The Yamato Computational Framework: High-Performance Mathematical-Physical Synthesis via Pneuma Constant Optimization and Discrete Modular Architecture
Year: 2026
Type: article
Abstract: This paper introduces the Yamato Computational Framework, a high-performance computational architecture implemented in Python and NumPy that integrates classical mechanics principles, historical mathematical algorithms (rooted in the works of Al-Khwarizmi and Al-Jazari), and discrete modular systems. To rigorously evaluate its performance, the framework is tested under strict empirical protocols, including Op-Count Equalization, Alternating-Order Benchmarking, and Divisor-Sweep Analysis, which confirms a scalar divisor value of 1200 as the optimal stable parameter. Furthermore, the framework introduces the fundamental Pneuma constant (\Upsilon_{\text{pneuma}} \approx 1.6180342823) alongside the Persica laws to address infinite divergences and singularities across major scientific problems—such as QED, gravitational and Planck constants, the Riemann Hypothesis, Navier-Stokes equations, and the Poincaré conjecture—utilizing integer-based bitwise masking (np.int32). Ultimately, this work emphasizes that modern computational science should intertwine rigorous technological optimization with historical scientific roots and ethical values. Computational Framework; Mathematical Physics; Pneuma Constant; High-Performance Computing; Singularities Resolution; Algorithmic Synthesis
Author: Fakhri, Ahmad
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7203473810