Discovering new solutions to century-old problems in fluid dynamics
Google DeepMind
Researchers used physics-informed neural networks to discover new families of unstable singularities in fluid dynamics equations that have resisted mathematical analysis for centuries. The method achieved precision equivalent to predicting Earth's diameter to within a few centimeters, and identified a pattern in the instability parameter lambda across the Incompressible Porous Media and Boussinesq equations. The approach enables computer-assisted mathematical proofs to tackle long-standing unsolved problems in fluid dynamics, including the Millennium Prize Problem of the Navier-Stokes equations.
Why it matters
Our new method could help mathematicians leverage AI techniques to tackle long-standing challenges in mathematics, physics and engineering.
