A New Approach for Reconstructing SUSY Particle Masses with a few fb^(-1) at the LHC

TL;DR

This paper introduces a novel cascade mass reconstruction method for SUSY particles at the LHC, combining endpoint analysis, event filtering, and likelihood maximization to achieve accurate mass estimates with limited data.

Contribution

The paper presents a new integrated approach for reconstructing SUSY particle masses in long decay chains using fewer fb^(-1) of data, improving accuracy and efficiency.

Findings

Masses reconstructed with about 10% precision for heavy sparticles.

Effective background suppression via event filtering.

Stable results across multiple simulated datasets.

Abstract

We describe a new cascade mass reconstruction approach to allow reconstruction of SUSY particle masses in long cascades (five or more particles) at the LHC with integrated luminosity as low as a few fb^(-1). This approach is based on a consecutive use of the endpoint method, an event filter and a combinatorial mass reconstruction method. The endpoint method gives a preliminary estimate of light sparticle masses. An event filter combining the maximum likelihood distributions for all events in the data sample allows suppression of backgrounds and gives a preliminary estimate of heavy sparticle masses. Finally, SUSY particle masses are reconstructed by a search for a maximum of a combined likelihood function constructed for each possible combination of five events in the data sample. SUSY data sample sets for the SU3 model point containing 80k events each were generated, corresponding to an integrated luminosity of 4.2 fb^(-1). These events were passed through the AcerDET detector simulator, which parametrized the response of a detector. To demonstrate the stability and precision of the approach five different 80k event data sets were considered. Masses were reconstructed with a precision of about 10% for heavy sparticles and 10-20% for light sparticles.