arXiv subjects

O. Bach

Publications and source records attributed to O. Bach.

11 recordsLinked to original sources

arXiv2026

An investigation of fast simulation techniques for pion showers using kernel density estimators with the CALICE AHCAL Technological Prototype

In this article, the development and investigation of fast hadron shower simulation methods is presented. A test beam dataset has been recorded in 2018 at CERN with the AHCAL Technological Prototype of the CALICE Collaboration, where the calorimeter prototype was exposed to electron, muon, and negatively charged pion beams of various initial energies. The pion shower dataset, covering energies between 10 GeV and 200 GeV, has been used to develop a data-driven fast simulation algorithm of the AHCAL response to pion showers. The resulting shower model demonstrates excellent agreement with measured shower observables. In addition, a method for simulating pion showers at arbitrary energies is introduced, based upon interpolation between simulated showers at neighbouring beam energies.

physics.ins-det↗

arXiv2025

The ILD Detector: A Versatile Detector for an Electron-Positron Collider at Energies up to 1 TeV

The International Large Detector, ILD, is a detector concept for an experiment at a future high energy lepton collider. The detector has been optimised for precision physics in a range of energies from 90~GeV to about 1~TeV. ILD features a high precision, large volume combined silicon and gaseous tracking system, together with a high granularity calorimeter, all inside a central solenoidal magnetic field. The paradigm of particle flow has been the guiding principle of the design of ILD. ILD is based mostly on technologies which have been demonstrated by extensive research and test programs. The ILD concept is proposed both for linear and circular lepton collider, be it at CERN or elsewhere. The concept has been developed by a group of nearly 60 institutes from around the world, and offers a well developed and powerful environment for science and technology studies at lepton colliders. In this document, the required performance of the detector, the proposed implementation and the readiness of the different technologies needed for the implementation are discussed.

hep-ex↗

arXiv2024

Shower Separation in Five Dimensions for Highly Granular Calorimeters using Machine Learning

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. Three published neural network-based shower separation models were applied to simulation and experimental data to measure the performance of the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL) technological prototype in distinguishing the energy deposited by a single charged and single neutral hadron for Particle Flow. The performance of models trained using only standard spatial and energy and charged track position information from an event was compared to models trained using timing information available from AHCAL, which is expected to improve sensitivity to shower development and, therefore, aid in clustering. Both simulation and experimental data were used to train and test the models and their performances were compared. The best-performing neural network achieved significantly superior event reconstruction when timing information was utilised in training for the case where the charged hadron had more energy than the neutral one, motivating temporally sensitive calorimeters. All models under test were observed to tend to allocate energy deposited by the more energetic of the two showers to the less energetic one. Similar shower reconstruction performance was observed for a model trained on simulation and applied to data and a model trained and applied to data.

physics.ins-det↗

arXiv2024

Software Compensation for Highly Granular Calorimeters using Machine Learning

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.

physics.ins-det↗

arXiv2023

Performance of the CMS High Granularity Calorimeter prototype to charged pion beams of 20$-$300 GeV/c

The upgrade of the CMS experiment for the high luminosity operation of the LHC comprises the replacement of the current endcap calorimeter by a high granularity sampling calorimeter (HGCAL). The electromagnetic section of the HGCAL is based on silicon sensors interspersed between lead and copper (or copper tungsten) absorbers. The hadronic section uses layers of stainless steel as an absorbing medium and silicon sensors as an active medium in the regions of high radiation exposure, and scintillator tiles directly readout by silicon photomultipliers in the remaining regions. As part of the development of the detector and its readout electronic components, a section of a silicon-based HGCAL prototype detector along with a section of the CALICE AHCAL prototype was exposed to muons, electrons and charged pions in beam test experiments at the H2 beamline at the CERN SPS in October 2018. The AHCAL uses the same technology as foreseen for the HGCAL but with much finer longitudinal segmentation. The performance of the calorimeters in terms of energy response and resolution, longitudinal and transverse shower profiles is studied using negatively charged pions, and is compared to GEANT4 predictions. This is the first report summarizing results of hadronic showers measured by the HGCAL prototype using beam test data.

physics.ins-det↗

arXiv2022

Response of a CMS HGCAL silicon-pad electromagnetic calorimeter prototype to 20-300 GeV positrons

The Compact Muon Solenoid Collaboration is designing a new high-granularity endcap calorimeter, HGCAL, to be installed later this decade. As part of this development work, a prototype system was built, with an electromagnetic section consisting of 14 double-sided structures, providing 28 sampling layers. Each sampling layer has an hexagonal module, where a multipad large-area silicon sensor is glued between an electronics circuit board and a metal baseplate. The sensor pads of approximately 1 cm$^2$ are wire-bonded to the circuit board and are readout by custom integrated circuits. The prototype was extensively tested with beams at CERN's Super Proton Synchrotron in 2018. Based on the data collected with beams of positrons, with energies ranging from 20 to 300 GeV, measurements of the energy resolution and linearity, the position and angular resolutions, and the shower shapes are presented and compared to a detailed Geant4 simulation.

physics.ins-det↗

arXiv2020

Construction and commissioning of CMS CE prototype silicon modules

As part of its HL-LHC upgrade program, the CMS Collaboration is developing a High Granularity Calorimeter (CE) to replace the existing endcap calorimeters. The CE is a sampling calorimeter with unprecedented transverse and longitudinal readout for both electromagnetic (CE-E) and hadronic (CE-H) compartments. The calorimeter will be built with $\sim$30,000 hexagonal silicon modules. Prototype modules have been constructed with 6-inch hexagonal silicon sensors with cell areas of 1.1~$cm^2$, and the SKIROC2-CMS readout ASIC. Beam tests of different sampling configurations were conducted with the prototype modules at DESY and CERN in 2017 and 2018. This paper describes the construction and commissioning of the CE calorimeter prototype, the silicon modules used in the construction, their basic performance, and the methods used for their calibration.

physics.ins-det↗

arXiv2020

The DAQ system of the 12,000 Channel CMS High Granularity Calorimeter Prototype

The CMS experiment at the CERN LHC will be upgraded to accommodate the 5-fold increase in the instantaneous luminosity expected at the High-Luminosity LHC (HL-LHC). Concomitant with this increase will be an increase in the number of interactions in each bunch crossing and a significant increase in the total ionising dose and fluence. One part of this upgrade is the replacement of the current endcap calorimeters with a high granularity sampling calorimeter equipped with silicon sensors, designed to manage the high collision rates. As part of the development of this calorimeter, a series of beam tests have been conducted with different sampling configurations using prototype segmented silicon detectors. In the most recent of these tests, conducted in late 2018 at the CERN SPS, the performance of a prototype calorimeter equipped with ${\approx}12,000\rm{~channels}$ of silicon sensors was studied with beams of high-energy electrons, pions and muons. This paper describes the custom-built scalable data acquisition system that was built with readily available FPGA mezzanines and low-cost Raspberry PI computers.

physics.ins-det↗

arXiv2019

Characterisation of different stages of hadronic showers using the CALICE Si-W ECAL physics prototype

A detailed investigation of hadronic interactions is performed using $π^-$-mesons with energies in the range 2--10 GeV incident on a high granularity silicon-tungsten electromagnetic calorimeter. The data were recorded at FNAL in 2008. The region in which the $π^-$-mesons interact with the detector material and the produced secondary particles are characterised using a novel track-finding algorithm that reconstructs tracks within hadronic showers in a calorimeter in the absence of a magnetic field. The principle of carrying out detector monitoring and calibration using secondary tracks is also demonstrated.

physics.ins-det↗

arXiv2019

Analysis of Testbeam Data of the Highly Granular RPC-Steel CALICE Digital Hadron Calorimeter and Validation of Geant4 Monte Carlo Models

We present a study of the response of the highly granular Digital Hadronic Calorimeter with steel absorbers, the Fe-DHCAL, to positrons, muons, and pions with momenta ranging from 2 to 60 GeV/c. Developed in the context of the CALICE collaboration, this hadron calorimeter utilises Resistive Plate Chambers as active media, interspersed with steel absorber plates. With a transverse granularity of $1\,\times\,1\,$cm$^{2}$ and a longitudinal segmentation of 38 layers, the calorimeter counted 350,208 readout channels, each read out with single-bit resolution (digital readout). The data were recorded in the Fermilab test beam in 2010-11. The analysis includes measurements of the calorimeter response and the energy resolution to positrons and muons, as well as detailed studies of various shower shape quantities. The results are compared to simulations based on Geant4, which utilise different electromagnetic and hadronic physics lists.

physics.ins-det↗

arXiv2018

Hadronic Energy Resolution of a Combined High Granularity Scintillator Calorimeter System

This paper presents results obtained with the combined CALICE Scintillator Electromagnetic Calorimeter, Analogue Hadronic Calorimeter and Tail Catcher & Muon Tracker, three high granularity scintillator-SiPM calorimeter prototypes. The response of the system to pions with momenta between 4 GeV/c and 32 GeV/c is analysed, including the energy response, resolution, and longitudinal shower profiles. The results of a software compensation technique based on weighting according to hit energy are compared to those of a standard linear energy reconstruction. The results are compared to predictions of the GEANT4 physics lists QGSP_BERT_HP and FTFP_BERT_HP.

physics.ins-det↗