Computers and Math from Science Daily Feed

A collaborative project has made a breakthrough in enhancing the speed and resolution of wide-field quantum sensing, leading to new opportunities in scientific research and practical applications.

Single-molecule magnets (SMMs) are exciting materials. In a recent breakthrough, researchers have used deep learning to predict SMMs from 20,000 metal complexes. The predictions were made solely based on the crystal structures of these metal complexes, thus eliminating the need for time-consuming experiments and complex simulations. As a result, this method is expected to accelerate the development of functional materials, especially for high-density memory and quantum computing devices.

New phased-array transmitter design overcomes common problems of CMOS technology in the 300 GHz band. Thanks to its remarkable area efficiency, low power consumption, and high data rate, the proposed transmitter could pave the way to many technological applications in the 300 GHz band, including body and cell monitoring, radar, 6G wireless communications, and terahertz sensors.

Researchers have developed a powerful new artificial intelligence model that can distinguish between male and female brains.

Researchers propose a framework for integrating online digital data into biodiversity monitoring.

Engineers have developed a new chip that uses light waves, rather than electricity, to perform the complex math essential to training AI. The chip has the potential to radically accelerate the processing speed of computers while also reducing their energy consumption.

Creating a quantum computer powerful enough to tackle problems we cannot solve with current computers remains a big challenge for quantum physicists. A well-functioning quantum simulator -- a specific type of quantum computer -- could lead to new discoveries about how the world works at the smallest scales. Quantum scientists have developed a guide on how to upgrade these machines so that they can simulate even more complex quantum systems.

Making quantum systems more scalable is one of the key requirements for the further development of quantum computers because the advantages they offer become increasingly evident as the systems are scaled up. Researchers have recently taken a decisive step towards achieving this goal.

New research shows that background checks for employment, housing and more can be highly problematic.

Throughout human history, technologies have been used to make peoples' lives richer and more comfortable, but they have also contributed to a global crisis threatening Earth's climate, ecosystems and even our own survival. Researchers have suggested that industrial civilization's best way forward may entail embracing further technological advancements but doing so with greater awareness of their potential drawbacks.

Chips and datacentres -- the 'compute' power driving the AI revolution -- may be the most effective targets for risk-reducing AI policies as they have to be physically possessed, according to a new report.

Ferromagnetism and antiferromagnetism have long been known to scientists as two classes of magnetic order of materials. Back in 2019, researchers postulated a third class of magnetism, called altermagnetism. This altermagnetism has been the subject of heated debate among experts ever since, with some expressing doubts about its existence. Recently, a team of experimental researchers was able to measure for the first time at DESY (Deutsches Elektronen-Synchrotron) an effect that is considered to be a signature of altermagnetism, thus providing evidence for the existence of this third type of magnetism.

The fields of chemistry and materials science are seeing a surge of interest in 'self-driving labs,' which make use of artificial intelligence and automated systems to expedite research and discovery. Researchers are now proposing a suite of definitions and performance metrics that will allow researchers, non-experts, and future users to better understand both what these new technologies are doing and how each technology is performing in comparison to other self-driving labs.

Researchers have discovered how to make an optical metamaterial that would underpin a variety of new technologies.

Physicists have uncovered that Josephson tunnel junctions -- the fundamental building blocks of superconducting quantum computers -- are more complex than previously thought. Just like overtones in a musical instrument, harmonics are superimposed on the fundamental mode. As a consequence, corrections may lead to quantum bits that are 2 to 7 times more stable. The researchers support their findings with experimental evidence from multiple laboratories across the globe.

There is now a new addition to the magnetic family: researchers have demonstrated the existence of altermagnetism. The experimental discovery of this new branch of magnetism signifies new fundamental physics, with major implications for spintronics.

Scientists have achieved a milestone by controlling quantum phenomena at room temperature.

The properties of supramolecular polymers are dictated by the self-assembled state of the molecules. However, not much is known about the impact of morphologies on the properties of nano- and mesoscopic-scale polymeric assemblies. Recently, a research team demonstrated how terminus-free toroids and random coils derived from the same luminescent molecule show different photophysical properties. The team also presented a novel method for purifying the toroidal structure.

Chiral skyrmions are a special type of spin textures in magnetic materials with asymmetric exchange interactions. They can be treated as quasi-particles and carry integer topological charges. Scientists have recently studied the random walk-behaviors of chiral skyrmions by simulating their dynamics within a ferromagnetic layer surrounded by chiral flower-like obstacles. The simulations reveal that the system behaves like a topological sorting device, indicating its use in information processing and computing devices.

New research establishes that the metric used to measure link prediction performance is missing crucial information, and link prediction tasks are performing significantly worse than popular literature indicates.