Introduces Relational Calculus to enhance analysis and reduce computational costs in various fields.
This paper introduces Relational Calculus, a domain-agnostic meta-mathematical framework that reformulates continuous physical and computational systems in terms of intrinsic, dimensionless relationships. By anchoring variables to their natural limits (“North Stars”), the method transforms absolute measurements into universal relational templates, enabling more efficient analysis and generalization across disciplines. Applications spanning physics, engineering, and artificial intelligence demonstrate significant reductions in computational cost—over 90% in complex simulations—while preserving predictive accuracy. The framework positions itself as a strategic layer complementing continuous calculus and modern machine learning, shifting problem-solving from brute-force exploration to structural insight.
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Massimiliano Concas (2026) studied this question.
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