An iterative method to estimate the combinatorial background

TL;DR

This paper introduces an innovative iterative method for estimating combinatorial background in heavy ion collision data, enabling more accurate reconstruction of broad resonances without relying on input models.

Contribution

The paper presents a novel iterative approach that identifies signal and background contributions without prior normalization models, validated on simulated data.

Findings

Successfully reconstructs resonant signals in simulated heavy ion collision data.

Demonstrates the method's effectiveness in high multiplicity environments.

Provides a powerful tool for analyzing broad resonances in complex events.

Abstract

The reconstruction of broad resonances is important for understanding the dynamics of heavy ion collisions. However, large combinatorial background makes this objective very challenging. In this work an innovative iterative method which identifies signal and background contributions without input models for normalization constants is presented. This technique is successfully validated on a simulated thermal cocktail of resonances. This demonstrates that the iterative procedure is a powerful tool to reconstruct multi-differentially inclusive resonant signals in high multiplicity events as produced in heavy ion collisions.