A Statistical Framework for Automating Resonance Detection: Modelling Pion Proton Collision Activity

Authors

Shahnaz Abdul Hameed, Indian Institute of Technology Joghpur

Mentor

Maxim Mai, The George Washington University.

Publication Date

Summer 2023

Document Type

Paper

DOI

10.25776/eg99-c583

Pages

1-6 pp.

Abstract

In this paper, we analyze π− − p elastic collision data from the Particle Data Group (PDG), by creating a general framework to study resonance activity: automating peak detection, extrapolating, parametrizing thresholds, filtering resonances and further comparing and extracting characteristics, to identify Delta (Δ) baryons. We then analyse experimental Energy vs Phase-Shift (δ) data for the collision π+ +π− → π− +π+, model the T matrix from a curve fitted polynomial representation of the K⁻¹ matrix, simulate its Riemann sheets and analyse it to identify the characteristics of ρ⁰(770) meson, as well as estimate their uncertainties. These methodologies offer a foundation for similar analyses in different systems and events.

Repository Citation

Hameed, Shahnaz Abdul, "A Statistical Framework for Automating Resonance Detection: Modelling Pion Proton Collision Activity" (2023). 2023 REYES Proceedings. 11.
https://digitalcommons.odu.edu/reyes-2023/11