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AUTHOR(S): Alessio Drivet
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ABSTRACT This study investigates the integration of computational methods—specifically the Python programming language—into the exploration and empirical testing of mathematical theorems and conjectures. The distinction between formally proven theorems and conjectures, which remain unproven but are widely believed to be true, serves as the conceptual framework. Three case studies are presented: a numerical verification of Pick’s Theorem; an algorithmic test of Goldbach’s Conjecture up to a user-specified bound; and a novel, AI-generated conjecture concerning “prime jump permutations,” examined through exhaustive enumeration. While emphasizing the inherent limitations of computational experimentation in place of formal proof, this work also highlights the value of such approaches in supporting mathematical intuition, facilitating pattern recognition, and stimulating conjecture formulation. The results underscore the growing role of programming and artificial intelligence in contemporary mathematical inquiry. |
KEYWORDS Theorems, Conjectures, Python, Computational Mathematics |
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Cite this paper Alessio Drivet. (2025) Theorems and Conjectures with Python. International Journal of Computers, 10, 133-137 |
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