The "Micro gravity regression AI self-regulation system" is not just an indicator; it is a physical simulation system based on the four-dimensional space of Price-Volume-Time-Entropy. Through the layered analysis of the code logic, we see that it uses the "density" of micro-data to build a gravitational field, uses "entropy" to regulate time perception, and uses "AI" to correct physical constants. This interdisciplinary fusion provides a brand-new analytical perspective for quantitative trading based on first principles. Traditional technical indicators (such as MA, RSI) are mostly based on linear processing of closing prices, which often results in lag and difficulty in capturing the internal gaming details of price. With the development of high-frequency trading, data based on Order Flow and microstructure has become crucial. The MicroStructure HUD system proposed in this study no longer views price merely as a numerical sequence but as a physical entity with "Mass" and "Energy." By simulating the Center of Mass (CoM) in a physical field and the elastic tension under Hooke's Law, it reveals the intrinsic driving forces of price movement.