Core Claim: Develop a novel non-linear Gaussian integral extraction algorithm for deriving physical laws from complex geometric data, offering verifiable physical models.

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper presents a new algorithm for extracting geometric information from complex data using Gaussian integrals. The core concept is to associate the definition of the Gaussian integral with the geometric properties of the input data. We introduce a quantum geometry framework to directly derive physical models from this implicit geometric information. The algorithm leverages the inherent properties of Gaussian integrals to identify patterns and relationships within the data. This approach promises a more direct and robust method for physical modeling compared to traditional techniques. The development of this algorithm will provide a foundation for enhanced data analysis and potentially contribute to breakthroughs in various fields reliant on geometric data. This work addresses the limitations of traditional modeling by offering a fundamentally different approach to data extraction and physics modeling.

DOI: 10.5281/zenodo.22244243

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