Bridging the Past and Present: Implementing Ancient Indian Mathematical Techniques Using Python

Abstract: Ancient Indian Mathematics has made significant contributions to arithmetic, trigonometry and algebra, many of which continue to influence modern computational methods. Techniques such as Bhaskara I’s sine approximation and Vedic multiplication were designed for rapid mental calculations and have inspired the development of various modern algorithms. This paper explores the implementation and computational performance of two ancient Indian mathematical techniques—Vedic Multiplication and Bhaskara I’s Sine Approximation using Python. Their efficiencies are evaluated against modern numerical libraries like NumPy in terms of execution time, computational complexity and accuracy. The findings show that some ancient techniques are highly efficient for specific tasks even today. This study connects traditional mathematical knowledge with modern computational methods, emphasizing the lasting impact of Indian mathematical innovations.

Bhaskara I’s Sine Approximation, Vedic Multiplication, Mean Absolute Error, Mean Squared Error, Computational Efficiency, Absolute Error Analysis, Algorithm Development

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