Science

A new generation of AI is learning to predict and understand motion, opening doors for advanced applications across robotics, autonomous systems, and beyond.

Researchers have discovered a method to enhance the intrinsic ‘trembling’ motion of relativistic electrons, potentially opening a pathway for direct observation and a deeper understanding of fundamental quantum phenomena.

Researchers demonstrate a novel method for generating and sustaining multi-particle entanglement in optomechanical systems using precise control of dark modes and mechanical coupling.

Researchers have developed a new optimization algorithm to overcome key limitations in relativistic continuous tensor networks, paving the way for more accurate simulations of complex quantum systems.

New research demonstrates that the Generalized Born Rule, a cornerstone of quantum theory, emerges naturally from the fundamental principles of probabilistic processes rather than being an arbitrary postulate.

New research reveals how ring-like structures within protoplanetary disks influence the movement of planets, leading to varied migratory fates.

New research provides a geometric framework for understanding and certifying quantum advantages in high-dimensional systems by analyzing the relationship between state fidelity and deviation.

New research reveals that decoherence significantly alters the predictions of Fermi’s Golden Rule for modeling electron dynamics, challenging long-held assumptions in quantum mechanics.

Researchers have developed a novel geometric framework to quantify entanglement using the curvature of projective Hilbert space.

Researchers have developed a versatile technique for generating complex quantum states of light, paving the way for more powerful quantum information processing.