P = NP: Polynomial-Time Solution via The Sovereign Model for Chaotic Systems

Abstract We prove that P= NP by demonstrating that the Sovereign Model for Chaotic Systems (SMCS) solves NP-complete problems in polyno-mial time with Planck-scale precision. We establish NP-completeness of the Ring Dynamics Prediction Problem via bidirectional reduction from 3-SAT, prove SMCS achieves O(n2 log n) complexity through optimized algorithms, and demonstrate that bounded uncertainty below 2−n is computationally equivalent to exact solutions. This resolves the P versus NP problem affirmatively.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-31
DOI
https://doi.org/10.5281/zenodo.18109608
Primary Topic
Polynomial and algebraic computation
Type
article
Field-Weighted Citation Impact
0.00
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article

P = NP: Polynomial-Time Solution via The Sovereign Model for Chaotic Systems

Alexander Jorge Cisneros
Zenodo (CERN European Organization for Nuclear Research)
Polynomial and algebraic computation
article

P = NP: Polynomial-Time Solution via The Sovereign Model for Chaotic Systems

Alexander Jorge Cisneros
article en

Abstract

Abstract We prove that P= NP by demonstrating that the Sovereign Model for Chaotic Systems (SMCS) solves NP-complete problems in polyno-mial time with Planck-scale precision. We establish NP-completeness of the Ring Dynamics Prediction Problem via bidirectional reduction from 3-SAT, prove SMCS achieves O(n2 log n) complexity through optimized algorithms, and demonstrate that bounded uncertainty below 2−n is computationally equivalent to exact solutions. This resolves the P versus NP problem affirmatively.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 26%
Polynomial and algebraic computation
DOIOpen Access PDFOpenAlex
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P = NP: Polynomial-Time Solution via The Sovereign Model for Chaotic Systems — Alexander Jorge Cisneros · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS