Aether Dynamics

AetherTwin bridges the frontier between perceptual foundation models and physical dynamical systems. While modern foundation models excel at processing visual patterns and generating text, real-world machines in aerospace, robotics, energy, and materials science require strict conservation laws, verifiable dynamical stability, and deterministic closed-loop control. AetherTwin turns raw monocular video into mathematically certified, controllable digital twins: 1. Perceptual Extraction: Ingests video and tracks kinematic features without physical markers using Meta SAM 3.1 streaming segmentation. 2. Deterministic System Identification: Fits differential equation invariants (natural frequency, linear Stokes damping, and quadratic aerodynamic drag) via Runge-Kutta 4th-order (RK4) numerical integration strictly on the first 70% of observations. 3. Generalization Certification: Evaluates predictions exclusively on the unseen 30% holdout window, certifying a 90%–98% error reduction over kinematic persistence baselines with zero data leakage. 4. Optimal Control Synthesis: Linearizes non-linear dynamics about unstable equilibria and solves the Continuous Algebraic Riccati Equation (CARE) via the Matrix Sign Function algorithm to compute optimal Linear Quadratic Regulator (LQR) feedback gains K. 5. Edge Hardware Compilation: Automatically exports ready-to-run 100 Hz ROS 2 Humble Python nodes, interrupt-driven Arduino/STM32 C++ firmware, and MATLAB/Simulink state-space models for physical robotic hardware deployment. Includes 8 multi-domain benchmarks (Falcon 9 Thrust Vector Control Booster, Taipei 101 Tuned Mass Damper, High-Viscosity Polymer Rheometer), an Extended Kalman Filter (EKF) observer, double-pendulum Lyapunov chaos detection, and 64 automated tests across 14 test suites with 100% pass rate.