Lifeboat Foundation

Scientists from the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory have created the first-ever atomic movies showing how atoms rearrange locally within a quantum material as it transitions from an insulator to a metal. With the help of these movies, the researchers discovered a new material phase that settles a yearslong scientific debate and could facilitate the design of new transitioning materials with commercial applications.

Despite its immense success in describing the fundamental building blocks of matter and their interactions, the Standard Model of particle physics is known to be incomplete. Experiments around the globe and in space are therefore searching for signs of new physics phenomena that would guide physicists towards a more comprehensive theory.

The key to developing quantum electronics may have a few kinks. According to a team led by researchers at Penn State, that’s not a bad thing when it comes to the precise control needed to fabricate and operate such devices, including advanced sensors and lasers.

The formation of a black hole from light alone is permitted by general relativity, but a new study says quantum physics rules it out.

Black holes are known to form from large concentrations of mass, such as burned-out stars. But according to general relativity, they can also form from ultra-intense light. Theorists have speculated about this idea for decades. However, calculations by a team of researchers now suggest that light-induced black holes are not possible after all because quantum-mechanical effects cause too much leakage of energy for the collapse to proceed [1].

The extreme density of mass produced by a collapsed star can curve spacetime so severely that no light entering the region can escape. The formation of a black hole from light is possible according to general relativity because mass and energy are equivalent, so the energy in an electromagnetic field can also curve spacetime [2]. Putative electromagnetic black holes have become popularly known as kugelblitze, German for “ball lightning,” following the terminology used by Princeton University physicist John Wheeler in early studies of electromagnetically generated gravitational fields in the 1950s [3].

In most neutral-atom quantum computers, atoms are held in arrays of optical tweezers. Researchers typically populate the arrays stochastically, meaning that whether a given site receives an atom is down to chance. Atoms can later be rearranged individually, but the total number of atoms depends on the success of the initial loading.

The Atom Computing team developed an iterative process to fill an array to capacity. Instead of filling the array directly, the researchers first stochastically populated a second “reservoir” array. They then transferred atoms one by one from this reservoir to the target array using an optical tweezer. Between each loading step, the researchers imaged both arrays to determine which sites in each array were occupied. This step required temporarily switching off the tweezers and holding the atoms in an optical lattice formed from interfering laser beams.

The researchers showed that this sequence could be repeated as many times as necessary without losing atoms from the target array. They also showed that they could limit atom loss during the imaging step by enhancing the lattice strength using optical cavities. This enhancement allowed the atoms to be more strongly confined without increasing the optical lattice’s laser-power requirements.

The mechanisms of recognition and response to emotional stimuli are not fully understood. Here, the authors reveal tuning to semantic and emotional image features within occipital temporal cortex that efficiently encodes information suited to guiding behavior.

Study: AI “incest” may cause model collapse for tools like ChatGPT, Microsoft Copilot.

It’s like Game of Thrones, but for artificial intelligence large language models.

The technology not only aids in robot survival, it enables dynamic shape-change.

The idea of the brain as a computer is everywhere. So much so we have forgotten it is a model and not the reality. It’s a metaphor that has lead some to believe that in the future they’ll be uploaded to the digital ether and thereby achieve immortality. It’s also a metaphor that garners billions of dollars in research funding every year. Yet researchers argue that when we dig down into our grey matter our biology is anything but algorithmic. And increasingly, critics contend that the model of the brain as computer is sending scientists (and their resources) nowhere fast. Is our attraction to the idea of the brain as computer an accident of current human technology? Can we find a better metaphor that might lead to a new paradigm?