Resolution Horizon: Finding the Mathematical Limit Where AI Overfits to Noise
Resolution Horizon explores the limits of recovering mathematical structure from noisy observations in dynamical systems.
Resolution Horizon is an experimental research framework that studies how much mathematical structure can be recovered from finite, noisy observations of dynamical systems. It proposes that structural recovery is determined by the dynamics, the observer, and available computational resources. The framework hypothesizes that every observation process has a measurable resolution horizon, beyond which additional analysis fails to reveal genuine invariants.