Related papers: Hadron Identification Prospects With Granular Calo…
We investigate whether state-of-the-art classification features commonly used to distinguish electrons from jet backgrounds in collider experiments are overlooking valuable information. A deep convolutional neural network analysis of…
Pions constitute nearly $70\%$ of final state particles in ultra high energy collisions. They act as a probe to understand the statistical properties of Quantum Chromodynamics (QCD) matter i.e. Quark Gluon Plasma (QGP) created in such…
In the context of a gas-sampling Digital Hadronic Calorimeter (DHCAL), we explore the potential of using Graph Neural Networks (GNN) for hadron energy reconstruction and Particle Identification (PID) in future collider experiments. For PID,…
An improved weighting algorithm applied to hadron showers has been developed for a fine grained LAr calorimeter. The new method uses tabulated weights which depend on the density of energy deposited in individual cells and in a surrounding…
Calorimeters with a high granularity are a fundamental requirement of the Particle Flow paradigm. This paper focuses on the prototype of a hadron calorimeter with analog readout, consisting of thirty-eight scintillator layers alternating…
Motivated by the computational limitations of simulating interactions of particles in highly-granular detectors, there exists a concerted effort to build fast and exact machine-learning-based shower simulators. This work reports progress on…
The energy resolution of a highly granular 1 m3 analogue scintillator-steel hadronic calorimeter is studied using charged pions with energies from 10 GeV to 80 GeV at the CERN SPS. The energy resolution for single hadrons is determined to…
We present a first proof of concept to directly use neural network based pattern recognition to trigger on distinct calorimeter signatures from displaced particles, such as those that arise from the decays of exotic long-lived particles.…
Accurate simulation of physical processes is crucial for the success of modern particle physics. However, simulating the development and interaction of particle showers with calorimeter detectors is a time consuming process and drives the…
In the context of developing a hadron calorimeter with extremely fine granularity for the application of Particle Flow Algorithms to the measurement of jet energies at a future lepton collider, we report on extensive tests of a small scale…
The paper describes a novel neural-network-based approach to study the distributions of secondaries produced in hadronic showers using observables provided by highly granular calorimeters. The response is analysed of the highly granular…
To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to separate energy deposits from charged and neutral particles.…
One of the key design choices of any sampling calorimeter is how fine to make the longitudinal and transverse segmentation. To inform this choice, we study the impact of calorimeter segmentation on energy reconstruction. To ensure that the…
The design of detector concepts has been driven for a long time by requirements on transverse momentum, impact parameter and jet energy resolutions, as well as hermeticity. Only rather recently it has been realised that the ability to…
The design of detector concepts has been driven for a long time by requirements on transverse momentum, impact parameter and jet energy resolutions, as well as hermeticity. Only rather recently it has been realised that the ability to…
The performance demands of future particle-physics experiments investigating the high-energy frontier pose a number of new challenges, forcing us to find improved solutions for the detection, identification, and measurement of final-state…
We investigate the effect of longitudinal and transverse calorimeter segmentation on event-by-event software compensation for hadronic showers. To factorize out sampling and electronics effects, events are simulated in which a single…
We investigate photon--pion discrimination in regimes where electromagnetic showers overlap at the scale of calorimeter granularity. Using full detector simulations with fine-grained calorimeter segmentation of approximately…
The CALICE collaboration has constructed highly granular electromagnetic and hadronic calorimeter prototypes to evaluate technologies for the use in detector systems at a future Linear Collider. The hadron calorimeter uses small…
Hadron therapy is a novel treatment against cancer. The main advantage of this therapy causes less side effect in comparison to X-ray irradiation methods. Hadron therapy is just ahead of a significant breakthrough since this technique can…