Spectral shaper provides unprecedented control over 10,000 laser frequency comb lines
Peer-Reviewed Publication
Updates every hour. Last Updated: 31-Oct-2025 23:11 ET (1-Nov-2025 03:11 GMT/UTC)
Researchers from China present a new framework to simulate how black hole images change over time, focusing on rotating regular black holes with nonsingular cores. Using spatio-temporal random fields and efficient light ray tracing, the model captures realistic brightness fluctuations, turbulence, and light-travel effects around the black hole. The simulated results reproduce time-varying features like the shifting bright ring seen in M87*, offering a fast, physically grounded alternative to full GRMHD simulations and paving the way for future dynamic black hole imaging studies.
As cities grow denser and hotter, creating space for greenery becomes increasingly difficult. To address this challenge, researchers from Chiba University developed a data-driven framework that integrates artificial intelligence and spatial analysis to map vertical greenery across Tokyo’s 23 wards. By analyzing over 80,000 street-view images, the team identified uneven distribution patterns and proposed a vertical greening demand index to guide future urban greening initiatives and climate-resilient urban planning.
Crystal structure prediction (CSP) of organic molecules is a critical task, especially in pharmaceuticals and materials science. However, conventional methods are computationally intensive and time-consuming. Now, researchers from Japan have developed a new workflow: SPaDe-CSP that accelerates CSP by machine learning-based prediction of most probable space groups and crystal densities and employing an efficient neural network potential for structure refinement. It achieved faster and more reliable CSP than conventional methods.