Birds in flocks, bacteria and cells: In many collective systems, individual elements respond to only part of their surroundings, seemingly defying Newton’s third law of motion—action equals reaction. These exceptions are known as nonreciprocal interactions. A Dresden physics team working with Roderich Moessner, a founding member of the Würzburg–Dresden Cluster of Excellence ctd.qmat, has now developed a theory that makes it possible to describe these interactions efficiently and simulate them far more precisely.
Our universe’s expansion is still accelerating despite recent claims suggesting otherwise, an international team of astrophysicists says.
They refuted a study published last year claiming the growth of the universe is slowing and insist there is no flaw in the widely accepted theory that a mysterious force known as dark energy is driving the expanding cosmos.
The researchers, who include two Nobel laureates and represent institutions worldwide, say the debate that followed last November’s revelations was the result of a scientific misunderstanding rather than a cosmic grenade threatening to blow apart everything we know about the universe.
A 90 minute interview about AI and our human future.
Dr. Hugo de Garis is a computer scientist, AI researcher, and former professor known for his early work on evolvable hardware, artificial brains, and the long-term risks of superintelligent machines. He coined and popularized the idea of the “Artilect War,” a future conflict between those who want to build godlike artificial intellects and those who believe such systems pose an existential threat to humanity. In the interview, he describes himself as trained in pure mathematics and theoretical physics, formerly a computer science professor, and now focused on broader questions about AI, cosmology, civilization, and the future of humanity.
The interview with Prof. Hugo de Garis centers on his long-standing warning that humanity may face an “Artilect War,” a civilizational conflict over whether to build godlike artificial intellects vastly superior to humans. De Garis argues that future computation, potentially extending from nanotech to femtotech and beyond, could produce minds trillions of trillions of times more capable than ours. He distinguishes between Cosmists, who want to build such beings to expand intelligence into the universe, and Terrans, who oppose them because superintelligence may eliminate or marginalize humanity. He personally remains torn, admiring the cosmic grandeur of posthuman intelligence while recognizing the existential danger.
The conversation also covers AI timelines, recursive self-improvement, AI alignment, the U.S.-China race, the Fermi paradox, simulation theory, cyborgs, cryonics, AI-generated content, the decline of universities, and the future of work. De Garis is impressed by current AI systems, treating them almost as intellectual companions, but he doubts that humanity can guarantee long-term control over recursively improving machines. The central theme is that the question “Should humanity build artilects?” may become the defining political and moral problem of the twenty-first century.
A new theoretical study may have cracked one of the most puzzling discoveries of the James Webb Space Telescope (JWST): Little Red Dots, spotted across the early universe. The paper, posted to the arXiv preprint server on May 29, argues that these objects could be black holes caught in rare, violent bursts of feeding at a rate exceeding theoretical limits.
Since JWST began its survey of the deep universe, astronomers have been puzzled by a class of tiny, faint objects appearing in the early universe in far greater numbers than expected. They have a distinctive V-shaped spectrum—bright in both ultraviolet and optical light, but with a dip in between—along with broad emission lines hinting at active black holes. They also show an absence of X-ray, radio and infrared emission.
They don’t look like ordinary galaxies, and they don’t completely look like quasars, either. What they are has been an open question. Some researchers argue that Little Red Dots may need some outside-the-box physics to explain their origin and nature.
Using a novel simulation model based on machine learning, an international research team at GSI/FAIR has succeeded in gaining a deeper understanding of element formation in stellar events such as neutron star mergers. For the first time, the scientists used deep learning with a neural network to model the energy release during r-process nucleosynthesis in hydrodynamic simulations. The results are published in the journal Physical Review D.
Many of the chemical elements we know are created in massive stellar events such as exploding stars or neutron star mergers. These events release incredible amounts of energy, allowing for the production of heavy nuclides. One key nuclear production process is the so-called rapid neutron-capture process, or r-process, in which free neutrons are captured by existing nuclei and converted into protons—thus creating larger, heavier atomic nuclei.
“Researchers around the world strive to make these complex reactions understandable through theoretical simulations. However, modeling all parameters requires incredible computing power, which is why the models often have to be simplified,” said Dr. Oliver Just, first author of the publication and a researcher in the Nuclear Astrophysics & Structure Department at GSI/FAIR. “Our new model, RHINE, which uses artificial intelligence, offers an efficient alternative.”
Every commercial nuclear reactor in the world runs on uranium. Uranium brings three undeniable problems. It creates weapons-grade plutonium. It melts down under pressure. Its radioactive waste lasts for tens of thousands of years.
Thorium solves all three. Physicists have known this since the 1960s. The United States actually built a working thorium reactor. They proved the technology was viable. Then they deliberately abandoned it.
The hunt is over. After more than 50 years of searching, astrophysicists at Northwestern University have finally discovered evidence of a powerful wind blowing from the Milky Way’s central supermassive black hole, Sagittarius A* (Sgr A•.
According to theoretical physics and a long-accepted understanding of galaxies’ evolution, as black holes consume materials, they should produce wind or jets. Even a small amount of gas falling into a black hole should generate enough energy to push material outwards. Without wind, Sgr A* would be a unique outlier.
Inside cells, certain functions are carried out by locally adjusting molecular composition. This condensation of material results in the formation of dense droplets that can dynamically rearrange. Because of this, interactions between such dense regions determine the shaping of condensates. Scientists from the Department of Living Matter Physics at MPI-DS recently developed a model that can describe such phase separation dynamics based solely on attraction. The work is published in the journal Physical Review Letters.
“It’s natural to think that a system with only attractive forces would form one large, stationary condensate,” explained Jacopo Romano, first author of the study.
“However, instead we observed an unexpected emergent property of chasing dynamics resulting in movement and propulsion,” he said.
