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March 1, 2026Open Access

Bypassing Shannon's Limit: A Kolmogorov Complexity Approach to Stateless Inverse Data Mapping and Zero-Storage Materialization

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Authors

MJMin Ho Jung

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Overview

Presents a novel architecture that achieves lossless data reconstruction in volatile memory, suggesting transformative implications for distributed computing.

Key Points

  • To explore a new approach for data compression and restitution that transcends Shannon's limits using Kolmogorov complexity.
  • Developed a framework that uses a high-dimensional Mersenne Prime Lattice Engine.
  • Defined an Inverse Mapping protocol to facilitate data reconstruction.
  • Utilized a localized phase coordinate for reconstructing original data from minimal descriptors.
  • Achieved 100% bit-for-bit integrity in data reconstruction.
  • Bypassed traditional storage I/O constraints entirely.
  • Showed that gigabyte-scale structured data can be processed without physical storage requirements.

Cite This Study

Min Ho Jung (2026) studied this question.

synapsesocial.com/papers/69a3d824ec16d51705d2eaebhttps://doi.org/10.5281/zenodo.18808516
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  1. 1Bypassing 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)2026
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  3. 3Data Materialization over Transmission: Kolmogorov Inverse Mapping via M51 High-Dimensional Lattice Resonance and JM Deterministic Generators2026
  4. 4The Absolute Zero-Storage Protocol: Stateless Materialization Architecture for the Post-Quantum Era2026
  5. 5Bypassing Shannon's Limit: Zero-Payload Topological Communication via Latent Spatiotemporal Resonance (Phase 4.1 Empirical Proof)2026