I’ve been lurking for a decade, but I have something worth sharing.I’m a physicist (Rice Space Physics) working on my own framework called Axiomatic Physical Homeostasis (APH), which models how Earth’s magnetosphere "relaxes" into stable shapes after solar storms.It occurred to me that Monte Carlo Path Tracing is doing it the hard way treating light like individual particles bouncing around. In plasma physics, we treat the field as a Stressed Fluid. I define a Geometric Stiffness (beta) for the vacuum and let it relax.The Experiment:- Seed: Shoot <1 ray per pixel (extremely noisy/stressed state).- Relax: Run a matrix multiplication on Tensor Cores minimizing the Geometric Stress of the light field.The Result:The light field snaps into the correct global illumination almost instantly. It preserves temporal inertia (no noise when moving the camera) because the field has mass.I’ve encrypted the whitepaper and put the Abstract/Proof on GitHub:Standard real-time ray tracing relies on Monte Carlo integration, where convergence requires millions of samples per pixel. WTS-RT (Wolf-Toffoletto-Schutza Ray Tracing) treats the radiance field as a continuous fluid governed by symplectic geometry. Using the WTS Relaxation Method originally for magnetospheric plasma modeling—the global illumination problem becomes an energy minimization problem. This achieves stable global illumination with sparse inputs (<1 ray per pixel), offloading healing of the light field to Tensor Core operations and decoupling rendering time from scene complexity.GitHub (Abstract + Encrypted Proof):https://github.com/aaronschutza/Researchhttps://github.com/aaronschutza/Research/blob/main/WTS_RTX.7zhttps://zenodo.org/communities/aph_physics
