Elon Musk predicts that trillions of dollars will be spent in attempts to make antimatter propulsion a reality in the future, NASA chief agrees.
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Autism study reveals shared brain cell changes during early development
Hundreds of genes have been linked to autism, yet the precise molecular and cellular mechanisms behind it remain largely unclear. A new study published in Nature, led by Gaia Novarino at the Institute of Science and Technology Austria (ISTA), aims to uncover these mechanisms-and in doing so, might lay the groundwork for developing medical therapies.
Autism spectrum conditions, often abbreviated as ASD in scientific and medical literature, are, for example, neurodevelopmental disorders such as epilepsy or intellectual disability. The underlying changes begin during early brain development, while the first signs often become apparent in early childhood and can persist throughout life.
ALMA spots a nine-member stellar family in the act of formation
Massive stars much bigger than our sun always come in pairs or groups, not alone. But astronomers don’t fully understand how these groupings form. In a new study, astronomers using ALMA have serendipitously discovered a young system containing nine baby stars forming together, and they have detailed a rare glimpse of the formation of such a stellar family in its earliest assembly stage in a paper submitted to the arXiv preprint server on June 2.
There are a few competing theories of how groups of stars form: disk, core and filament fragmentation. That is, a spinning disk of gas around a young star breaks apart into multiple pieces, or a big core of gas fragments into multiple star-forming clumps before the stars even form, or a long filamentary cloud of gas breaks into clumps along its length, each clump forming a star.
Massive stars, growing together as a group, are hard to study because they are far away, buried in thick dust and grow up fast while still in dense clouds. So astronomers have not caught many of them “in the act” of forming.
Horizon edge states gain finite description in string theory calculation
Modern physics theories highlight the key role of horizons—boundaries beyond which information cannot reach an observer—in a variety of cosmological and gravitational phenomena. Two renowned examples of these boundaries are event horizons in black holes and the cosmological horizon of the de Sitter spacetime, a model of an expanding universe with a positive vacuum energy.
Many quantum theories predict the existence of quantum states or excitations in the proximity of horizons, which are known as edge modes. Edge modes are additional degrees of freedom that can emerge when space is divided into two distinct regions. Rather than being distributed throughout space, they are typically localized near or on the boundary that divides the two regions.
Researchers at the Abdus Salam International Center for Theoretical Physics and the University of Amsterdam recently set out to calculate the contribution of edge modes to the Euclidean partition function, a quantity that encodes information about all possible quantum states of a system and their statistical properties.
Brain-inspired AI architecture could compute faster while using far less power
Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with each other. While biological neurons exchange information in the form of electrical impulses, SNNs rely on brief signals known as spikes.
SNNs have proved promising for reducing power consumption, as developers can ensure they do not process information continuously, but rather only when meaningful changes occur. This could be highly advantageous, as current AI systems are known to consume large amounts of energy.
While some SNNs introduced in the past achieved encouraging results, they typically struggle to retain useful information (i.e., context) for long periods. This was found to be particularly challenging when the models have only a limited amount of data storage available or are operating under energy constraints.
Anatomically accurate digital twin of 2-year-old’s brain uncovers neural signatures linked to autism
For decades, researchers have been trying to understand the biological roots of autism spectrum disorder (ASD), a common neurodevelopmental condition that shapes how people communicate, learn and interact with the world. One of the major hurdles is that the brain’s neural networks are extraordinarily complex. Existing models still lack the detail needed to capture both the brain’s structure and its dynamic activity in a unified manner.
In a recent study published in PLOS Digital Health, researchers created a new system called FEDE (high FidElity Digital brain modEl) that builds a digital twin, a detailed computer replica or virtual copy of a real-world object. In this study, it was a virtual copy of the brain of a 2-year-old child with ASD.
To build FEDE, researchers combined maps of the child’s brain structure obtained using MRI with mathematical modeling to create a digital brain that can simulate both how the brain is built and how it functions.
Chinese supercomputer displaces US machines as world’s fastest for first time since 2017
A supercomputer in China now outranks its U.S. counterparts as the world’s most powerful, marking the first time since 2017 that a Chinese computer has topped a list sometimes viewed as a measure of a nation’s technological prowess.
The LineShine computer in Shenzhen, China, displaced top-ranked U.S. computer El Capitan in the latest version of the TOP500 ranking announced Tuesday. It was the Chinese computer’s debut on the list.
Scientists behind the TOP500 project said the LineShine computer at China’s National Supercomputing Center achieved 2.198 exaflops, meaning it can perform more than 2 quintillion calculations per second.
Graphene plasmon cavities enable advanced and scalable terahertz photodetectors
How could we noninvasively distinguish between healthy and cancerous tissue? And how could we increase the speed of wireless communications? These two seemingly unrelated questions may share the same answer: terahertz (THz) light. Spanning frequencies between 0.3 and 20 THz, THz light interacts with matter without causing damage and allows for faster data transfer than radio waves. It is thus ideal for advancing many applications in biomedicine and telecommunications, for which simple yet sensitive and fast detectors are needed.
The challenge, however, is enormous: When detectors are fast enough and operate at room temperature, they suffer from high noise levels; and when noise is minimized, some work only within a narrow frequency range and under cryogenic cooling, while others offer broadband operation but at much slower response times. Far from defeated, researchers keep seeking ways to develop the (close to) ideal THz detector—one that could potentially turn noninvasive melanoma diagnosis or high-speed wireless communication into a reality.
ICFO researchers Dr. Domenico De Fazio, Dr. Sebastián Castilla, Dr. Karuppasamy P. Soundarapandian, Dr. Simone Marconi, Riccardo Bertini and Dr. Roshan K. Kumar, led by ICREA Prof. Frank Koppens, together with Instituto de Nanociencia y Materiales de Aragón (INMA), Universidad de Zaragoza, University of Ioannina, Queen Mary University of London, University of Manchester and Catalan Institute of Nanoscience and Nanotechnology (ICN2), have now taken a step forward in that direction. The team designed a novel device based on monolayer graphene that, under liquid nitrogen cooling, emits a strong electric signal when struck by THz radiation. The results, published in ACS Photonics, open a route to build practical, tunable and selective THz detectors.
Wave-packet interferometry captures elusive dark excitons in organic superconductor
In a recent study, Manish Garg, independent group leader at Max Planck Institute for Solid State Research (MPI FKF), succeeded in probing the local properties of bright and dark excitons in the organic superconductor copper naphthalocyanine (CuNc). The findings are published in the journal Nature Communications.
This study was the result of the efforts of an international collaboration that brought together the MPI for Solid State Research in Stuttgart, the Università della Calabria and the Universidad Autónoma de Madrid.
By combining scanning tunneling microscopy with wave-packet interferometry, the authors gained remarkable—and previously inaccessible—insights into exciton dynamics. The insights gained with this technique can be of paramount importance both in the field of energy materials—where excitons play a central role in light-harvesting technologies such as solar cells—and in quantum technologies, as excitons are considered a promising platform for quantum computing.