Amazing Science

After analyzing the achondrite meteorite samples, researchers discovered that water comprised less than two millionths of their mass. For comparison, the wettest meteorites -- a group called carbonaceous chondrites -- contain up to about 20% of water by weight, or 100,000 times more than the meteorite samples studied by Newcombe and her co-authors.

This means that the heating and melting of planetesimals leads to near-total water loss, regardless of where these planetesimals originated in the solar system and how much water they started out with. Newcombe and her co-authors discovered that, contrary to popular belief, not all outer solar system objects are rich in water. This led them to conclude that water was likely delivered to Earth via unmelted, or chondritic, meteorites.

Newcombe said their findings have applications beyond geology. Scientists of many disciplines -- and especially exoplanet researchers -- are interested in the origin of Earth's water because of its deep connections with life.

"Water is considered to be an ingredient for life to be able to flourish, so as we're looking out into the universe and finding all of these exoplanets, we're starting to work out which of those planetary systems could be potential hosts for life," Newcombe said. "In order to be able to understand these other solar systems, we want to understand our own."

Breaking a longstanding impasse in our understanding of olfaction, scientists at UC San Francisco (UCSF) have created the first molecular-level, 3D picture of how an odor molecule activates a human odorant receptor, a crucial step in deciphering the sense of smell.

The findings, appearing online March 15, 2023, in the journal Nature, are poised to reignite interest in the science of smell with implications for fragrances, food science, and beyond. Odorant receptors -- proteins that bind odor molecules on the surface of olfactory cells -- make up half of the largest, most diverse family of receptors in our bodies; A deeper understanding of them paves the way for new insights about a range of biological processes.

"This has been a huge goal in the field for some time," said Aashish Manglik, MD, PhD, an associate professor of pharmaceutical chemistry and a senior author of the study. The dream, he said, is to map the interactions of thousands of scent molecules with hundreds of odorant receptors, so that a chemist could design a molecule and predict what it would smell like.

"But we haven't been able to make this map because, without a picture, we don't know how odor molecules react with their corresponding odor receptors," Manglik said.

In a groundbreaking announcement at the 54th Lunar and Planetary Science Conference held in The Woodlands, Texas, scientists revealed the discovery of a relict glacier near Mars' equator. Located in Eastern Noctis Labyrinthus at coordinates 7° 33' S, 93° 14' W, this finding is significant as it implies the presence of surface water ice on Mars in recent times, even near the equator. This discovery raises the possibility that ice may still exist at shallow depths in the area, which could have significant implications for future human exploration.

Wouldn’t finding life on other worlds be easier if we knew exactly where to look for it? Researchers have limited opportunities to collect samples on Mars or elsewhere or access remote sensing instruments when hunting for life beyond Earth. In a paper published in Nature Astronomy, an interdisciplinary study led by SETI Institute Senior Research Scientist Kim Warren-Rhodes, mapped the sparse life hidden away in salt domes, rocks and crystals at Salar de Pajonales at the boundary of the Chilean Atacama Desert and Altiplano. Warren-Rhodes then worked with co-investigators Michael Phillips (Johns Hopkins Applied Physics Lab) and Freddie Kalaitzis (University of Oxford) to train a machine learning model to recognize the patterns and rules associated with their distributions so it could learn to predict and find those same distributions in data on which it was not trained. In this case, by combining statistical ecology with AI/ML, the scientists could locate and detect biosignatures up to 87.5% of the time (versus ≤10% by random search) and decrease the area needed for search by up to 97%.

“Our framework allows us to combine the power of statistical ecology with machine learning to discover and predict the patterns and rules by which nature survives and distributes itself in the harshest landscapes on Earth.,” said Rhodes. “We hope other astrobiology teams adapt our approach to mapping other habitable environments and biosignatures. With these models, we can design tailor-made roadmaps and algorithms to guide rovers to places with the highest probability of harboring past or present life—no matter how hidden or rare.”

A video clip showing the major concepts of integrating datasets from orbit to the ground is presented. The first frames zoom in from a global view to an orbital image of Salar de Pajonales. The salar is then overlain with an interpretation of its compositional variability derived from ASTER multispectral data. The next sequence of frames transitions to drone-derived images of the field site within Salar de Pajonales. Note features of interest that become identifiable in the scene, starting with polygonal networks of ridges, then individual gypsum domes and polygonal patterned ground, and ending with individual blades of selenite. The video ends with a first-person view of a set of gypsum domes studied in the article using machine learning techniques. Video credit: M. Phillips

Ultimately, similar algorithms and machine learning models for many different types of habitable environments and biosignatures could be automated onboard planetary robots to efficiently guide mission planners to areas at any scale with the highest probability of containing life. Rhodes and the SETI Institute NASA Astrobiology Institute (NAI) team used the Salar de Pajonales, as a Mars analog. Pajonales is a high altitude (3,541 m), high U/V, hyperarid, dry salt lakebed, considered inhospitable to many life forms but still habitable.

During the NAI project’s field campaigns, the team collected over 7,765 images and 1,154 samples and tested instruments to detect photosynthetic microbes living within the salt domes, rocks and alabaster crystals. These microbes exude pigments that represent one possible biosignature on NASA’s Ladder of Life Detection.

At Pajonales, drone flight imagery connected simulated orbital (HiRISE) data to ground sampling and 3D topographical mapping to extract spatial patterns. The study’s findings confirm (statistically) that microbial life at the Pajonales terrestrial analog site is not distributed randomly but concentrated in patchy biological hotspots strongly linked to water availability at km to cm scales.

Next, the team trained convolutional neural networks (CNNs) to recognize and predict macro-scale geologic features at Pajonales—some of which, like patterned ground or polygonal networks, are also found on Mars—and micro-scale substrates (or ‘micro-habitats’) most likely to contain biosignatures.

Like the Perseverance team on Mars, the researchers tested how to effectively integrate a UAV/drone with ground-based rovers, drills and instruments (e.g., VISIR on ‘MastCam-Z’ and Raman on ‘SuperCam’ on the Mars 2020 Perseverance rover).

Astronomers using the SMARTS 1.5-meter Telescope at Cerro Tololo Inter-American Observatory in Chile, a Program of NSF's NOIRLab, have uncovered the first example of a phenomenally rare type of binary star system, one that has all the right conditions to eventually trigger a kilonova -- the ultra-powerful, gold-producing explosion created by colliding neutron stars. Such an arrangement is so vanishingly rare that only about 10 such systems are thought to exist in the entire Milky Way Galaxy. The findings are published today in the journal Nature.

This unusual system, known as CPD-29 2176, is located about 11,400 light-years from Earth. It was first identified by NASA's Neil Gehrels Swift Observatory. Later observations with the SMARTS 1.5-meter Telescope allowed astronomers to deduce the orbital characteristics and types of stars that make up this system -- a neutron star created by an ultra-stripped supernova and a closely orbiting massive star that is in the process of becoming an ultra-stripped supernova itself.

An ultra-stripped supernova is the end-of-life explosion of a massive star that has had much of its outer atmosphere stripped away by a companion star. This class of supernova lacks the explosive force of a traditional supernova, which would otherwise "kick" a nearby companion star out of the system. "The current neutron star would have to form without ejecting its companion from the system. An ultra-stripped supernova is the best explanation for why these companion stars are in such a tight orbit," said Noel D. Richardson at Embry-Riddle Aeronautical University and lead author of the paper. "To one day create a kilonova, the other star would also need to explode as an ultra-stripped supernova so the two neutron stars could eventually collide and merge." As well as representing the discovery of an incredibly rare cosmic oddity, finding and studying kilonova progenitor systems such as this can help astronomers unravel the mystery of how kilonovae form, shedding light on the origin of the heaviest elements in the Universe.

"For quite some time, astronomers speculated about the exact conditions that could eventually lead to a kilonova," said NOIRLab astronomer and co-author André-Nicolas Chené. "These new results demonstrate that, in at least some cases, two sibling neutron stars can merge when one of them was created without a classical supernova explosion."

Producing such an unusual system, however, is a long and unlikely process. "We know that the Milky Way contains at least 100 billion stars and likely hundreds of billions more. This remarkable binary system is essentially a one-in-ten-billion system," said Chené. "Prior to our study, the estimate was that only one or two such systems should exist in a spiral galaxy like the Milky Way."

The synthetic galaxy catalog will help test Roman's capabilities and foster collaboration with the Rubin project. 

We’re seeing a new wave of generative AI applications that are transforming the way people interact with technology – from games and dialog agents to creative brainstorming and coding tools. Google wants to continue making AI accessible by empowering all developers to start building the next generation of applications with generative AI by providing easy-to-use APIs and tools.

Just recently, Google announced the PaLM API, a new developer offering that makes it easy and safe to experiment with Google’s large language models (LLMs). Alongside the API, Google is now releasing MakerSuite, a tool that lets developers start prototyping quickly and easily. Currently, they are making these tools available to only a select group of developers through a Private Preview, and a waitlist for others will follow soon.

According to Andreas Braun, the CTO of Microsoft Germany, Microsoft will release GPT-4 next week with AI powered video generation capabilities.

This announcement was made by Andreas Braun, the CTO of Microsoft Germany and Lead Data & AI STU, during the AI in Focus Digital Kickoff.

Bing, which currently runs on the power of ChatGPT and GPT 3.5, has faced criticism for its sluggishness in generating and presenting search results.

The forthcoming release of GPT-4 is anticipated to enhance Bing's capabilities and provide users with fresh opportunities. Through the use of multimodal models, users will be able to engage via various channels, such as text, images, and sounds. A major highlight of the latest version is its capability to generate videos.

OpenAI recently made an announcement about the development of a mobile app for ChatGPT, featuring the latest GPT-4 AI technology. The app will allow users to create videos with AI assistance, showcasing the potential of GPT-4.

Along with this, GPT-4 will offer faster answer generation compared to the current GPT 3.5 version. Furthermore, GPT-4's answers will be more akin to human responses, enhancing its human-like capabilities. These advancements will also be incorporated into Bing Chat in the near future.

Having invested billions of dollars in OpenAI, Microsoft is poised to quickly integrate GPT-4 into Bing search. Although, Andreas Braun did not mention a specific timeline for when Bing Chat will receive the benefits of GPT-4.

This updated version, with its capabilities of generating videos and producing more lifelike answers, has the potential to revolutionize our experience with AI technology.

What lies at the bottom of Hyperion's strange craters?

To help find out, the robot Cassini spacecraft that once orbited Saturn swooped past the sponge-textured moon and took images of unprecedented detail. A six-image mosaic from the 2005 pass, featured here in scientifically assigned colors, shows a remarkable world strewn with strange craters and an odd, sponge-like surface. At the bottom of most craters lies some type of unknown dark reddish material. This material appears similar to that covering part of another of Saturn's moons, Iapetus, and might sink into the ice moon as it better absorbs warming sunlight. Hyperion is about 250 kilometers across, rotates chaotically, and has a density so low that it likely houses a vast system of caverns inside.

You can even see the difference between protons and neutrons!

The Relativistic Heavy Ion Accelerator (RHIC), from the Brookhaven Laboratory in the United States, is a sophisticated device capable of accelerating gold ions to a speed of up to 99.995% that of light. Thanks to him, it has recently been possible to verify, for example, Einstein's famous equation E=mc2.

Now, researchers in this laboratory have shown how it is possible to obtain precise details about the arrangement of protons and neutrons in gold using a type of quantum interference never seen before in an experiment . The technique is reminiscent of the positron emission tomography (PET) scan that doctors use to peer into the brain and other anatomical parts.

No microscopic probe or X-ray machine is capable of peering into the innards of the atom, so physicists can only theorize what happens there based on the remains of high-speed collisions that take place in particle colliders , such as CERN 's LHC .

However, this new tool opens the possibility of making more precise inferences of protons and neutrons (which make up atomic nuclei) thanks to the quantum entanglement of particles produced when gold atoms rub against each other at high speed.

The researchers have shown how it is possible to obtain precise details about the arrangement of protons and neutrons in gold using a type of quantum interference never seen before in an experiment. 

At this scale, nothing can be observed directly because the very light used to carry out the observation interferes with the same observation. However, given enough energy, light waves can actually stir up pairs of particles that make up protons and neutrons, such as quarks and antiquarks . 

When two nuclei intersect within a few nuclear radii, a photon from one nucleus can interact through a virtual quark-antiquark pair with gluons from the other nucleus (gluons are mediators of the strong interaction, the force that binds nuclei). quarks inside protons and neutrons).

This allows for the equivalent of the first experimental observation of entanglement involving different particles, allowing images so precise that the difference between the place of neutrons and protons within the atomic nucleus can even begin to be appreciated.

Aber-clam Lincoln, a quahog clam believed to be 214 years old found at Alligator Point, was released into the Gulf of Mexico Friday by his caretakers at the Gulf Specimen Marine Lab in Panacea.  Americorps member Blaine Parker dug up the two-century old mollusk while collecting shellfish to make chowder.  Parker said it is hefty enough to make two servings and has shells large enough to use as bowls to serve it in.  “We were just going to eat it, but we thought about it a while and figured it was probably pretty special. So, we didn’t want to kill it,” said Parker. 

Instead, he took it to the aquarium at the Gulf Specimen Marine Lab where he works as a specimen collector.  While most Ocean quahogs are within 2.8 to 4.3 inches in length and weigh up to a half pound, Lincoln checks in at 6 inches and weighs 2.6 pounds.  The clam has been drawing up to 100 visitors a day. 

Parker is a recent Eckerd College graduate with a degree in environmental studies and marine science. He said, a clam, like a tree, lays down annual growth bands, alternating bands of light on its shell, that scientists used to estimate its age.   There are 214 layers on the shell of the clam he found, which would mean it was likely born in 1809, the same year as Abraham Lincoln. It was also discovered on Presidents Day weekend. So, Parker named his find Aber-clam Lincoln. 

Quahogs occur in the Atlantic from Greenland south to North Carolina. They move about by being tossed in the surf, and crawl along the sand by expanding and contracting their muscle. 

With Lincoln being so old it is possible, like many Floridians, circumstances moved him south for him to become one of the oldest known Florida transplants. 

Quahogs are known to live 200 or more years. A 507-year-old clam, found in the Icelandic seabed and named Ming, broke the Guinness World Record for oldest animal when it was discovered in 2007. Scientists think an incredible low metabolic rates of Lincoln and other quahogs is responsible for their long life.

A University of Kansas study of the energy needs of 299 species of extinct and living bivalves found those with minimal energy requirements escaped extinction. 

Northwestern University and the University of California San Diego (UC San Diego) astrophysicists have discovered the tightest ultracool dwarf binary system ever observed. The two stars are so close that it takes them less than one Earth day to revolve around each other. In other words, each star's "year" lasts just 17 hours.

The newly discovered system, named LP 413-53AB, is composed of a pair of ultracool dwarfs, a class of very low-mass stars that are so cool that they emit their light primarily in the infrared, making them completely invisible to the human eye. They are nonetheless one of the most common types of stars in the universe.

Previously, astronomers had only detected three short-period ultracool dwarf binary systems, all of which are relatively young -- up to 40 million years old. LP 413-53AB is estimated to be billions of years old -- similar age to our sun -- but has an orbital period that is at least three times shorter than the all ultracool dwarf binaries discovered so far.

The research was published on March 1 in the Astrophysical Journal Letters. "It's exciting to discover such an extreme system," said Chih-Chun "Dino" Hsu, a Northwestern astrophysicist who led the study. "In principle, we knew these systems should exist, but no such systems had been identified yet."

Hsu is a postdoctoral researcher in Northwestern's Center for Interdisciplinary Exploration and Research in Astrophysics(CIERA). He began this study while a Ph.D. student at UC San Diego, where he was advised by Professor Adam Burgasser.

For the first time, scientists now have a continuous model of the the Earth's past 100 million years. This will provide a new tool to understand ocean chemistry and how geomorphology affects biological evolution.

Climate, tectonics and time combine to create powerful forces that craft the face of our planet. Add the gradual sculpting of the Earth's surface by rivers and what to us seems solid as rock is constantly changing. However, our understanding of this dynamic process has at best been patchy. Scientists have now published new research revealing a detailed and dynamic model of the Earth's surface over the past 100 million years. Working with scientists in France, University of Sydney geoscientists have published this new model in the journal Science.

For the first time, it provides a high-resolution understanding of how today's geophysical landscapes were created and how millions of tonnes of sediment have flowed to the oceans.

Bumblebees are clumsy fliers. It is estimated that a foraging bee bumps into a flower about once per second, which damages its wings over time. Yet despite having many tiny rips or holes in their wings, bumblebees can still fly.

Aerial robots, on the other hand, are not so resilient. Poke holes in the robot’s wing motors or chop off part of its propellor, and odds are pretty good it will be grounded.

Inspired by the hardiness of bumblebees, MIT researchers have developed repair techniques that enable a bug-sized aerial robot to sustain severe damage to the actuators, or artificial muscles, that power its wings — but to still fly effectively.

They optimized these artificial muscles so the robot can better isolate defects and overcome minor damage, like tiny holes in the actuator. In addition, they demonstrated a novel laser repair method that can help the robot recover from severe damage, such as a fire that scorches the device.

Using their techniques, a damaged robot could maintain flight-level performance after one of its artificial muscles was jabbed by 10 needles, and the actuator was still able to operate after a large hole was burnt into it. Their repair methods enabled a robot to keep flying even after the researchers cut off 20 percent of its wing tip.

This could make swarms of tiny robots better able to perform tasks in tough environments, like conducting a search mission through a collapsing building or dense forest.

“We spent a lot of time understanding the dynamics of soft, artificial muscles and, through both a new fabrication method and a new understanding, we can show a level of resilience to damage that is comparable to insects,” says Kevin Chen, the D. Reid Weedon, Jr. Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS), the head of the Soft and Micro Robotics Laboratory in the Research Laboratory of Electronics (RLE), and the senior author of the paper on these latest advances. “We’re very excited about this. But the insects are still superior to us, in the sense that they can lose up to 40 percent of their wing and still fly. We still have some catch-up work to do.”

Venus appears to have volcanic activity, according to a new research paper that offers strong evidence to answer the lingering question about whether Earth's sister planet currently has eruptions and lava flows.

In a new study, University of California, Irvine astronomers describe how extraterrestrial life has the potential to exist on distant exoplanets inside a special area called the "terminator zone," which is a ring on planets that have one side that always faces its star and one side that is always dark.

"These planets have a permanent day side and a permanent night side," said Ana Lobo, a postdoctoral researcher in the UCI Department of Physics & Astronomy who led the new work, which just published in The Astrophysical Journal. Lobo added that such planets are particularly common because they exist around stars that make up about 70 percent of the stars seen in the night sky -- so-called M-dwarf stars, which are relatively dimmer than our sun.

Cambridge scientists have successfully trialed an artificial pancreas for use by patients living with type 2 diabetes. The device – powered by an algorithm developed at the University of Cambridge -- doubled the amount of time patients were in the target range for glucose compared to standard treatment and halved the time spent experiencing high glucose levels.

Physicists at the University of Cincinnati are learning more about the bizarre behavior of “strange metals,” which operate outside the normal rules of electricity.

Physicists are learning more about the bizarre behavior of "strange metals," which operate outside the normal rules of electricity. Theoretical physicist Yashar Komijani, an assistant professor at the University of Cincinnati, contributed to an international experiment using a strange metal made from an alloy of ytterbium, a rare earth metal. Physicists in a lab in Hyogo, Japan, fired radioactive gamma rays at the strange metal to observe its unusual electrical behavior.

Led by Hisao Kobayashi with the University of Hyogo and RIKEN, the study was published in the journal Science. The experiment revealed unusual fluctuations in the strange metal's electrical charge. "The idea is that in a metal, you have a sea of electrons moving in the background on a lattice of ions," Komijani said. "But a marvelous thing happens with quantum mechanics. You can forget about the complications of the lattice of ions. Instead, they behave as if they are in a vacuum."

Komijani for years has been exploring the mysteries of strange metals in relation to quantum mechanics. "You can put something in a black box and I can tell you a lot about what's inside it without even looking at it just by measuring things like resistivity, heat capacity and conductivity," he said.

Atmospheric muons and neutrinos are the most abundant signals detected in IceCube. They are produced in cosmic-ray-induced air showers in the Earth’s atmosphere. Cosmic rays are high-energy protons and heavier nuclei traveling through space. When these cosmic rays reach Earth and collide with atoms in the atmosphere, they create an avalanche-like cascade of secondary particles called an air shower. The production of atmospheric neutrinos and muons in  high-energy particle interactions depends on the properties of the Earth’s atmosphere and, thus, its seasonal change in temperature. Although seasonal variations for atmospheric muons have been previously measured, this had not yet been achieved for atmospheric neutrinos.

In a paper submitted to The European Physical Journal C, the IceCube Collaboration investigated the temperature dependence of the atmospheric muon neutrino flux.  The collaborators report a significant observation of a correlation between the rate of neutrinos spanning gigaelectronvolt to petaelectronvolt energies detected by the IceCube Neutrino Observatory—a gigaton-scale neutrino detector operating at the South Pole—and atmospheric temperatures of the stratosphere. While at first glance these measurements establish IceCube as a gigantic atmospheric thermometer, they scientifically open a new view on the physics of high-energy particle interactions in air showers.

When a neutrino interacts with a molecule of ice in the detector, it creates a secondary charged particle that produces Cherenkov light, which is then picked up by the optical sensors. Scientists are then able to reconstruct each detected neutrino and determine its direction. To look at the temperature dependence of atmospheric neutrinos, the collaborators determined the atmospheric conditions for the respective time and direction of each neutrino event from a sample of 260,000 neutrinos detected by IceCube over a 6-year period. They also used a temperature dataset provided by the Atmospheric Infrared Sounder (AIRS) on NASA’s Aqua satellite, which provides daily coverage of the global distribution of atmospheric temperatures. The atmospheric neutrino rate measured by IceCube was then correlated with an average of the atmospheric temperature called effective temperature.

“We observed a highly significant correlation between the temperature and the neutrino rate, but at the same time there is a slight tension between these results and the results we expect from current air shower models,” says Jakob Böttcher, a physics PhD student at RWTH Aachen University and study lead. “We measured a 3.5% change in the atmospheric muon neutrino flux for the observed 10% seasonal change of the effective atmospheric temperature.” 

MIT's Kulik Lab has designed better ways of discovering and designing novel, environmentally benign, and energy-efficient materials for energy applications in a vast chemical space where molecular combinations that offer remarkable optical, conductive, magnetic, and heat transfer properties await discovery.

Swift and significant gains against climate change require the creation of novel, environmentally benign, and energy-efficient materials. One of the richest veins researchers hope to tap in creating such useful compounds is a vast chemical space where molecular combinations that offer remarkable optical, conductive, magnetic, and heat transfer properties await discovery. But finding these new materials has been slow going.

“While computational modeling has enabled us to discover and predict properties of new materials much faster than experimentation, these models aren’t always trustworthy,” says Heather J. Kulik  PhD ’09, associate professor in the departments of Chemical Engineering and Chemistry. “In order to accelerate computational discovery of materials, we need better methods for removing uncertainty and making our predictions more accurate.”

A team from Kulik’s lab set out to address these challenges with a team including Chenru Duan PhD ’22.

A tool for building trust

Kulik and her group focus on transition metal complexes, molecules comprised of metals found in the middle of the periodic table that are surrounded by organic ligands. These complexes can be extremely reactive, which gives them a central role in catalyzing natural and industrial processes. By altering the organic and metal components in these molecules, scientists can generate materials with properties that can improve such applications as artificial photosynthesis, solar energy absorption and storage, higher efficiency OLEDS (organic light emitting diodes), and device miniaturization.

“Characterizing these complexes and discovering new materials currently happens slowly, often driven by a researcher’s intuition,” says Kulik. “And the process involves trade-offs: You might find a material that has good light-emitting properties, but the metal at the center may be something like iridium, which is exceedingly rare and toxic.”

Researchers attempting to identify nontoxic, earth-abundant transition metal complexes with useful properties tend to pursue a limited set of features, with only modest assurance that they are on the right track. “People continue to iterate on a particular ligand, and get stuck in local areas of opportunity, rather than conduct large-scale discovery,” says Kulik.

Dr. Alan D. Thompson is a world expert in artificial intelligence (AI), specializing in the augmentation of human intelligence, and advancing the evolution of ‘integrated AI’. 

Alan’s applied AI research and visualizations are featured worldwide, with citations in the University of Oxford’s debate on AI Ethics in December 2021, and in the US Government’s economic research report in February 2023. His 2021-2022 experiments with Leta AI and Aurora AI have been viewed over 2.5 million times.

Prior to his work in AI, Alan was a major contributor to human intelligence research and practice. As chairman for Mensa International’s gifted families committee, Alan served two consecutive terms sharing best practice among 54 countries, and his work on gifted education was referenced in the Department of Education’s High Potential policy.

Alan’s best-selling book, Bright, was made available to families at Elon Musk’s gifted school. A copy of the book will be sent to the moon aboard the Peregrine lunar lander in 2023. Alan continues to advise enterprise, government, and international media in the fields of artificial intelligence and human intelligence, consulting to the award-winning series Decoding Genius for GE, Making Child Prodigies for ABC (with the Australian Prime Minister), 60 Minutes for Network Ten/CBS, and Child Genius for Warner Bros.

Alan completed his Bachelor of Science (Computer Science, AI, and Psychology) at Edith Cowan University, 2004; studied Gifted Education at Flinders University, 2017; became a Fellow of the Institute of Coaching affiliated with Harvard Medical School, 2017; and received his doctorate from Emerson, 2021. Alan’s dissertation was adapted into a book featuring Dr Rupert Sheldrake, Connected: Intuition and Resonance in Smart People.

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Researchers have developed a cheaper and more energy-efficient way to make hydrogen directly from seawater.

The new method from RMIT University researchers splits the seawater directly into hydrogen and oxygen – skipping the need for desalination and its associated cost, energy consumption and carbon emissions.

Hydrogen has long been touted as a clean future fuel and a potential solution to critical energy challenges, especially for industries that are harder to decarbonise like manufacturing, aviation and shipping.

Almost all the world’s hydrogen currently comes from fossil fuels and its production is responsible for around 830 million tonnes of carbon dioxide a year*, equivalent to the annual emissions of the United Kingdom and Indonesia combined.  But emissions-free ‘green’ hydrogen, made by splitting water, is so expensive that it is largely commercially unviable and accounts for just 1% of total hydrogen production globally.

Lead researcher Dr Nasir Mahmood, a Vice-Chancellor’s Senior Research Fellow at RMIT, said green hydrogen production processes were both costly and relied on fresh or desalinated water. “We know hydrogen has immense potential as a clean energy source, particularly for the many industries that can’t easily switch over to be powered by renewables,” Mahmood said. “But to be truly sustainable, the hydrogen we use must be 100% carbon-free across the entire production life cycle and must not cut into the world’s precious freshwater reserves. Our method to produce hydrogen straight from seawater is simple, scaleable and far more cost-effective than any green hydrogen approach currently in the market. With further development, we hope this could advance the establishment of a thriving green hydrogen industry in Australia.”   

A provisional patent application has been filed for the new method, detailed in a lab-scale study published in Wiley journal, Small.

A new technique greatly reduces the error in an optical neural network, which uses light to process data instead of electrical signals. With their technique, the larger an optical neural network becomes, the lower the error in its computations. This could enable them to scale these devices up so they would be large enough for commercial uses.

As machine-learning models become larger and more complex, they require faster and more energy-efficient hardware to perform computations. Conventional digital computers are struggling to keep up.

An analog optical neural network could perform the same tasks as a digital one, such as image classification or speech recognition, but because computations are performed using light instead of electrical signals, optical neural networks can run many times faster while consuming less energy.

However, these analog devices are prone to hardware errors that can make computations less precise. Microscopic imperfections in hardware components are one cause of these errors. In an optical neural network that has many connected components, errors can quickly accumulate.

Even with error-correction techniques, due to fundamental properties of the devices that make up an optical neural network, some amount of error is unavoidable. A network that is large enough to be implemented in the real world would be far too imprecise to be effective.

MIT researchers have overcome this hurdle and found a way to effectively scale an optical neural network. By adding a tiny hardware component to the optical switches that form the network’s architecture, they can reduce even the uncorrectable errors that would otherwise accumulate in the device.

Their work could enable a super-fast, energy-efficient, analog neural network that can function with the same accuracy as a digital one. With this technique, as an optical circuit becomes larger, the amount of error in its computations actually decreases.  

“This is remarkable, as it runs counter to the intuition of analog systems, where larger circuits are supposed to have higher errors, so that errors set a limit on scalability. This present paper allows us to address the scalability question of these systems with an unambiguous ‘yes,’” says lead author Ryan Hamerly, a visiting scientist in the MIT Research Laboratory for Electronics (RLE) and Quantum Photonics Laboratory and senior scientist at NTT Research.

Hamerly’s co-authors are graduate student Saumil Bandyopadhyay and senior author Dirk Englund, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), leader of the Quantum Photonics Laboratory, and member of the RLE. The research is published today in Nature Communications.

This observation from the NASA/ESA/CSA James Webb Space Telescope contains three different images of the same supernova-hosting galaxy, all of which were created by a colossal gravitational lens. Gravitational lensing occurs when a massive celestial body causes a sufficient curvature of spacetime to bend the path of light traveling past or through it, almost like a vast lens. In this case, the lens is the galaxy cluster RX J2129, located around 3.2 billion light-years from Earth in the constellation Aquarius. This annotated image of the cluster highlights the three images of the lensed galaxy, including the one where the supernova was detected.

Astronomers discovered the supernova in the triply-lensed background galaxy using observations from the NASA/ESA Hubble Space Telescope, and they suspected that they had found a very distant Type Ia supernova. These supernovae always produce a fairly consistent luminosity — at the same distance, one looks as bright as any other — which makes them particularly helpful to astronomers. As their distance from Earth is proportional to how dim they appear in the night sky, objects with known brightness can be used as 'standard candles' to measure astronomical distances. 

The gravitational lens has created three lensed images of the background galaxy, which are not uniform in size, position or age. Because mass in the galaxy cluster is distributed unevenly, rays of light emitted by the supernova are bent by the lens in different amounts, and so they take longer or shorter paths to the viewer — resulting in separate images. The light that took the longest path gives us the oldest image of the galaxy, in which the supernova is still visible. The next image is of the galaxy as it appears roughly 320 days later than the first one, and the last image roughly 1000 days after the first. At both later points in time, the supernova has already faded from view. The name for the transient is AT 2022riv.

This observation was captured by Webb's Near-InfraRed Camera to measure the brightness of the lensed supernova. As part of the same programme, NIRSpec spectroscopy of the supernova was also obtained, which will allow comparison of this distant supernova to Type Ia supernovae in the nearby Universe. This is an important way to verify that one of astronomers’ tried-and-tested methods of measuring vast distances works as expected.

[Image description: The main image shows a large elliptical galaxy, surrounded by many small similar galaxies in a cluster, and background stars and galaxies. Three smaller pull-outs show three lensed images of a background galaxy, close up.]

Galaxies come in many different shapes and sizes, but the basic ingredients seem fairly consistent. There's usually a big black hole at the center, a bunch of stars and gas, and a generous serving of dark matter that helps glue the whole thing together.

While dark matter is, well, dark, the stars, gas, and swirling core of heated material stand out with the radiant beauty of a city in the night.

However, one newly discovered dwarf galaxy located a mere 94 million light-years away is defying expectations. It's named FAST J0139+4328, and it's not emitting any optical light. In fact, it's barely emitting any light at all.

FAST J0139+4328 appears to be what is known as a dark galaxy. Aside from a small smattering of stars, the galaxy seems to be made up almost entirely of dark matter.

A paper describing the discovery has been accepted for publication in The Astrophysical Journal Letters, and is available on the preprint server arXiv.

"This is the first time that an isolated dark galaxy has been detected in the nearby Universe" write a team of astronomers led by Jin-Long Xu of the Chinese Academy of Sciences in Beijing.

Dark matter is currently the leading explanation for a weird discrepancy between the amount of normal, or baryonic, matter observed in corners of the Universe and the strength of the gravity required to hold it together. Put simply, there's just not enough baryonic matter to account for all the gravity. Galaxies are spinning so fast that they should fly apart without something else binding it all together.

Whatever is responsible for this extra gravity remains elusive. It doesn't seem to interact with normal matter in any way other than through gravity; nor does it emit any form of radiation we can currently detect. We simply can't see the source of this extra mass. Still, reserving a space for some kind of unknown material goes a long way towards resolving the problems we observe.

However, dark matter theory isn't perfect either. One problems is a discrepancy between simulations of the dark matter distribution in the Universe and the number of dwarf galaxies we see out there orbiting larger galaxies. There are way fewer dwarf galaxies than the simulations suggest there ought to be. This is known as the dwarf galaxy problem.

It is possible we're simply unable to detect some kinds of dwarf galaxy, such as those with very few stars, consisting primarily of gas and dark matter. Finding enough of them would help resolve the whole shortfall in dwarf galaxies.