Today’s computers store information using only two values: 0 and 1. But as electronic devices become smaller and reach their limits, scientists are searching for new ways to pack more information into the same space. One idea is to use magnetism. In some materials, atoms behave like tiny magnets that can arrange themselves in different patterns. If each pattern represents a different value, one memory element could store more than just two possibilities.

Researchers at the University of California, Los Angeles (UCLA) have developed a novel image projection system that delivers super-resolution images over an extended depth of field. By combining a neural network-based digital encoder with a passive all-optical diffractive decoder, the system drastically compresses image data for efficient transmission of image information. This platform operates without extra power at the decoding stage, promising advancements for next-generation virtual and augmented reality displays.

Quantum technologies promise powerful new kinds of computers, giving scientists new tools to mimic and explore nature at its tiniest scales. At those levels, everything in nature—from atoms and electrons to light itself—follows the strange rules of quantum mechanics. But the real world is never perfectly clean: Signals fade, energy leaks away and systems pick up noise from their surroundings.

Physicists at the University of Bayreuth have investigated the so-called Basset–Boussinesq history force acting on particles in fluids. Due to the difficulty of calculating it, this force is often neglected—a fact that Bayreuth doctoral researcher Frederik Gareis already identified as a secondary school pupil during a student research project with his supervisor. The researchers report their new findings on the history force in Physical Review Fluids.

The scale of chemistry simulations with quantum computing has increased dramatically in just the last few months. In the latest milestone for the field, researchers from Cleveland Clinic, RIKEN, and IBM used a quantum-centric supercomputing (QCSC) framework to calculate the electronic structure of a pair of large protein-ligand complexes, reaching a scale of 12,635 atoms in the largest simulation.

While neutrinos are some of the most abundant particles in the universe, they remain among the least understood. One of the biggest puzzles is their mass: although experiments have shown that neutrinos must have some mass, pinning down exactly how much has proven extraordinarily difficult.