Tyler O'Neal, Staff Editor LATEST

Scottish built simulations show new spin on galaxy rotation saves controversial gravity theory

An international group of astronomers, led by a physicist at the University of St Andrews, has revived an alternative gravity theory.

Headed by Dr. Indranil Banik of the School of Physics and Astronomy at St Andrews in Scotland, the study revealed a high predicted rotation speed of gas in a dwarf galaxy consistent with the previously debunked theory known as Milgromian Dynamics (MOND).

An earlier study of the rotation speed of gas in the dwarf galaxy AGC 114905 (Mancera Pina et al, 2022) found that the gas rotated very slowly and claimed the MOND theory was dead.

Such theories are essential in understanding our universe because, according to known physics, galaxies rotate so quickly they should fly apart. MOND, a controversial alternative to General Relativity, the prevailing Einstein-inspired understanding of the phenomenon of gravity that requires dark matter to hold galaxies together; does not require dark matter. As the dark matter has never been detected despite decades of very sensitive searches, various theories have been put forward to explain what holds galaxies together, and debate rages over which is right. The very low rotation speed reported in the Mancera Pina et al study is inconsistent with predictions in a universe governed by General Relativity with large amounts of dark matter.

Dr. Banik’s group argues that the high predicted rotation speed in the MOND gravity theory is consistent with observations if the inclination of the galaxy is overestimated. Gravity 59557

The rotation of stars and gas in distant galaxies cannot be measured directly. Only the component along the line of sight is known from precise spectroscopic measurements. If the galaxy is viewed almost face-on, then it would mostly rotate within the plane of the sky. This could mislead observers into thinking that the galaxy is rotating very slowly, which would require them to overestimate the inclination between disc and sky planes. This inclination was estimated from how elliptical the galaxy appears (see image).

The new study explored this crucial issue using detailed MOND simulations of a disc galaxy similar to AGC 114905 made at the University of Bonn by Srikanth Nagesh and instigated by Pavel Kroupa, Professor at the University of Bonn, and the Charles University in Prague. The simulations show that it can appear somewhat elliptical even when viewed face-on. This is because stars and gas in the galaxy have gravity and can pull themselves into a somewhat non-circular shape. A similar process causes the spiral arms in disc galaxies, features which are so common that these are often called spiral galaxies.

As a result, the galaxy could be a lot closer to face-on than the observers thought. This could mean the galaxy is rotating much faster than reported, removing the tension with MOND.

Dr. Banik, the lead author of the new study, said: “Our simulations show that the inclination of AGC 114905 might be significantly less than reported, which would mean the galaxy is actually rotating much faster than people think, in line with MOND expectations.”

Dr. Hongsheng Zhao, of the School of Physics and Astronomy at the University of St Andrews, said: “The very low reported rotation speed of this galaxy is inconsistent with both MOND and the standard approach with dark matter. But only MOND can get around this apparent contradiction.”

The new study also argues that a similar ‘fake inclination’ effect is unlikely to arise in the standard dark matter approach because the galaxy is dominated by the smooth dark matter halo. The stars and gas contribute little to the gravity, so the disc is not ‘self-gravitating’.

This means it is likely to look very circular if viewed face-on, as confirmed by simulations carried out by another group (Sellwood & Sanders, 2022). As a result, the observed ellipticity must be due to a significant inclination between the disc and sky planes. The rotation velocity would then be very small, implying that the galaxy has very little dark matter. It is not possible in this framework that an isolated dwarf galaxy would have such a small amount of dark matter given how much mass it has in stars and gas.

Pavel Kroupa, Professor at the University of Bonn and Charles University in Prague, said of the broader context of these results: “While MOND works well in the tests conducted so far, the standard approach causes very severe problems on all scales ranging from dwarf galaxies like AGC 114905 all the way up to cosmological scales, as found by many independent teams.”

South Korean prof develops neuromorphic memory device that simulates neurons, synapses​

Tyler O'Neal, Staff Editor LATEST

Simultaneous emulation of neuronal and synaptic properties promotes the development of brain-like artificial intelligence

Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic supercomputing designed to rigorously mimic the human brain with semiconductor devices.

Neuromorphic supercomputing aims to realize artificial intelligence (AI) by mimicking the mechanisms of neurons and synapses that make up the human brain. Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses remains a challenge. To address these issues, a research team led by KAIST located in Daedeok Innopolis, Daejeon, South Korea, Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices. Neuromorphic memory device consisting of bottom volatile and top nonvolatile memory layers emulating neuronal and synaptic properties, respectively

Similar to commercial graphics cards, the artificial synaptic devices previously studied are often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost-efficiency. 

The human brain consists of a complex network of 100 billion neurons and 100 trillion synapses. The functions and structures of neurons and synapses can flexibly change according to the external stimuli, adapting to the surrounding environment. The research team developed a neuromorphic device in which short-term and long-term memories coexist using volatile and non-volatile memory devices that mimic the characteristics of neurons and synapses, respectively. A threshold switch device is used as volatile memory and phase-change memory is used as a non-volatile device. Two thin-film devices are integrated without intermediate electrodes, implementing the functional adaptability of neurons and synapses in the neuromorphic memory.

Professor Keon Jae Lee explained, "Neurons and synapses interact with each other to establish cognitive functions such as memory and learning, so simulating both is an essential element for brain-inspired artificial intelligence. The developed neuromorphic memory device also mimics the retraining effect that allows quick learning of the forgotten information by implementing a positive feedback effect between neurons and synapses.” Retraining operation in the neuromorphic device array. a) Schematic graph showing the retraining effect. b) Scanning electron microscope image of the neuromorphic device array. c) Training pattern “F” for the retraining test. d) Evolution of the memory state of the neuromorphic device array for the naive training and retraining scheme.

Chinese scientists show why meridional heat transport is underestimated

Tyler O'Neal, Staff Editor LATEST

The Atlantic Meridional Overturning Circulation (AMOC) is a phenomenon responsible for transporting ocean heat northward through the Atlantic Ocean. This process significantly influences the Arctic and North Atlantic oceanic climate and the Eurasian continental climate. The corresponding cross-equatorial northward heat transport also determines the location of the Intertropical Convergence Zone (ITCZ), affecting the global energy and rainfall distribution. Changes in ocean net surface heat flux play an important role in modulating the variability of the AMOC and hence the regional and global climate. However, the spread of simulated surface heat fluxes is still large and AMOC underestimation is common, due to poorly represented dynamical processes involving multi-scale interactions within the model simulations. Schematic diagram of the energy flow over the Atlantic. CREDIT Ning Cao, Chunlei Liu

Recently publishing their work in Advances of Atmospheric Sciences, Prof. Chunlei Liu, South China Sea Institute of Marine Meteorology, Guangdong Ocean University located in Zhanjiang, China, and collaborators from the University of Reading, UK and the University of Cambridge, UK have presented new findings on why heat loss over the North Atlantic is underestimated in state-of-the-art atmospheric climate model supercomputer simulations.

In their study, the DEEPC (Diagnosing Earth's Energy Pathways in the Climate system) dataset is used as the “truth” for comparison. DEEPC dataset is constructed using the energy conservation method mainly by Professor Liu and Professor Allan from the University of Reading. This dataset has been widely used by climatologists within the research community as it provides reasonable agreement regarding inferred oceanic heat transport with the in-situ RAPID (Rapid Climate Change-Meridional Overturning Circulation and Heat flux array) observations in both variability and quantity.

“The heat loss from the AMIP6 ensemble mean north of 26°N in the Atlantic is about 10 watts per square meter less than DEEPC, and the inferred meridional heat transport is about 0.3 petawatts (1 petawatt = 1015 watts) lower than the 1.22 petawatts from RAPID and DEEPC.” said co-author Dr. Ning Cao. “These findings can help the research community more accurately interpret the historical simulations and projections produced by contemporary models.”

After further investigation, the team found that low model horizontal resolution produced discrepancies between simulations. They showed that by increasing the resolution, it is possible to improve surface heat flux simulations north of 26°N and the inferred heat transport at 26°N in the Atlantic.

"Although there are problems in simulations, the climate model still plays an important role in climate change research.” said Professor Liu. "Further work is needed to improve model simulations of surface fluxes, and research to reduce observational flux uncertainty is also ongoing through collaboration with the University of Reading and UK Met Office."

Ahn wins $150K from Air Force for semiconductor research

Tyler O'Neal, Staff Editor LATEST

 The Air Force Research Laboratory’s Minority Leaders Research Collaborative Program (ML-RCP) has awarded a two-year, $150,000 award to Ethan Ahn, an assistant professor of the UTSA Electrical and Computer Engineering Department. Ahn, UTSA’s inaugural recipient of the ML-RCP award, will use the money to fund his research to develop a new class of semiconducting materials for high-temperature applications and to develop the next generation of minority researchers. Ethan Ahn, assistant professor of the UTSA Electrical and Computer Engineering Department, was awarded a two-year $150,000 award from the Air Force Research Laboratory's Minority Leaders Research Collaborative Program (ML-RCP).

The Air Force Research Laboratory ML-RCP fosters partnerships with academia while engaging students from diverse backgrounds in research that supports the nation’s air, space, and cyberspace technology needs. The funding will be particularly impactful at UTSA, a Hispanic Serving Institution (HSI) where 57% of the student population identifies as Hispanic.

“I’m very proud to be the first UTSA recipient of this award,” said Ahn, who is based in the Margie and Bill Klesse College of Engineering and Integrated Design. “And I’m proud of UTSA and the opportunities this will create for students.”

Ahn’s project, “Phase change alloys and memory devices for high-temperature applications,” is focused on enhancing the makeup of semiconducting materials to withstand high temperature and speed applications, such as those used in automobiles and other important sectors of the industry, as well as the military. His work also aims to help mitigate the nationwide semiconductor chip shortage. 

But above all else, he aspires to support minority student researchers through his work. Ahn, who notes two mentors along his journey, wants to serve as an inspiration as well to underrepresented UTSA students interested in establishing careers in the field.

He credits Supriyo Datta, his undergraduate research advisor at Purdue University, for leading him toward the study of nanoelectronics. Ahn’s calling to become a professor was inspired by his doctoral thesis advisor at Stanford University, Philip Wong.

Ahn plans to focus on engaging underrepresented undergraduate, master’s degree-seeking, and doctoral students in his work. The ML-RCP award opens the opportunity for future collaborations with UTSA that will advance this goal.

“That’s the whole point,” Ahn said. “This will help generate the next generation of tech force of minority students.”

According to the Air Force Research Laboratory, the ML-RCP is the single largest Department of the Air Force endeavor with Historically Black Colleges and Universities and Minority-Serving Institutions. UTSA’s recent classification as a Tier One research university and its designation as an HSI places it in a unique position to advance diversity in STEM.

Mann builds models of wildfires in an unprecedented time to insight

Tyler O'Neal, Staff Editor LATEST

With wildfires becoming more robust and more frequent, there is a need to predict when and how the next wildfire might occur.

By examining statistical data on California’s wildfires dating back more than 60 years, Michael Mann, an associate professor of geography at George Washington University, has created a model that can forecast the likelihood of wildfires throughout the state from now until the year 2050. Predictions are based on climate variations, indicators of tree and plant growth, population density, and potential ignition sources within each one-kilometer area. Michael Mann

According to Mann, California makes a great test case for the use of this model because the ecosystems that exist within its borders are representative of what is found in the rest of the country. However, Mann says there has been a shift in the modeling in the last five years.

“Basically, none of the models can ‘keep up’ with wildfire risks caused by the megadrought. It’s truly unprecedented in the historical record we use for modeling. There are all kinds of consequences that ripple through everything from insurance to carbon credits and more.”