Lifeboat Foundation

Super-resolution (SR) technology plays a pivotal role in enhancing the quality of images. SR reconstruction aims to generate high-resolution images from low-resolution ones. Traditional methods often result in blurred or distorted images. Advanced techniques such as sparse representation and deep learning-based methods have shown promising results but still face limitations in terms of noise robustness and computational complexity.

In a recent study published in Sensors, researchers from the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Sciences proposed innovative solutions that integrate chaotic mapping into SR image reconstruction process, significantly enhancing the image quality across various fields.

Researchers innovatively introduced circle chaotic mapping into the dictionary sequence solving process of the K-singular value decomposition (K-SVD) dictionary update algorithm. This integration facilitated balanced traversal and simplified the search for global optimal solutions, thereby enhancing the noise robustness of the SR reconstruction.

Gravitational waves could help us crack the case.

Using the Very Large Array (VLA), an international team of astronomers have observed a nearby galaxy merger known as CIZA J0107.7+5408. Results of the observational campaign, presented December 20 on the preprint server arXiv, could help us better understand the merging processes that take place between galaxy clusters.

Galaxy clusters contain up to thousands of galaxies bound together by gravity. They generally form as a result of mergers and grow by accreting sub-clusters. These processes provide an excellent opportunity to study matter in conditions that cannot be explored in laboratories on Earth. In particular, merging galaxy clusters could help us better understand the physics of shock and cold fronts seen in the diffuse intra-cluster medium, the cosmic ray acceleration in clusters, and the self-interaction properties of dark matter.

At a redshift of approximately 0.1, CIZA J0107.7+5408, or CIZA0107 for short, is a nearby, post-core passage, dissociative binary cluster merger. It is a large, roughly equal mass disturbed system consisting of two subclusters, hosting two optical density peaks, with associated but offset X-ray emission peaks.

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Continue reading “There Are Multiple Dimensions of TIME? | Woit and Conlon” »

For the past 30 years, NASA’s Great Observatories—the Hubble, Spitzer, Compton, and Chandra space telescopes—have revealed some amazing things about the universe. In addition to some of the deepest views of the universe provided by the Hubble Deep Fields campaign, these telescopes have provided insight into the unseen parts of the cosmos—i.e., in the infrared, gamma-ray, and ultraviolet spectrums.

With the success of these observatories and the James Webb Space Telescope (JWST), NASA is contemplating future missions that would reveal even more of the “unseen universe.”

This includes the UltraViolet Explorer (UVEX), a space telescope NASA plans to launch in 2030 as its next Astrophysics Medium-Class Explorer mission. In a recent study, a team led by researchers from the University of Michigan proposed another concept known as the Mission to Analyze the UltraViolet universE (MAUVE). This telescope and its sophisticated instruments were conceived during the inaugural NASA Astrophysics Mission Design School. According to the team’s paper, this mission would hypothetically be ready for launch by 2031.

The British-Canadian computer scientist often touted as a “godfather” of artificial intelligence has shortened the odds of AI wiping out humanity over the next three decades, warning the pace of change in the technology is “much faster” than expected.

Prof Geoffrey Hinton, who this year was awarded the Nobel prize in physics for his work in AI, said there was a “10% to 20%” chance that AI would lead to human extinction within the next three decades.

Genesis integrates various physics solvers and their coupling into a unified framework.

AI robotics training has been increased tremendously with the help of a new tool. Called ‘Genesis’, the tool is a new open-source computer simulation system.

Unveiled by a large group of university and private industry researchers, the system reportedly lets robots practice tasks in simulated reality 430,000 times faster than in the real world.

Continue reading “New physics engine lets robots practice tasks 430,000x faster” »

As the universe evolves, scientists expect large cosmic structures to grow at a certain rate: dense regions such as galaxy clusters would grow denser, while the void of space would grow emptier.

But University of Michigan researchers have discovered that the rate at which these large structures grow is slower than predicted by Einstein’s Theory of General Relativity.

They also showed that as dark energy accelerates the universe’s global expansion, the suppression of the cosmic structure growth that the researchers see in their data is even more prominent than what the theory predicts. Their results are published in Physical Review Letters.

In-plane magnetic fields unveil novel Hall effect behaviors in advanced materials, transforming our understanding of electronic transport.

Researchers from the Institute of Science Tokyo have reported that in-plane magnetic fields induce an anomalous Hall effect in EuCd₂Sb₂ films. By investigating how these fields alter the electronic structure, the team uncovered a significant in-plane anomalous Hall effect. This discovery opens new avenues for controlling electronic transport in magnetic fields, with potential applications in magnetic sensors.

The Hall effect, a fundamental phenomenon in material science, occurs when a material carrying an electric current is subjected to a magnetic field, creating a voltage perpendicular to both the current and the field. While the Hall effect has been extensively studied in materials under out-of-plane magnetic fields, the effects of in-plane magnetic fields have received comparatively little attention.