Abstract
We introduce a novel approach for the reconstruction of particle properties for the SHiP detector. The SHiP experiment significantly focuses on finding effects of dark matter particle interaction. A characteristic trace of such an interaction is an electromagnetic shower. Our algorithm aims to reconstruct the energy and origin of such showers using online Target Tracker subdetectors that do not suffer from pile-up. Thus, the online observation of the excess of events with proper energy can be a signal for a dark matter. Two different approaches were applied: classical, using Gaussian Mixtures and machine learning based on a convolutional neural network. We’ve refined the output of the previous step by clusterization techniques to improve transverse coordinate estimation. The obtained results are 25% for energy resolution, 0.8 cm for position resolution in the longitudinal direction and 1 mm in the transverse direction, without any usage of the emulsion.
Highlights
The SHiP experiment [1] is dedicated to the search for Beyond the Standard Model physics
One can search for Dark Matter (DM) scattering on electrons in the SHiP scattering detector
The detector consists of lead, an emulsion and target trackers (TT)
Summary
The SHiP experiment [1] is dedicated to the search for Beyond the Standard Model physics. In order to search for DM signatures, one must detect electromagnetic showers (EM) in either the emulsion or target trackers. It is challenging to identify energy and position of the initial particle in a particular scattering event in TT since the sampling frequency of TT is much smaller than of the emulsion. Data sample The electromagnetic shower is a cone-like structure, consisting of particles (hits), detected in emulsion. The collaboration is currently considering the possibility to identify events associated with Dark Matter, using target trackers, without emulsion. The events are determined by the energy of the initial particle and the vertex location. The vertex location will be determined by the distance d to the first TT plane This distance will vary from 0 to -7.5 cm, and all events are uniformly distributed in it. The response of the detector is described by the ”picture of hits”
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