📄 Paper Versions

• 🔹 Latest Version (Revised July 21, 2025):
  [P_vs_NP210725.pdf)

• 🔸 Previous Version (Before July 2025):
  [P_vs_NP(SUBSET_SUM)(Pre July 2025).pdf]

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✅ This repository contains the theoretical development and Python implementation related to the Subset Sum problem with fixed subset length

Structured Polynomial-Time Subset Sum This repository presents a self verified and rigrously developed attempt at a polynomial-time solution to the NP-complete Subset Sum problem. However, the work is currently ** under formal review at the Zenodo platform**. While it has not yet undergone external peer review or endorsement, it is shared here transparently for open scientific dialogue and constructive discussion. This repository contains the research, code, and documentation for a proposed polynomial-time solution to the Subset Sum problem — a cornerstone in P vs NP theory.

The work explores structured input evaluation using log and exponential transformations while rigorously preserving polynomial time and space complexity. It offers a constructive counter-view to the traditional belief that Subset Sum belongs to the NP-hard class beyond polynomial reach.

Author

Minakshi Aggarwal
Independent Researcher
ORCID | Zenodo Submission

Repository Contents

-Declaration.pdf -Subset Sum, P vs NP, Polynomial Time, NP-Complete, Ownership Declaration, Algorithmic Research

• P VS NP(SUBSET_SUM).py – core solver with polynomial guarantee
• P vs NP210725.tex - Revised version of LaTeX file for the academic write-up
• P VS NP (SUBSET_SUM).tex – Old version of LaTeX file for the academic write-up
• P vs NP210725.pdf – Revised compiled version of the research paper
• [P_vs_NP(SUBSET_SUM)(Pre July 2025).pdf] - Old version of the research paper
• P VS NP(SUBSET_SUM)output.jpg – visual summary or explanatory illustration
• stress1000k.jpeg - visual screenshot of output
• stress_graph.jpeg - visual comparative or explanatory illustration
• README.md – this file
• metadata.txt, license.txt, zenodo.txt – auxiliary files for archiving

📌 Published Version

This research has been officially archived and assigned a DOI by Figshare.

🔗 View on Figshare

License

Released under CC BY 4.0 – use with attribution. Developed by: Minakshi Aggarwal