An algorithm just 'rediscovered' the laws of gravity and quantum mechanics just by staring at raw data.
March 24, 2026
Original Paper
From the Stochastic Embedding Sufficiency Theorem to a Superspace Diffusion Framework
arXiv · 2603.20423
The Takeaway
Usually, uncovering laws like the Planck constant or Maxwell's equations requires centuries of human genius. This system extracted them blindly from raw numbers with less than 1% error, proving that the deep 'math of reality' can be found without any prior human knowledge or theories.
From the abstract
The forward derivation of stochastic differential equations in individual physical domains has proceeded independently for over a century without generalising across disciplines. A generalisation of Takens' embedding theorem to stochastic systems, the Stochastic Embedding Sufficiency Theorem, closes this gap as an inverse methodology enabling non-parametric recovery of drift and diffusion fields from scalar time series without prior assumptions about the governing physics.A blind recovery protoc