoneda, SMP student and co-author of the study. “We then divided them into two groups — some using telehealth and device-based health tracking and others attending traditional face-to-face appointments.”
The telehealth group wore wearable devices to track their movements, involuntary or not, throughout waking hours. The reported data was then reviewed during telehealth appointments to identify peak times patients experienced Parkinson’s symptoms.
“With the integration of accurate and reliable data from wearable devices, we were able to tailor a patient’s medication to better manage their symptoms throughout the day,” adds Wile.
As part of the study, patients were asked a series of questions from the standardized Parkinson Disease Quality of Life Index. Both study groups were assessed at intervals of six weeks, three months and six months.
Overall, the patients using the wearable devices reported positive experiences and health outcomes in combination with telehealth appointments to access specialized care.
“There’s definitely a strong case to leverage multiple technologies to improve a patient’s quality of life and limit the added stress and cost associated with travel,” says Yoneda.
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Sea cucumbers have a bumpy and oblong shape. They are soft but stiffen up quickly when touched. They can shrink or stretch to several meters, and their original shape can be recovered even after they die and shrivel up with the regulation of water uptake. Recently, a POSTECH research team has developed a soft actuator inspired by this unique behavior of sea cucumbers.
A research team led by Professor Dong Sung Kim, Dr. Andrew Choi (currently the director of R&D at EDmicBio, Inc.), and Hyeonseok Han of POSTECH’s Department of Mechanical Engineering was inspired by the mutable collagenous tissue (MCT) of sea cucumbers to develop a water-driven self-operating soft actuator that exceeds the strength and speed of conventional soft actuators. This research was published as the inside front cover paper in the latest issue of Journal of Materials Chemistry A.
The body of a sea cucumber is made of MCT; and thus, it can be hardened or softened according to the surrounding environment. In a matter of a few seconds, the elastic modulus of sea cucumbers can change up to 10 times to quickly squeeze through crevices or inflate to threaten predators. This change is induced by the formation or destruction of hydrogen bonds in collagenous tissues by controlling its chemical regulators.
An actuator is a rigid device that alters a physical state by using an electrical signal change, such as a motor or a switch. However, a soft actuator that responds to water – which uses water as an energy source – can be applied to soft robotics that requires freedom in movement. However, the existing soft actuators are limited in their application due to their fragility and slow speed.
Inspired by the MCT of sea cucumbers that freely change shape by reacting with water, the research team designed an actuator to be programmable. This actuator is based on the bulk PNIPAAm hydrogel that changes very flexibly and showed an actuation force 200 times (2 newtons) greater and an actuation force 300 times (1/3 second) faster than the conventional soft actuators that use water as an energy source – even underwater at 80°C temperature. In addition, through several tests, it was demonstrated that the actuator was robust enough to restore the original shape even when subjected to 300% of tensile strain.
This actuator can be applicable in many different sectors such as industrial and biomedical fields, including industrial robots such as grippers that grab and lift materials like a human arm, wound closures, and artificial fingers.
“The soft robot activates when it comes in contact with moisture and is flexible and deformable to easily adapt to various environments,” explained Professor Dong Sung Kim. “This newly developed hydrogel actuator is very powerful and actuates quickly to enable operation even in places without electricity by using chemical energy.”
This research was conducted with the support of the Mid-career Researcher Program and the Core Technology Biomedical Development Program funded by the Ministry of Science and ICT and the National Research Foundation of Korea, and the Alchemist Project funded by the Ministry of Trade, Industry and Energy.
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Violent activity on our Sun leads to some of the most extreme space weather events on Earth, impacting systems such as satellites, communications systems, power distribution and aviation. The roughly 11 year cycle of solar activity has three ‘seasons’, each of which affects the space weather felt at Earth differently: (i) solar maximum, the sun is active and disordered, when space weather is stormy and events are irregular (ii) the declining phase, when the sun and solar wind becomes ordered, and space weather is more moderate and (iii) solar minimum, when activity is quiet.
In a new study led by the University of Warwick and published in The Astrophysical Journal, scientists found that the change from solar maximum to the declining phase is fast, happening within a few (27 day) solar rotations. They also showed that the declining phase is twice as long in even-numbered solar cycles as it is in odd-numbered cycles.
No two solar cycles are the same in amplitude or duration. To study the solar seasons, the scientists built a sun clock from the daily sunspot number record available since 1818. This maps the irregular solar cycles onto a regular clock. The magnetic polarity of the sun reverses after each roughly 11 year solar cycle giving a roughly 22 year magnetic cycle (named after George Ellery Hale) and to explore this, a 22 year clock was constructed. The effect on space weather at earth can be tracked back using the longest continuous records of geomagnetic activity over the past 150 years, and once the clock is constructed, it can be used to study multiple observations of seasonal solar activity which affect the earth.
With the greater detail afforded by the sun clock, the scientists could see that the switch from solar maximum to the declining phase is fast, occurring within a few (27 day) solar rotations. There was also a clear difference in the duration of the declining phase when the sun’s magnetic polarity is ‘up’ compared to ‘down’: in even-numbered cycles it is around twice as long as odd-numbered cycles. As we are about to enter cycle 25, the scientists anticipate that the next declining phase will be short.
Lead author Professor Sandra Chapman of the University of Warwick Department of Physics said: “By combining well known methods in a new way, our clock resolves changes in the Sun’s climate to within a few solar rotations. Then you find the changes between some phases can be really sharp.
“If you know you’ve had a long cycle, you know the next one’s going to be short, we can estimate how long it’s going to last. Knowing the timing of the climate seasons helps to plan for space weather. Operationally it is useful to know when conditions will be active or quiet, for satellites, power grids, communications.”
The results also provide a clue to understanding how the Sun reverses polarity after every cycle.
Professor Chapman adds: “I also think it is remarkable that something the size of the sun can flip its magnetic field every 11 years, and going down-up is different to going up-down. Somehow the sun ‘knows which way up it is’, and this is an intriguing problem, at the heart of how the sun generates its magnetic field.”
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