Astronomers have discovered patterns of regularity within the chaotic three-body problem, which is a fundamental challenge in physics. The researcher's findings suggest that certain configurations of three massive objects can lead to predictable outcomes, offering new insights into astrophysics and the behavior of black holes.
A new study by Kyu-Hyun Chae found conclusive evidence for the breakdown of standard gravity in low acceleration limit using up to 26,500 wide binaries observed by Gaia. The results show a boost factor of 30-40% higher than Newton-Einstein prediction, meeting conventional criteria of 5 sigma significance.
Researchers at the University of Missouri have developed a smart material prototype that can control the direction and intensity of energy waves. This breakthrough could have significant implications for various fields, including military and commercial applications.
Researchers investigated open star clusters, finding they dissolve faster than predicted by Newton's laws. The team developed a new method to count stars in tidal tails, revealing a significant difference in the number of stars between the front and rear tails.
Researchers from ETH Zurich conducted a new experiment to redetermine the gravitational constant G, obtaining a value 2.2% higher than the current official figure. The team used a dynamic measurement method involving resonating beams, allowing for real-time data analysis and minimization of interference.
Researchers developed AI that extracts hidden equations of motion from observational data, creating models faithful to the laws of physics. This enables physics-based investigations and simulations for ecosystem sustainability, among other applications.
A novel machine learning algorithm developed by Princeton physicist Hong Qin accurately predicts planetary orbits without using traditional physics laws. The technology has potential applications in predicting plasma behavior in fusion facilities, challenging the fundamental role of theories in science.
A new survey more than doubles the known number of copies of Isaac Newton's groundbreaking science book, challenging the idea that it was only read by expert mathematicians. The research suggests that the Principia was widely read and comprehended in 17th-century Europe.
The study establishes relationships between game progress and entertainment experiences using Newtonian laws of motion, revealing the player's mental state. The game refinement theory explores fundamental mechanisms of game playing mechanics, mapping different cultures to human mind sophistication.
Researchers at Hebrew University of Jerusalem use traditional mathematics to predict planets' movements in unstable three-body systems. Their findings provide a new understanding of these complex processes and are essential for visualizing complicated phenomena.
Researchers at MIT have created an algorithm that significantly speeds up the planning process required for robots to adjust their grasp on objects. The new approach uses motion cones to efficiently calculate feasible pushes and reposition objects in less than a second, compared to traditional algorithms that take over 500 seconds.
The proposed Parallel Intelligence framework enables machines to learn from real-world interactions, moving beyond traditional AI approaches that rely on big data. This new paradigm allows software to learn from millions of scenarios and make decisions in parallel with physical systems.
Researchers used Modified Newtonian Dynamics (MOND) to predict velocity dispersion in faint dwarf galaxies of Andromeda. In 16 out of 17 cases, their predictions matched the measured velocity dispersions, suggesting that MOND may be a viable alternative to dark matter.
Researchers teach computer to find regularities in nature that become established laws without prior knowledge, applicable to biology, cosmology, and complex systems. The algorithm tests equations against known derivatives, repeats until accurate equations are found.