Bypassing Shannon's Limit: A Kolmogorov Complexity Approach to Stateless Inverse Data Mapping and Zero-Storage Materialization (Version 2.0: Official Establishment of the 4th-Gen V2M Reconstruction Communication Protocol)

The fundamental limits of data compression and transmission, governed by Claude Shannon’s Source Coding Theorem, dictate that the physical size of lossless data cannot be reduced below its inherent entropy. Consequently, processing gigabyte-scale structured data intrinsically suffers from persistent physical network and storage bottlenecks. This paper officially proposes a structural paradigm shift in data transmission theory, declaring the obsolescence of the 'Transfer Network' era. We introduce the V2M (Vaporization-to-Materialization) Architecture, mathematically formalizing it as the industry's first "Reconstruction Communication Protocol" (RCP). By leveraging high-dimensional Mersenne Prime topological lattices (M51-M52) and deterministic inverse mappings via the J.M. generating resonance function, the system does not compress data; it mathematically evaporates (vaporizes) the state from the sender's origin and reconstitutes (materializes) it purely within the receiver's volatile memory (RAM). This framework conclusively proves that by transferring ultra-compressed 24-byte mathematical parameters instead of raw data files, data communication can bypass Shannon’s Limit, replacing physical bandwidth latency with algorithmic execution complexity and birthing the 4th-Generation Zero-Storage Communication Infrastructure.