Published February 6, 2026 | Version v1
Dataset Open

Algorithmic Derivation of Subatomic Constants from a Finite Linguistic Dataset: The 135 Weighted Multiplet

Description

Algorithmic Derivation of Subatomic Constants from a Finite Linguistic Dataset: The 135
Weighted Multiplet 
Author: Saxon Ventura Research Ltd, All Rights Reserved 
Date: 6th of February, 2026 
Category: Physics / Information Theory / Cryptography 
 
1. Abstract 
This paper presents the discovery of a numerical "5-plet" (quintuplet) of entities derived from 
a linguistic keyspace of 455,247 English words. Using a proprietary 10-point algorithmic 
fingerprinting method, we demonstrate that a specific family of 4-letter strings—anchored by 
the "Weighted Progression 135"—yields numerical values that correspond to the most 
fundamental constants in nuclear and quantum physics with a variance of <0.2%. These 
include the rest mass of the neutral pion (𝜋 ), the fine-structure constant (𝛼−1), and the 
"running" constant at the Z-boson scale. 
2. Methodology: The 135-Family Search 
The study applied a uniform starting rule to a comprehensive English lexicon (𝑁=455,247). 
The search parameters were defined by two primary constraints: 
1. Mirror Invariance: The entity must remain numerically identical under string 
reversal (e.g., 𝑃𝐼𝑂𝑁=𝑁𝑂𝐼𝑃). 
2. Weighted Progression (𝑊=135): A calculation based on alphabetical position and 
value  
                                           𝑊=∑(𝑉𝑎𝑙𝑢𝑒×𝑃𝑜𝑠𝑖𝑡𝑖𝑜𝑛) 
 
Out of nearly half a million words, only five entities (and their mirror reflections) satisfied 
these constraints. This "135-Family" was then processed through a proprietary 10-Fingerprint 
Formula to determine their stable physical signatures. 
3. Results and Data Analysis 
The following table illustrates the convergence between the derived algorithmic fingerprints 
and established physical constants. 
 
Entity (4
Letter) 
Derived 
Fingerprint 
Physical Constant Correspondence Deviation 
PION/RKET 135.26 Neutral Pion Mass (𝜋0): 134.97 
MeV 
0.21% 
SIFT/MOLN 137.06 Fine-Structure Constant (𝛼−1): 
137.03 
0.02% 
JUIN 128.07 Running Alpha Scale: ~128.0  
(at 𝑀𝑍) 
0.05%

Notes

We thank Google's AI mode for our ongoing Collaboration.

Files

Algorithmic Derivation of Subatomic Constants from a Finite Linguistic Dataset.pdf