Hi HN. I'm O_of_1, the creator.I'm publishing this because I've always been frustrated by the $O(N)$ memory cost of traditional simulations. If you want to rewind time, you're forced to store history, which is fundamentally impure and scales poorly.This project was my attempt to solve this by building the structure backward from an "impossible" goal.The entire system is functional, not iterative. It rejects neighbor-dependency and chaotic models (State_G+1 = f(State_G)) in favor of a pure, deterministic, and parallel-friendly equation:State_T = S ^ K(t)(State = Seed XOR Time-Key)This means the system is its own inverse; the function to generate a state and the function to reverse it are identical.The full philosophy is in the README. I've also included the original architectural sketches that show the project's philosophical origins.Happy to answer questions about the $O(1)$ approach vs. traditional RCAs.
Hi HN. I'm O_of_1, the creator.I'm publishing this because I've always been frustrated by the $O(N)$ memory cost of traditional simulations. If you want to rewind time, you're forced to store history, which is fundamentally impure and scales poorly.This project was my attempt to solve this by building the structure backward from an "impossible" goal.The entire system is functional, not iterative. It rejects neighbor-dependency and chaotic models (State_G+1 = f(State_G)) in favor of a pure, deterministic, and parallel-friendly equation:State_T = S ^ K(t)(State = Seed XOR Time-Key)This means the system is its own inverse; the function to generate a state and the function to reverse it are identical.The full philosophy is in the README. I've also included the original architectural sketches that show the project's philosophical origins.Happy to answer questions about the $O(1)$ approach vs. traditional RCAs.