Design and Expected Performance for an hKLM at the EIC

TL;DR

This paper presents a novel iron-scintillator sampling calorimeter design for the Electron Ion Collider, integrating machine learning for optimization, with capabilities for timing, particle identification, and improved resolution.

Contribution

The design uniquely combines multi-dimensional readout and machine learning-driven optimization to enhance detector performance at lower costs.

Findings

Achieves 10% momentum resolution for low-energy neutral hadrons using time-of-flight.

Demonstrates calorimetric energy resolution surpassing similar less granular detectors.

Integrates machine learning from design to performance optimization.

Abstract

We describe the design concept and estimated performance of an iron-scintillator sampling calorimeter for the future Electron Ion Collider. The novel aspect of this detector is a multi-dimensional readout coupled with foreseen excellent timing resolution, enabling time-of-flight capabilities as well as a more compact overall assembly. Machine learning has been integrated into the detector design process from the ground up. Detector design objectives are defined using Machine Learning based reconstruction and Machine Learning is used to optimize the detector design. The highly segmented readout is implemented with Machine Learning algorithms in mind to reach performance levels usually reserved for much more expensive detector systems. The primary physics objective is to serve as a muon detector/ID system and a neutron hadron calorimeter. In EIC kinematics, charged particles are best measured through tracking rather than calorimetry, but the hKLM can identify and measure the momentum of neutral hadrons. The latter are mainly $K_L$'s and neutrons: for lower energies, excellent relative momentum measurements of a few 10\% are achieved using time of flight, while for higher particle momenta, the energy can be measured calorimetrically with a resolution significantly better than that demonstrated for similar calorimeters read out with less granularity.