The series that IISc scientists have stumbled upon combines specific parameters in such a way that scientists can rapidly arrive at the value of pi and use the same in calculations.
Indian Institute of Science (IISc) scientists have discovered a new series representation for the irrational number pi while investigating how string theory can be used to explain certain physical phenomena. It offers a simpler method of retrieving 'pi' from algorithms related to deciphering phenomena such as high-energy particle quantum scattering.
The representation of ‘pi’ proposed by Indian mathematician Sangamagrama Madhava in the 15th century, which was the first series for pi ever documented in history, is nearly approached by the new formula under some limits. The researchers behind the study were Aninda Sinha, a professor at the Centre for High Energy Physics (CHEP), and Arnab Saha.
Saha was searching for an effective approach to illustrate these particle interactions while working on the optimization problem. Saha and Sinha made the decision to combine two mathematical tools i.e. the Feynman Diagram and the Euler-Beta Function, to create an effective model. Mathematical functions called Euler-Beta functions are utilized to solve issues in many branches of engineering and science, including machine learning. The energy exchange that takes place when two particles encounter and the scatter is explained mathematically by the Feynman Diagram.
Consequently, The group discovered a series representation of ‘pi’ in addition to an effective model that explains particle interaction.
“Our efforts, initially, were never to find a way to look at pi. All we were doing was studying high-energy physics in quantum theory and trying to develop a model with fewer and more accurate parameters to understand how particles interact. We were excited when we got a new way to look at pi,” Sinha says.
In mathematics, a series is used to represent a parameter such as pi in its component form. If pi is the “dish” then the series is the “recipe”. Pi can be represented as a combination of many numbers of parameters (or ingredients).
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