The CALICE collaboration pioneered the new trend in calorimetry—highly granular devices for high energy and particle physics applications. During the last fifteen years, several highly granular ...electromagnetic and hadron calorimeters based on different technologies were constructed and successfully tested. The technologies comprise optical readout, signal collection with semi-conducting devices and gaseous detectors. All current CALICE prototypes address technological aspects such as embedded electronics. Dedicated tools are developed for the analysis of test beam data collected with the standalone and combined setups of both physics and technological prototypes of highly granular calorimeters. The tools are described, which help to improve the precision of hadronic shower analysis including the implementation of a calorimeter-based particle identification.
Abstract
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 scintillator-steel
hadron calorimeter to negative pions with momenta from 10 to 80 GeV
simulated with two physics lists from the Geant4 package
version 10.3. Several global observables, which characterise
different aspects of hadronic shower development, are used as inputs
for a deep neural network. The network regression model is trained
using a supervised learning and exploiting true information from the
simulations. The trained model is applied to predict a number of
neutrons and energy of neutral pions produced within a hadronic
shower. The achieved performance and possible application of the
model to validation of simulations are discussed.
The intrinsically large variation of the energy deposited in a calorimeter by hadrons imposes limitations on the improvement of hadron energy resolution. The fluctuation of electromagnetic fraction ...within a hadronic shower is known to be one of the main sources of such variations. Several techniques were developed to improve the energy resolution for hadrons including the hardware compensation, dual-readout calorimetry and software compensation approaches. The reliable prediction of the amount of electromagnetic fraction on an event-by-event basis opens a possibility to correct the energy during the offline reconstruction and improve the energy resolution. In this study, the samples were investigated of hadronic showers simulated with physics lists from Geant4 package version 10.3 in the model of a highly granular hadron calorimeter for the initial hadron energies 10–80 GeV. The deep neural network was trained using a supervised learning and calorimetric observables as inputs to predict the electromagnetic fraction in a shower. The achieved neural network performance and observed improvement in hadron energy resolution of more than 15
are presented and discussed.
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In the detectors currently being developed for experiments on the next-generation lepton colliders, highly granular calorimeters are to be used. In particular, the hadron calorimeter is planned to ...be assembled from scintillation cells with direct readout of light by silicon photomultipliers. According to the results of experimental measurements of the light collection in a cell developed for the CALICE prototype hadron calorimeter, when detecting minimum ionizing particles, an estimate of the detector effects was obtained. The detector effect on the resolution of the ILD hadron calorimeter was studied by modeling the response of the detector to single neutral kaons. It was shown that the contribution of experimentally measured detector effects to the resolution for single particles is on the order of 0.5–1% in the range of hadron energy of 5–60 GeV.
The direct coupling of silicon photomultiplier to the scintillator tile is considered to be the main option for active elements of the highly granular hadron calorimeter developed for future linear ...collider experiments. In this study, the response of the scintillator-SiPM system to minimum ionising particles was simulated using the optical photon transport functionality available in the Geant4 package. The uniformity of response for both flat tile and tile with dimple was estimated from the simulations and compared to the experimental results obtained in the previous studies.
Various calibration techniques for the CMS Hadron calorimeter in Run 2 and the results of calibration using 2016 collision data are presented. The radiation damage corrections, intercalibration of ...different channels using the phi-symmetry technique for barrel, endcap and forward calorimeter regions are described, as well as the intercalibration with muons of the outer hadron calorimeter. The achieved intercalibration precision is within 3%. The in situ energy scale calibration is performed in the barrel and endcap regions using isolated charged hadrons and in the forward calorimeter using the Zarrowee process. The impact of pileup and the developed technique of correction for pileup is also discussed. The achieved uncertainty of the response to hadrons is 3.4% in the barrel and 2.6% in the endcap region (at the pseudorapidity range |η|<2) and is dominated by the systematic uncertainty due to pileup contributions.
To accomplish the physical program of studies at the planned Super Charm-Tau Factory electron-positron collider, a high-precision particle identification system is required. A FARICH–ring-imaging ...Cherenkov detector based on focusing aerogel and an array of silicon photomultipliers is proposed. The paper describes a reconstruction algorithm developed for such a detector. The algorithm was tested on simulated pion events with different photodetector noise levels. For dark count rates up to 10
5
Hz/mm
2
, the factor
uncertainty is shown to be less than 5 × 10
–4
(1 × 10
–3
) for pions with momenta of 0.6–1.5 GeV/c and incident angles of 0°–10° (0°–45°) with respect to the normal to the detector plane.
Abstract A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information ...from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied.
A modern trend in calorimetry is an increase in calorimeter granularity. A high-granularity hadron calorimeter assembled from scintillator tiles with signal readout by silicon photomultipliers is ...developed and tested by the CALICE collaboration. The uniformity of the tile response to minimum ionizing particles is studied, and these experimental measurements are compared with simulation based on the Geant4 package.
The highly granular analogue hadron calorimeter was developed and constructed by the CALICE collaboration. The active layers of the calorimeter are assembled from scintillator tiles with individual ...readout by silicon photomultipliers and are interleaved with absorber plates. The response and resolution of the calorimeter equipped with steel absorber was intensively tested in single particle beams. The application of software compensation techniques developed for the scintillator-steel prototype allows for reduction of the stochastic term of the single particle resolution from 58%/ √E/GeV to 45%/ √E/GeV. The detailed study and decomposition of the longitudinal and radial profiles of hadron-induced showers in the energy range from 10 to 80 GeV are presented and compared to GEANT4 simulations.
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