Our personal identity is composed of many dimensions, such as age, gender, ethnic background, or socioeconomic status. A research team led by Fariba Karimi from the Institute of Human-Centred Computing at Graz University of Technology (TU Graz) and Samuel Martin-Gutierrez from the Complexity Science Hub developed the statistical computational model “MAPS” to calculate the influence of these factors on our social relationships. The researchers have recently published a MAPS-based analysis of high school friendships and marriages in the US in the journal Communications Physics. The study shows that humans are extremely selective.

The new AI model, called the Earth System Foundation Model, has learned the fundamental relationships between the atmosphere, the land surface and the water cycle. 

The AI model can fill in missing data and flexibly handle a wide range of data types and research questions in weather and environmental science. 

By understanding how air, land and water interact, it helps improve insight into extreme weather events such as storms or droughts. 

Researchers developed a technique to detect and measure the strength of a phenomenon called Josephson harmonics, which can cause a quantum circuit to perform differently than expected, increasing the error in computations. Their method could be used to design quantum circuits that can compensate for this effect.

CSHL Associate Professor Saket Navlakha and former graduate student Cici Zheng have discovered a naturally occurring Voronoi diagram in Chinese money plants’ leaves. Their research answers a longstanding question in biology regarding the mathematics of looping vein structures and could help explain how plants solve complex problems in nature.

A new Rice University study is shedding light on a long-debated question: Can climate variability influence the risk of armed conflict? The answer, researchers say, is yes — but in more nuanced and region-specific ways than previously understood. Led by Rice statistics doctoral student Tyler Bagwell, with climate scientist Sylvia Dee and statistician Frederi Viens, the study uses high-resolution data and empirical modeling to examine how large-scale climate patterns shape the probability of civil conflict and war.