What Lies Discarded: Search for new physics from Long- Lived Particles in the ATLAS detector

Date
2020-05-04
Authors
Thiyagarajan, Vijay Venu
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At the record-breaking energies of today’s particle accelerators many types of new particles are expected to be observable. However, since 2012, no new particles have been discovered. We suspect the particles we are looking for could be long-lived particles (LLPs), for which the detectors were not designed for. The signals from protonproton collisions received by the calorimeters in the ATLAS detector at the Large Hadron Collider at CERN are converted into meaningful information about the particles through a process called reconstruction. The reconstruction at ATLAS is done by assuming most of the points in space where a parent particle decays into its daughter particles, called decay vertices, are within 15 centimetes of the center of the 25 meters wide detector. However, LLPs, as they are long-lived, have displaced decay vertices, which leads to LLP signals either being reconstructed inaccurately or discarded as uninteresting data. To reconstruct those LLP decay vertices, an algorithm was designed which used cell-level information of the calorimeter as its input. The algorithm was tested on simulations of Higgs bosons decaying into two photons at various positions in the detector. The distance between the decay vertex from the simulation (truth) and the decay vertex from the algorithm (candidate) was compared to the distance between the truth vertex and the decay vertex from the standard reconstruction (primary). If the candidate vertex was found 50-75 cm from the origin and within 25 cm from the beam pipe, or if it was found in the outer regions of the Inner Detector, i.e, the candidate vertex had 50 cm < |z| < 115 cm, or 75 cm < | r | = \sqrt{x^2 + y^2} < 115 cm, then there would be an 80 percent chance of d(candidate,truth) < d(primary, truth). This will translate to higher chances of observing statistically significant signals of LLPs when the sample size is increased many-fold.

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