Dynamic Matrix Logic (DML): Version 2 — Extension to Geometric Sequences with Invariant Noise

This work is an official extension of Dynamic Matrix Logic (DML) Version 1. While the previous version explored the Fibonacci sequence, Version 2 focuses on Geometric Sequences (r=2). In this version, we report a major discovery: the emergence of a scale-invariant noise behavior, which we define as the Adya Constant (η). By identifying this constant (η = 4096/4095), DML achieves 100% computational precision in target reconstruction through divergent paths (DML-4 and DML-8). The results presented in this paper prove that what was previously perceived as dynamic noise in binary systems can be quantified as a fixed structural residue, providing a new framework for data integrity, cryptography, and geometric deconstruction.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-12
DOI
https://doi.org/10.5281/zenodo.18221276
Primary Topic
Cryptographic Implementations and Security
Type
article
Field-Weighted Citation Impact
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article

Dynamic Matrix Logic (DML): Version 2 — Extension to Geometric Sequences with Invariant Noise

Adya Reza Pahlevi
Zenodo (CERN European Organization for Nuclear Research)
Cryptographic Implementations and Security
article

Dynamic Matrix Logic (DML): Version 2 — Extension to Geometric Sequences with Invariant Noise

Adya Reza Pahlevi
article en

Abstract

This work is an official extension of Dynamic Matrix Logic (DML) Version 1. While the previous version explored the Fibonacci sequence, Version 2 focuses on Geometric Sequences (r=2). In this version, we report a major discovery: the emergence of a scale-invariant noise behavior, which we define as the Adya Constant (η). By identifying this constant (η = 4096/4095), DML achieves 100% computational precision in target reconstruction through divergent paths (DML-4 and DML-8). The results presented in this paper prove that what was previously perceived as dynamic noise in binary systems can be quantified as a fixed structural residue, providing a new framework for data integrity, cryptography, and geometric deconstruction.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 91%
Cryptographic Implementations and Security
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