All articles tagged with #dusty plasma
Researchers at Emory used a physics-guided neural network trained on limited 3D particle-trajectory data from dusty plasma to reveal non-reciprocal inter-particle forces with over 99% accuracy, challenging some standard assumptions about charge-related scaling and distance decay and demonstrating a general AI workflow to discover new physical laws in complex many-body systems.
Physicists at Emory used a physics-tailored neural network trained on 3D dusty-plasma data to reveal precise, non-reciprocal inter-particle forces, correct key theoretical assumptions, and propose a universal AI-based framework for inferring physical laws in complex many-body systems.
A new study demonstrates that an AI system can independently discover and describe new physics related to dusty plasma, correcting previous misconceptions and providing detailed predictions, showcasing AI's potential as a tool for scientific discovery.
Physicists at Emory University used AI and neural networks to discover new physics in dusty plasma, correcting previous assumptions and providing precise models of non-reciprocal forces, with potential applications across various complex systems.