Stunning simulation of stars being born is most realistic ever

A team including Northwestern University astrophysicists has developed the most realistic, highest-resolution 3D simulation of star formation to date. The result is a visually stunning, mathematically-driven marvel that allows viewers to float around a colorful gas cloud in 3D space while watching twinkling stars emerge.

Called STARFORGE (Star Formation in Gaseous Environments), the computational framework is the first to simulate an entire gas cloud -- 100 times more massive than previously possible and full of vibrant colors -- where stars are born.

It also is the first simulation to simultaneously model star formation, evolution and dynamics while accounting for stellar feedback, including jets, radiation, wind and nearby supernovae activity. While other simulations have incorporated individual types of stellar feedback, STARFORGE puts them altogether to simulate how these various processes interact to affect star formation.

Using this beautiful virtual laboratory, the researchers aim to explore longstanding questions, including why star formation is slow and inefficient, what determines a star's mass and why stars tend to form in clusters.

The researchers have already used STARFORGE to discover that protostellar jets -- high-speed streams of gas that accompany star formation -- play a vital role in determining a star's mass. By calculating a star's exact mass, researchers can then determine its brightness and internal mechanisms as well as make better predictions about its death.

Newly accepted by the Monthly Notices of the Royal Astronomical Society, an advanced copy of the manuscript, detailing the research behind the new model, appeared online today. An accompanying paper, describing how jets influence star formation, was published in the same journal in February 2021.

"People have been simulating star formation for a couple decades now, but STARFORGE is a quantum leap in technology," said Northwestern's Michael Grudi?, who co-led the work. "Other models have only been able to simulate a tiny patch of the cloud where stars form -- not the entire cloud in high resolution. Without seeing the big picture, we miss a lot of factors that might influence the star's outcome."

"How stars form is very much a central question in astrophysics," said Northwestern's Claude-André Faucher-Giguère, a senior author on the study. "It's been a very challenging question to explore because of the range of physical processes involved. This new simulation will help us directly address fundamental questions we could not definitively answer before."

Grudi? is a postdoctoral fellow at Northwestern's Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA). Faucher-Giguère is an associate professor of physics and astronomy at Northwestern's Weinberg College of Arts and Sciences and member of CIERA. Grudi? co-led the work with Dávid Guszejnov, a postdoctoral fellow at the University of Texas at Austin.

From start to finish, star formation takes tens of millions of years. So even as astronomers observe the night sky to catch a glimpse of the process, they can only view a brief snapshot.

"When we observe stars forming in any given region, all we see are star formation sites frozen in time," Grudi? said. "Stars also form in clouds of dust, so they are mostly hidden."

For astrophysicists to view the full, dynamic process of star formation, they must rely on simulations. To develop STARFORGE, the team incorporated computational code for multiple phenomena in physics, including gas dynamics, magnetic fields, gravity, heating and cooling and stellar feedback processes. Sometimes taking a full three months to run one simulation, the model requires one of the largest supercomputers in the world, a facility supported by the National Science Foundation and operated by the Texas Advanced Computing Center.

The resulting simulation shows a mass of gas -- tens to millions of times the mass of the sun -- floating in the galaxy. As the gas cloud evolves, it forms structures that collapse and break into pieces, which eventually form individual stars. Once the stars form, they launch jets of gas outward from both poles, piercing through the surrounding cloud. The process ends when there is no gas left to form anymore stars.

Already, STARFORGE has helped the team discover a crucial new insight into star formation. When the researchers ran the simulation without accounting for jets, the stars ended up much too large -- 10 times the mass of the sun. After adding jets to the simulation, the stars' masses became much more realistic -- less than half the mass of the sun.

"Jets disrupt the inflow of gas toward the star," Grudi? said. "They essentially blow away gas that would have ended up in the star and increased its mass. People have suspected this might be happening, but, by simulating the entire system, we have a robust understanding of how it works."

Beyond understanding more about stars, Grudi? and Faucher-Giguère believe STARFORGE can help us learn more about the universe and even ourselves.

"Understanding galaxy formation hinges on assumptions about star formation," Grudi? said. "If we can understand star formation, then we can understand galaxy formation. And by understanding galaxy formation, we can understand more about what the universe is made of. Understanding where we come from and how we're situated in the universe ultimately hinges on understanding the origins of stars."

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Supermassive black holes devour gas just like their petite counterparts

 On Sept. 9, 2018, astronomers spotted a flash from a galaxy 860 million light years away. The source was a supermassive black hole about 50 million times the mass of the sun. Normally quiet, the gravitational giant suddenly awoke to devour a passing star in a rare instance known as a tidal disruption event. As the stellar debris fell toward the black hole, it released an enormous amount of energy in the form of light.

Researchers at MIT, the European Southern Observatory, and elsewhere used multiple telescopes to keep watch on the event, labeled AT2018fyk. To their surprise, they observed that as the supermassive black hole consumed the star, it exhibited properties that were similar to that of much smaller, stellar-mass black holes.

The results, published today in the Astrophysical Journal, suggest that accretion, or the way black holes evolve as they consume material, is independent of their size.

"We've demonstrated that, if you've seen one black hole, you've seen them all, in a sense," says study author Dheeraj "DJ" Pasham, a research scientist in MIT's Kavli Institute for Astrophysics and Space Research. "When you throw a ball of gas at them, they all seem to do more or less the same thing. They're the same beast in terms of their accretion."

Pasham's co-authors include principal research scientist Ronald Remillard and former graduate student Anirudh Chiti at MIT, along with researchers at the European Southern Observatory, Cambridge University, Leiden University, New York University, the University of Maryland, Curtin University, the University of Amsterdam, and the NASA Goddard Space Flight Center.

A stellar wake-up

When small stellar-mass black holes with a mass about 10 times our sun emit a burst of light, it's often in response to an influx of material from a companion star. This outburst of radiation sets off a specific evolution of the region around the black hole. From quiescence, a black hole transitions into a "soft" phase dominated by an accretion disk as stellar material is pulled into the black hole. As the amount of material influx drops, it transitions again to a "hard" phase where a white-hot corona takes over. The black hole eventually settles back into a steady quiescence, and this entire accretion cycle can last a few weeks to months.

Physicists have observed this characteristic accretion cycle in multiple stellar-mass black holes for several decades. But for supermassive black holes, it was thought that this process would take too long to capture entirely, as these goliaths are normally grazers, feeding slowly on gas in the central regions of a galaxy.

"This process normally happens on timescales of thousands of years in supermassive black holes," Pasham says. "Humans cannot wait that long to capture something like this."

But this entire process speeds up when a black hole experiences a sudden, huge influx of material, such as during a tidal disruption event, when a star comes close enough that a black hole can tidally rip it to shreds.

"In a tidal disruption event, everything is abrupt," Pasham says. "You have a sudden chunk of gas being thrown at you, and the black hole is suddenly woken up, and it's like, 'whoa, there's so much food -- let me just eat, eat, eat until it's gone.' So, it experiences everything in a short timespan. That allows us to probe all these different accretion stages that people have known in stellar-mass black holes."

A supermassive cycle

In September 2018, the All-Sky Automated Survey for Supernovae (ASASSN) picked up signals of a sudden flare. Scientists subsequently determined that the flare was the result of a tidal disruption event involving a supermassive black hole, which they labeled TDE AT2018fyk. Wevers, Pasham, and their colleagues jumped at the alert and were able to steer multiple telescopes, each trained to map different bands of the ultraviolet and X-ray spectrum, toward the system.

The team collected data over two years, using X-ray space telescopes XMM-Newton and the Chandra X-Ray Observatory, as well as NICER, the X-ray-monitoring instrument aboard the International Space Station, and the Swift Observatory, along with radio telescopes in Australia.

"We caught the black hole in the soft state with an accretion disk forming, and most of the emission in ultraviolet, with very few in the X-ray," Pasham says. "Then the disk collapses, the corona gets stronger, and now it's very bright in X-rays. Eventually there's not much gas to feed on, and the overall luminosity drops and goes back to undetectable levels."

The researchers estimate that the black hole tidally disrupted a star about the size of our sun. In the process, it generated an enormous accretion disk, about 12 billion kilometers wide, and emitted gas that they estimated to be about 40,000 Kelvin, or more than 70,000 degrees Fahrenheit. As the disk became weaker and less bright, a corona of compact, high-energy X-rays took over as the dominant phase around the black hole before eventually fading away.

"People have known this cycle to happen in stellar-mass black holes, which are only about 10 solar masses. Now we are seeing this in something 5 million times bigger," Pasham says.

"The most exciting prospect for the future is that such tidal disruption events provide a window into the formation of complex structures very close to the supermassive black hole such as the accretion disk and the corona," says lead author Thomas Wevers, a fellow at the European Southern Observatory. "Studying how these structures form and interact in the extreme environment following the destruction of a star, we can hopefully start to better understand the fundamental physical laws that govern their existence."

In addition to showing that black holes experience accretion in the same way, regardless of their size, the results represent only the second time that scientists have captured the formation of a corona from beginning to end.

"A corona is a very mysterious entity, and in the case of supermassive black holes, people have studied established coronas but don't know when or how they formed," Pasham says. "We've demonstrated you can use tidal disruption events to capture corona formation. I'm excited about using these events in the future to figure out what exactly is the corona."

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Engineers harvest WiFi signals to power small electronics

With the rise of the digital age, the amount of WiFi sources to transmit information wirelessly between devices has grown exponentially. This results in the widespread use of the 2.4GHz radio frequency that WiFi uses, with excess signals available to be tapped for alternative uses.

To harness this under-utilised source of energy, a research team from the National University of Singapore (NUS) and Japan's Tohoku University (TU) has developed a technology that uses tiny smart devices known as spin-torque oscillators (STOs) to harvest and convert wireless radio frequencies into energy to power small electronics. In their study, the researchers had successfully harvested energy using WiFi-band signals to power a light-emitting diode (LED) wirelessly, and without using any battery.

"We are surrounded by WiFi signals, but when we are not using them to access the Internet, they are inactive, and this is a huge waste. Our latest result is a step towards turning readily-available 2.4GHz radio waves into a green source of energy, hence reducing the need for batteries to power electronics that we use regularly. In this way, small electric gadgets and sensors can be powered wirelessly by using radio frequency waves as part of the Internet of Things. With the advent of smart homes and cities, our work could give rise to energy-efficient applications in communication, computing, and neuromorphic systems," said Professor Yang Hyunsoo from the NUS Department of Electrical and Computer Engineering, who spearheaded the project.

The research was carried out in collaboration with the research team of Professor Guo Yong Xin, who is also from the NUS Department of Electrical and Computer Engineering, as well as Professor Shunsuke Fukami and his team from TU. The results were published in Nature Communications on 18 May 2021.

Converting WiFi signals into usable energy

Spin-torque oscillators are a class of emerging devices that generate microwaves, and have applications in wireless communication systems. However, the application of STOs is hindered due to a low output power and broad linewidth.

While mutual synchronisation of multiple STOs is a way to overcome this problem, current schemes, such as short-range magnetic coupling between multiple STOs, have spatial restrictions. On the other hand, long-range electrical synchronisation using vortex oscillators is limited in frequency responses of only a few hundred MHz. It also requires dedicated current sources for the individual STOs, which can complicate the overall on-chip implementation.

To overcome the spatial and low frequency limitations, the research team came up with an array in which eight STOs are connected in series. Using this array, the 2.4 GHz electromagnetic radio waves that WiFi uses was converted into a direct voltage signal, which was then transmitted to a capacitor to light up a 1.6-volt LED. When the capacitor was charged for five seconds, it was able to light up the same LED for one minute after the wireless power was switched off.

In their study, the researchers also highlighted the importance of electrical topology for designing on-chip STO systems, and compared the series design with the parallel one. They found that the parallel configuration is more useful for wireless transmission due to better time-domain stability, spectral noise behaviour, and control over impedance mismatch. On the other hand, series connections have an advantage for energy harvesting due to the additive effect of the diode-voltage from STOs.

Commenting on the significance of their results, Dr Raghav Sharma, the first author of the paper, shared, "Aside from coming up with an STO array for wireless transmission and energy harvesting, our work also demonstrated control over the synchronising state of coupled STOs using injection locking from an external radio-frequency source. These results are important for prospective applications of synchronised STOs, such as fast-speed neuromorphic computing."

Next steps

To enhance the energy harvesting ability of their technology, the researchers are looking to increase the number of STOs in the array they had designed. In addition, they are planning to test their energy harvesters for wirelessly charging other useful electronic devices and sensors.

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Proteins that predict future dementia, Alzheimer's risk, identified

The development of dementia, often from Alzheimer's disease, late in life is associated with abnormal blood levels of dozens of proteins up to five years earlier, according to a new study led by researchers at the Johns Hopkins Bloomberg School of Public Health. Most of these proteins were not known to be linked to dementia before, suggesting new targets for prevention therapies.

The findings are based on new analyses of blood samples of over ten thousand middle-aged and elderly people -- samples that were taken and stored during large-scale studies decades ago as part of an ongoing study. The researchers linked abnormal blood levels of 38 proteins to higher risks of developing Alzheimers within five years. Of those 38 proteins, 16 appeared to predict Alzheimer's risk two decades in advance.

Although most of these risk markers may be only incidental byproducts of the slow disease process that leads to Alzheimer's, the analysis pointed to high levels of one protein, SVEP1, as a likely causal contributor to that disease process.

The study was published May 14 in Nature Aging.

"This is the most comprehensive analysis of its kind to date, and it sheds light on multiple biological pathways that are connected to Alzheimer's," says study senior author Josef Coresh, MD, PhD, MHS, George W. Comstock Professor in the Department of Epidemiology at the Bloomberg School. "Some of these proteins we uncovered are just indicators that disease might occur, but a subset may be causally relevant, which is exciting because it raises the possibility of targeting these proteins with future treatments."

More than six million Americans are estimated to have Alzheimer's, the most common type of dementia, an irreversible fatal condition that leads to loss of cognitive and physical function. Despite decades of intensive study, there are no treatments that can slow the disease process, let alone stop or reverse it. Scientists widely assume that the best time to treat Alzheimer's is before dementia symptoms develop.

Efforts to gauge people's Alzheimer's risk before dementia arises have focused mainly on the two most obvious features of Alzheimer's brain pathology: clumps of amyloid beta protein known as plaques, and tangles of tau protein. Scientists have shown that brain imaging of plaques, and blood or cerebrospinal fluid levels of amyloid beta or tau, have some value in predicting Alzheimer's years in advance.

But humans have tens of thousands of other distinct proteins in their cells and blood, and techniques for measuring many of these from a single, small blood sample have advanced in recent years. Would a more comprehensive analysis using such techniques reveal other harbingers of Alzheimer's? That's the question Coresh and colleagues sought to answer in this new study.

The researchers' initial analysis covered blood samples taken during 2011-13 from more than 4,800 late-middle-aged participants in the Atherosclerosis Risk in Communities (ARIC) study, a large epidemiological study of heart disease-related risk factors and outcomes that has been running in four U.S. communities since 1985. Collaborating researchers at a laboratory technology company called SomaLogic used a technology they recently developed, SomaScan, to record levels of nearly 5,000 distinct proteins in the banked ARIC samples.

The researchers analyzed the results and found 38 proteins whose abnormal levels were significantly associated with a higher risk of developing Alzheimer's in the five years following the blood draw.

They then used SomaScan to measure protein levels from more than 11,000 blood samples taken from much younger ARIC participants in 1993-95. They found that abnormal levels of 16 of the 38 previously identified proteins were associated with the development of Alzheimer's in the nearly two decades between that blood draw and a follow-up clinical evaluation in 2011-13.

To verify these findings in a different patient population, the scientists reviewed the results of an earlier SomaScan of blood samples taken in 2002-06 during an Icelandic study. That study had assayed proteins including 13 of the 16 proteins identified in the ARIC analyses. Of those 13 proteins, six were again associated with Alzheimer's risk over a roughly 10-year follow-up period.

In a further statistical analysis, the researchers compared the identified proteins with data from past studies of genetic links to Alzheimer's. The comparison suggested strongly that one of the identified proteins, SVEP1, is not just an incidental marker of Alzheimer's risk but is involved in triggering or driving the disease.

SVEP1 is a protein whose normal functions remain somewhat mysterious, although in a study published earlier this year it was linked to the thickened artery condition, atherosclerosis, which underlies heart attacks and strokes.

Other proteins associated with Alzheimer's risk in the new study included several key immune proteins -- which is consistent with decades of findings linking Alzheimer's to abnormally intense immune activity in the brain.

The researchers plan to continue using techniques like SomaScan to analyze proteins in banked blood samples from long-term studies to identify potential Alzheimer's-triggering pathways -- a potential strategy to suggest new approaches for Alzheimer's treatments.

The scientists have also been studying how protein levels in the ARIC samples are linked to other diseases such as vascular (blood vessel-related) disease in the brain, heart and the kidney.

First author Keenan Walker, PhD, worked on this analysis while on faculty at the Johns Hopkins University School of Medicine and the Bloomberg School's Welch Center for Prevention, Epidemiology and Clinical Research. He is currently an investigator with the National Institute of Aging's Intramural Research Program.

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Trace gases from ocean are source of particles accelerating Antarctic climate change

Scientists exploring the drivers of Antarctic climate change have discovered a new and more efficient pathway for the creation of natural aerosols and clouds which contribute significantly to temperature increases.

The Antarctic Peninsula has shown some of the largest global increases in near-surface air temperature over the last 50 years, but experts have struggled to predict temperatures because little was known about how natural aerosols and clouds affect the amount of sunlight absorbed by the Earth and energy radiated back into space.

Studying data from seas around the Peninsula, experts have discovered that most new particles are formed in air masses arriving from the partially ice-covered Weddell Sea -- a significant source of the sulphur gases and alkylamines responsible for 'seeding' the particles.

A new study shows that increased concentrations of sulphuric acid and alkylamines are essential for the formation of new particles around the northern Antarctic Peninsula. High concentrations of other acids and oxygenated organics coincided with high levels of sulphuric acid, but by themselves did not lead to measurable particle formation and growth.

An international team of researchers from the University of Birmingham; Institute of Marine Science, Barcelona, Spain; and King Abdulaziz University, Jeddah, Saudi Arabia studied summertime open ocean and coastal new particle formation in the region, based on data from ship and land stations, and today published its findings in Nature Geoscience.

The researchers revealed that the newly discovered pathway is more efficient than the ion-induced sulphuric acid-ammonia pathway previously observed in Antarctica and can occur rapidly under neutral conditions.

Study co-author Roy Harrison OBE, Professor of Environmental Health at the University of Birmingham, commented: "New particle formation is globally one of the major sources of aerosol particles and cloud condensation nuclei. This previously overlooked pathway to natural aerosol formation could prove a key tool in predicting the future climate of polar regions.

"The key to unlocking Antarctica's climate change lies in examining particles created in the atmosphere by the chemical reaction of gases. These particles start tiny and grow bigger, becoming cloud condensation nuclei leading to more reflective clouds which direct outgoing terrestrial radiation back to earth and warm the lower atmosphere."

New particle formation is globally one of the major sources of aerosol particles and cloud condensation nuclei. Existing research suggests that natural aerosols contribute disproportionately to global warming, whilst sulphuric acid is thought to be responsible for most aerosol seeding observed in the atmosphere.

The research team identified numerous sulphuric acid-amine cluster peaks during new particle formation events -- providing evidence that alkylamines provided the basis for sulphuric acid nucleation.

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Two biodiversity refugia identified in the Eastern Bering Sea

Scientists from Hokkaido University have used species survey and climate data to identify two marine biodiversity refugia in the Eastern Bering Sea -- regions where species richness, community stability and climate stability are high.

Marine biodiversity, the diversity of life in the seas and oceans, supports ecosystem services of immense societal benefits. However, climate change and human activities have been adversely affecting marine biodiversity for many decades, resulting in population decline, community shifts, and species loss and extinction. Developing effective means to mitigate this rapid biodiversity loss is vital.

Scientists from Hokkaido University have identified and characterised regions in the Eastern Bering Sea where biodiversity has been protected from the effects of climate change. Their work was published in the journal Global Change Biology.

Conservation is one of the many approaches by which we have been able to protect biodiversity in various environments from climate change, pollution and human encroachment. Conservation hinges on the identification of areas where the maximum amount of biodiversity is preserved. One such area are refugia, regions that are relatively buffered from the impacts of ongoing climatic changes, which provide favorable habitats for species when the surrounding environment becomes inhospitable.

The scientists tracked the distribution of 159 marine species in the Eastern Bering Sea, off the coast of Alaska, from data collected by the National Oceanic and Atmospheric Administration (NOAA) between 1990 and 2018. Using statistical analysis, they attempted to find regions where there existed persistently high species richness and a stable marine community over a longer period of time. They also, separately, mapped out the changes in climate across the Eastern Bering Sea over the same period.

The scientists identified two distinct refugia in the fishery-rich waters of the Eastern Bering Sea. These regions covered less than 10% of the total study area but harbored 91% of the species analyzed. Most significantly, among the species sheltered in these refugia, commercially important fish and crabs were present in high numbers -- indicating that these refugia conserved high-value resources in addition to supporting high species diversity and community stability. Moreover, these refugia overlapped with regions of high climatic stability over time, where trends in seasonal sea surface temperatures and winter sea ice conditions remained largely unchanged.

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The incredible return of Griffon Vulture to Bulgaria's Eastern Balkan Mountains

Fifty years after presumably becoming extinct as a breeding species in Bulgaria, the Griffon Vulture, one of the largest birds of prey in Europe, is back in the Eastern Balkan Mountains. Since 2009, three local conservation NGOs -- Green Balkans -- Stara Zagora, the Fund for Wild Flora and Fauna and the Birds of Prey Protection Society, have been working on a long-term restoration programme to bring vultures back to their former breeding range in Bulgaria. The programme is supported by the Vulture Conservation Foundation, the Government of Extremadura, Spain, and EuroNatur. Its results have been described in the open-access, peer-reviewed Biodiversity Data Journal.

Two large-scale projects funded by the EU's LIFE tool, one of them ongoing, facilitate the import of captive-bred or recovered vultures from Spain, France and zoos and rehabilitation centres across Europe. Birds are then accommodated in special acclimatization aviaries, individually tagged and released into the wild from five release sites in Bulgaria. Using this method, a total of 153 Griffon Vultures were released between 2009 and 2020 from two adaptation aviaries in the Kotlenska Planina Special Protection Area and the Sinite Kamani Nature Park in the Eastern Balkan Mountains of Bulgaria.

After some 50 years of absence, the very first successful reproduction in the area was reported as early as 2016. Now, as of December 2020, the local population consists of more than 80 permanently present individuals, among them about 25 breeding pairs, and has already produced a total of 31-33 chicks successfully fledged into the wild.

"Why vultures of all creatures? Because they were exterminated, yet provide an amazing service for people and healthy ecosystems," Elena Kmetova-Biro, initial project manager for the Green Balkans NGO explains.

"We have lost about a third of the vultures set free in that site, mostly due to electrocution shortly after release. The birds predominantly forage on feeding sites, where the team provides dead domestic animals collected from local owners and slaughterhouses," the researchers say.

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How plankton hold secrets to preventing pandemics

Whether it's plankton exposed to parasites or people exposed to pathogens, a host's initial immune response plays an integral role in determining whether infection occurs and to what degree it spreads within a population, new University of Colorado Boulder research suggests.

The findings, published May 13 in The American Naturalist, provide valuable insight for understanding and preventing the transmission of disease within and between animal species. From parasitic flatworms transmitted by snails into humans in developing nations, to zoonotic spillover events from mammals and insects to humans -- which have caused global pandemics like COVID-19 and West Nile virus -- an infected creature's immune response is a vital variable to consider in calculating what happens next.

"One of the biggest patterns that we're seeing in disease ecology and epidemiology is the fact that not all hosts are equal," said Tara Stewart Merrill, lead author of the paper and a postdoctoral fellow in ecology. "In infectious disease research, we want to build host immunity into our understanding of how disease spreads."

Invertebrates are common vectors for disease, which means they can transmit infectious pathogens between humans or from animals to humans. Vector-borne diseases, like malaria, account for almost 20% of all infectious diseases worldwide and are responsible for more than 700,000 deaths each year.

Yet epidemiological studies have rarely considered invertebrate immunity and recovery in creatures that are vectors for human disease. They assume that once exposed to a pathogen, the invertebrate host will become infected.

But what if it was possible for invertebrates to fight off these diseases, and break the link in the chain that passes them on to humans?

While observing a tiny species of zooplankton (Daphnia dentifera) throughout its lifecycle and exposure to a fungal parasite (Metschnikowia bicuspidata), the researchers saw this potential in action. Some of the plankton were good at stopping fungal spores from entering their bodies, and others cleared the infection within a limited window of time after ingesting the spores.

"Our results show that there are several defenses that invertebrates can use to reduce the likelihood of infection, and that we really need to understand those immune defenses to understand infection patterns," said Stewart Merrill.

Unexpected recovery

Stewart Merrill started this work in her first year as a doctoral student at the University of Illinois, studying this little plankton and its collection of defenses. It's a gruesome process if the plankton fails to ward off the parasite: Its fungal spores attack the plankton's gut, fill its body and grow until they are released when the host finally dies.

But she noticed something that had not been recorded before: Some of the doomed plankton recovered. Several years later, she has found that when faced with identical levels of exposure, the success or failure of these infections depends on the strength of the host's internal defenses during this early limited window of opportunity.

Based on their observations of these individual outcomes, the researchers developed a simple probabilistic model for measuring host immunity that can be applied across wildlife systems, with important applications for diseases transmitted to humans by invertebrates.

"When immune responses are good, they act as a filter that reduces transmission," said Stewart Merrill. "But any environmental change that degrades immunity can actually amplify transmission, because it will let all of that exposure go through and ultimately become infectious."

It's a model that can also apply to COVID-19, as research from CU Boulder has shown that not all hosts are the same in transmitting the coronavirus, and exposure does not directly determine infection.

COVID-19 is also believed to be the result of a zoonotic spillover, an infection that moved from animals into people, and similar probabilistic models could be advantageous in predicting the occurrence and spread of future spillover events, said Stewart Merrill.

Understanding prevention of infection

Stewart Merrill hopes that a better understanding of infections in a simple animal like plankton can be applied more broadly to invertebrates that matter for human health.

In Africa, Southeast Asia, as well as South and Central America, 200 million people suffer from infections caused by schistosomes -- invertebrates more commonly known as parasitic flatworms. They cause illness and death, and significant economic and public health consequences, so much so that the World Health Organization considers them the second-most socioeconomically devastating parasitic disease after malaria.

They're just one of many neglected tropical diseases transmitted to people by invertebrate hosts such as snails, mosquitoes and biting flies. These diseases infect a large portion of a population but occur in areas with low levels of sanitation that don't have the economic resources to address those diseases, said Stewart Merrill.

Schistosomes live in freshwater environments that people use for their drinking water, laundry and bathing. So even though there are treatments, the next day a person can easily get reinfected just by accessing the water they need. By better understanding how the flatworms themselves succumb to or fight off infection, scientists like Stewart Merrill help us get closer to stopping the chain of transmission into humans.

"We really need to work on understanding prevention of infection, and what that risk is in those aquatic systems, rather than just cures for infection," she said.

The good news is we can learn from the same invertebrates which infect us. In invertebrate hosts that suffer or die from their infections, there is a good incentive to learn how to build an immune response and fight it off. Some snails have even shown the ability to retain an immunological memory: If they get infected once and survive, then they might never get infected again.

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Quantum machine learning hits a limit

A new theorem from the field of quantum machine learning has poked a major hole in the accepted understanding about information scrambling.

"Our theorem implies that we are not going to be able to use quantum machine learning to learn typical random or chaotic processes, such as black holes. In this sense, it places a fundamental limit on the learnability of unknown processes," said Zoe Holmes, a post-doc at Los Alamos National Laboratory and coauthor of the paper describing the work published today in Physical Review Letters.

"Thankfully, because most physically interesting processes are sufficiently simple or structured so that they do not resemble a random process, the results don't condemn quantum machine learning, but rather highlight the importance of understanding its limits," Holmes said.

In the classic Hayden-Preskill thought experiment, a fictitious Alice tosses information such as a book into a black hole that scrambles the text. Her companion, Bob, can still retrieve it using entanglement, a unique feature of quantum physics. However, the new work proves that fundamental constraints on Bob's ability to learn the particulars of a given black hole's physics means that reconstructing the information in the book is going to be very difficult or even impossible.

"Any information run through an information scrambler such as a black hole will reach a point where the machine learning algorithm stalls out on a barren plateau and thus becomes untrainable. That means the algorithm can't learn scrambling processes," said Andrew Sornborger a computer scientist at Los Alamos and coauthor of the paper. Sornborger is Director of Quantum Science Center at Los Alamos and leader of the Center's algorithms and simulation thrust. The Center is a multi-institutional collaboration led by Oak Ridge National Laboratory.

Barren plateaus are regions in the mathematical space of optimization algorithms where the ability to solve the problem becomes exponentially harder as the size of the system being studied increases. This phenomenon, which severely limits the trainability of large scale quantum neural networks, was described in a recent paper by a related Los Alamos team.

"Recent work has identified the potential for quantum machine learning to be a formidable tool in our attempts to understand complex systems," said Andreas Albrecht, a co-author of the research. Albrecht is Director of the Center for Quantum Mathematics and Physics (QMAP) and Distinguished Professor, Department of Physics and Astronomy, at UC Davis. "Our work points out fundamental considerations that limit the capabilities of this tool."

In the Hayden-Preskill thought experiment, Alice attempts to destroy a secret, encoded in a quantum state, by throwing it into nature's fastest scrambler, a black hole. Bob and Alice are the fictitious quantum dynamic duo typically used by physicists to represent agents in a thought experiment.

"You might think that this would make Alice's secret pretty safe," Holmes said, "but Hayden and Preskill argued that if Bob knows the unitary dynamics implemented by the black hole, and share a maximally entangled state with the black hole, it is possible to decode Alice's secret by collecting a few additional photons emitted from the black hole. But this prompts the question, how could Bob learn the dynamics implemented by the black hole? Well, not by using quantum machine learning, according to our findings."

A key piece of the new theorem developed by Holmes and her coauthors assumes no prior knowledge of the quantum scrambler, a situation unlikely to occur in real-world science.

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New study reveals where memories of familiar places are stored in the brain

As we move through the world, what we see is seamlessly integrated with our memory of the broader spatial environment. How does the brain accomplish this feat? A new study from Dartmouth College reveals that three regions of the brain in the posterior cerebral cortex, which the researchers call "place-memory areas," form a link between the brain's perceptual and memory systems. The findings are published in Nature Communications.

"As we navigate our surroundings, information enters the visual cortex and somehow ends up as knowledge of where we are -- the question is where this transformation into spatial knowledge occurs. We think that the place-memory areas might be where this happens," explains lead author Adam Steel, a Neukom Fellow with the department of psychology and brain sciences in the Robertson Lab at Dartmouth. "When you look at the location of the brain areas that process visual scenes and those that process spatial memories, these place-memory areas literally form a bridge between the two systems. Each of the brain areas involved in visual processing are paired with a place-memory counterpart."

For the study, an innovative methodology was employed. Participants were asked to perceive and recall places that they had been to in the real world during functional magnetic resonance imaging (fMRI), which produced high-resolution, subject specific maps of brain activity. Past studies on scene perception and memory have often used stimuli that participants knew of but had never visited, like famous landmarks, and have pooled data across many subjects. By mapping the brain activity of individual participants using real-world places that they had been to, researchers were able to untangle the brain's fine-grained organization.

In one experiment, 14 participants provided a list of people that they knew personally and places that they have visited in real-life (e.g., their father or their childhood home). Then, while in the fMRI scanner, the participants imagined that they were seeing those people or visiting those places. Comparing the brain activity between people and places revealed the place-memory areas. Importantly, when the researchers compared these newly identified regions to the brain areas that process visual scenes, the new regions were overlapping but distinct.

"We were surprised," says Steel, "because the classic understanding is that the brain areas that perceive should be the same areas that are engaged during memory recall."

In another experiment, the team investigated whether the place-memory areas were involved in recognition of familiar places. During fMRI scanning, participants were presented with panning images of familiar and unfamiliar real-world locations downloaded from Google Street View. When the researchers looked at the neural activity, they found that the place-memory areas were more active when images of familiar places were shown. The scene-perception areas did not show the same enhancement when viewing familiar places. This suggests that the place-memory areas play an important role in recognizing familiar locations.

"Our findings help explain how a generic image of a clock tower becomes one that we recognize, such as Baker-Berry Library's tower here on Dartmouth's campus," says Steel.

"It's thrilling to discover a new set of brain areas," says senior author Caroline Robertson, an assistant professor of psychological and brain sciences at Dartmouth. "Learning how the mind is organized is at the heart of the quest of understanding what makes us human."

"The place-memory network provides a new framework for understanding the neural processes that drive memory-guided visual behaviors, including navigation," explains Robertson.

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