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At least 559 records · Page 31

Design and simulated performance of calorimetry systems for the ECCE detector at the electron ion collider

Here, we describe the design and performance the calorimeter systems used in the ECCE detector to achieve the overall performance specifications cost-effectively with careful consideration of appropriate technical and schedule risks. The calorimeter systems consist of three electromagnetic calorimeters, covering the combined pseudorapidity range from -3.7 to 3.8 and two hadronic calorimeters covering a combined range of -1.1<η<3.8. Key calorimeter performances which include energy and position resolutions, reconstruction efficiency, and particle identification will be presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders

Calorimeters with dual readout measure both scintillation and Cherenkov light produced in their active media. They offer improvements in energy resolution and, therefore, have become increasingly interesting due to the need for precision jet measurements at Higgs factories. Furthermore, this paper presents GEANT4 simulations of single-particle responses in sampling and homogeneous calorimeters, and demonstrates the effect of inclusion of Cherenkov light in the reconstruction of energies.

Detector modeling and simulations↗

A low-latency graph computer to identify metastable particles at the Large Hadron Collider for real-time analysis of potential dark matter signatures

Abstract Image recognition is a pervasive task in many information-processing environments. We present a solution to a difficult pattern recognition problem that lies at the heart of experimental particle physics. Future experiments with very high-intensity beams will produce a spray of thousands of particles in each beam-target or beam-beam collision. Recognizing the trajectories of these particles as they traverse layers of electronic sensors is a massive image recognition task that has never been accomplished in real time. We present a real-time processing solution that is implemented in a commercial field-programmable gate array using high-level synthesis. It is an unsupervised learning algorithm that uses techniques of graph computing. A prime application is the low-latency analysis of dark-matter signatures involving metastable charged particles that manifest as disappearing tracks.

47 OTHER INSTRUMENTATION↗