Hadron Calorimeter Research Articles

Simulation of the spatial shift in detector response for polarized protons within a calorimeter

Measurement of the helicity dependent elastic electron–proton scattering cross section provides a key means of investigating parity violation within the proton. However, such measurements exhibit potential instrumental effects associated with the detection of polarized recoiled protons. In particular, spin–orbit interactions within a massive detector induce a systematic spatial shift in the detector signal. In this study, we determine the size of this shift using the Geant4 simulation toolkit. For a typical hadron calorimeter, we found a polarization dependent shift on the order of 0.01–0.1 mm, multiple orders of magnitude smaller than the typical spatial resolution seen in hadronic calorimeters. Additionally, we provide the custom modifications required of the Geant4 source code to implement the quasi-elastic scattering of polarized protons incident on nuclei in the detector. The modifications are readily extendable to generic matter sources, and can be used for the study of additional spin dependent observables in Geant4.

Measurement of the energy response of the ATLAS\xa0calorimeter to charged\xa0pions from W^{pm }rightarrow tau ^{pm }(rightarrow pi ^{pm }nu _{tau })nu _{tau } events in Run\xa02 data

The energy response of the ATLAS calorimeter is measured for single charged pions with transverse momentum in the range 10<p_text {T}<300 GeV. The measurement is performed using 139 text {fb}^{-1} of LHC proton–proton collision data at sqrt{s}=13 TeV taken in Run 2 by the ATLAS detector. Charged pions originating from tau -lepton decays are used to provide a sample of high-p_{text {T}} isolated particles, where the composition is known, to test an energy regime that has not previously been probed by in situ single-particle measurements. The calorimeter response to single-pions is observed to be overestimated by {sim }2% across a large part of the p_{text {T}} spectrum in the central region and underestimated by {sim }4% in the endcaps in the ATLAS simulation. The uncertainties in the measurements are {lesssim }1% for 15<p_text {T}<185 GeV in the central region. To investigate the source of the discrepancies, the width of the distribution of the ratio of calorimeter energy to track momentum, the energies per layer and response in the hadronic calorimeter are also compared between data and simulation.

The CMS Magnetic Field Measuring and Monitoring Systems

This review article describes the performance of the magnetic field measuring and monitoring systems for the Compact Muon Solenoid (CMS) detector. To cross-check the magnetic flux distribution obtained with the CMS magnet model, four systems for measuring the magnetic flux density in the detector volume were used. The magnetic induction inside the 6 m diameter superconducting solenoid was measured and is currently monitored by four nuclear magnetic resonance (NMR) probes installed using special tubes at a radius of 2.9148 m outside the barrel hadron calorimeter at ±0.006 m from the coil median XY-plane. Two more NRM probes were installed at the faces of the tracking system at Z-coordinates of −2.835 and +2.831 m and a radius of 0.651 m from the solenoid axis. The field inside the superconducting solenoid was precisely measured in 2006 in a cylindrical volume of 3.448 m in diameter and 7 m in length using ten three-dimensional (3D) B-sensors based on the Hall effect (Hall probes). These B-sensors were installed on each of the two propeller arms of an automated field-mapping machine. In addition to these measurement systems, a system for monitoring the magnetic field during the CMS detector operation has been developed. Inside the solenoid in the horizontal plane, four 3D B-sensors were installed at the faces of the tracking detector at distances X = ±0.959 m and Z-coordinates of −2.899 and +2.895 m. Twelve 3D B-sensors were installed on the surfaces of the flux-return yoke nose disks. Seventy 3D B-sensors were installed in the air gaps of the CMS magnet yoke in 11 XY-planes of the azimuthal sector at 270°. A specially developed flux loop technique was used for the most complex measurements of the magnetic flux density inside the steel blocks of the CMS magnet yoke. The flux loops are installed in 22 sections of the flux-return yoke blocks in grooves of 30 mm wide and 12–13 mm deep and consist of 7–10 turns of 45 wire flat ribbon cable. The areas enclosed by these coils varied from 0.3 to 1.59 m2 in the blocks of the barrel wheels and from 0.5 to 1.12 m2 in the blocks of the yoke endcap disks. The development of these systems and the results of the magnetic flux density measurements across the CMS magnet are presented and discussed in this review article.

Energy reconstruction in a liquid argon calorimeter cell using convolutional neural networks

The liquid argon ionization current in a sampling calorimeter cell can be analyzed to determine the energy of detected particles. In practice, experimental artifacts such as pileup and electronic noise make the inference of energy from current a difficult process. The beam intensity of the Large Hadron Collider will be significantly increased during the Phase-II long shut-down of 2025–2027. Signal processing techniques that are used to extract the energy of detected particles in the ATLAS detector will suffer a significant loss in performance under these conditions. This paper compares the presently used optimal filter technique to convolutional neural networks for energy reconstruction in the ATLAS liquid argon hadronic end cap calorimeter. In particular, it is shown that convolutional neural networks trained with an appropriately tuned and novel loss function are able to outperform the optimal filter technique.

Upgrade of the ATLAS Tile Calorimeter high voltage system

The high voltage system of TileCal, the ATLAS central hadron calorimeter, is being upgraded for the high-luminosity LHC, in the so called phase II upgrade. In the new configuration for the upgrade, the high voltage regulation boards are not located inside the detector anymore, they are deployed far from the radiation caused by the collisions, in a room where there is permanent access for maintenance. This option requires a large number of 100 m long high voltage cables but removes the requirement of radiation hardened boards. HVremote regulation boards and the respective high voltage supplies boards have been developed and tested, as well as a crate to house the boards. Preliminary results of the HVremote boards performance are presented.

Operational Experience and Evolution of the ATLAS Tile Hadronic Calorimeter Read-Out Drivers

TileCal is the central hadronic calorimeter of the ATLAS experiment at the Large Hadron Collider (LHC). It is a sampling detector where scintillating tiles are embedded in steel absorber plates. The tiles are grouped forming cells, which are read-out on both sides by photomultiplier tubes (PMTs). The PMT digital samples are transmitted to the Read-Out Drivers (ROD) located in the back-end system for the events accepted by the Level 1 trigger system. The ROD is the core element of the back-end electronics and it represents the interface between the front-end electronics and the ATLAS overall Data AcQuisition (DAQ) system. It is responsible for energy and time reconstruction, trigger and data synchronization, busy handling, data integrity checking and lossless data compression. The TileCal ROD is a standard 9U VME board equipped with DSP based Processing Units mezzanine cards. A total of 32 ROD modules are required to read-out the entire TileCal detector. Each ROD module has to process the data from up to 360 PMTs in real time in less than 10 microseconds. The commissioning of the RODs was completed in 2008 before the first LHC collisions. Since then, several hardware and firmware updates have been implemented to accommodate the RODs to the evolving ATLAS Trigger and DAQ conditions adjusted to follow the LHC parameters. The initial ROD system, the different updates implemented and the operational experience during the LHC Run 1 and Run 2 are presented.

Measurements of Spectators with Forward Hadron Calorimeter in MPD/NICA Experiment

Measurements of Spectators with Forward Hadron Calorimeter in MPD/NICA Experiment

Learning to identify electrons

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 electromagnetic and hadronic calorimeter deposits is compared to the performance of typical features, revealing a $\approx 5\%$ gap which indicates that these lower-level data do contain untapped classification power. To reveal the nature of this unused information, we use a recently developed technique to map the deep network into a space of physically interpretable observables. We identify two simple calorimeter observables which are not typically used for electron identification, but which mimic the decisions of the convolutional network and nearly close the performance gap.

A novel high dynamic-range SiPM for scintillator-based hadronic calorimetry

The Analog Hadronic Calorimeter (AHCAL) is one option of highly granular calorimeters optimised with the Particle Flow Algorithm (PFA) and considered for experiments at future lepton colliders. It consists of dense steel plates as absorber interleaved with plastic scintillator tiles, individually read out by Silicon Photomultipliers (SiPMs). A novel SiPM developed by the Novel Device Laboratory (NDL) with an active area of 1 mm2 and a pixel pitch of 12.5 micron[NDL-SiPM-12.5] has been mainly investigated. The characterisation studies include single photon calibration, dynamic range and performance of crosstalk as well as Minimum Ionising Particle (MIP) detection efficiency of a detector unit. Combined tests with a dedicated ASIC (SPIROC2E) for multi-channel SiPMs show that single photon spectra can be obtained, given the relatively small SiPM gain (∼2 × 105). The linearity of the SiPMs in response to incident photons of less than 10,000 (500 MIPs) is within 5% from measurements. Meanwhile, the dark count rate (DCR) is around 2×10-3 Hz at a threshold 0.5 MIP (10 p.e.) and the MIP detection efficiency of a detector unit can be near 95% from the MIP spectrum. These studies indicate the NDL-SiPM-12.5 can be a photosensor candidate for the future scintillator-based hadronic calorimeters.

Application of FHCal for Heavy-Ion Collision Centrality Determination in MPD/NICA Experiment

Two approaches related to the centrality determination in heavy-ion Multi-Purpose Detector (MPD) experiments, using charge-particles multiplicity in Time Projection Chamber (TPC) and the energy deposition in Forward Hadron Calorimeter (FHCal) are discussed. The main features of the FHCal are the fine transverse segmentation and the beam holes in the center of the calorimeters. Leaking the heavy non-interacting fragments (spectators) leads to ambiguity in the dependence of energy deposition in the FHCal on the collision centrality. However, the calorimeter transverse segmentation allows one to measure the energy distributions in each of the FHCal modules and to construct combined observables to resolve the problems associated with the beam hole. The comparison of these approaches in the collision centrality measurements is discussed.

Upgrade of the ATLAS Hadronic Tile Calorimeter for the High Luminosity LHC

The Tile Calorimeter (TileCal) is the hadronic calorimeter covering the central region of the ATLAS experiment. It is a scintillating plastic tiles and steel absorbers sampling calorimeter. The scintillators are read-out by wavelength shifting fibers coupled to photomultiplier tubes (PMTs). The TileCal response and its readout electronics are monitored to better than 1 $$\%$$ using radioactive source, laser and charge injection systems. The TileCal electronics will undergo major upgrades for the high luminosity phase of the LHC (HL-LHC), so that the system can cope with increased radiation and can meet the requirements of a 1-MHz trigger. Digitized signals from all PMTs are sent to the back-end electronics and to the first level of trigger at 40 MHz. This will provide better precision in the trigger system and will allow the development of more complex trigger algorithms. The TileCal upgrade program has included extensive R&D and test beam studies. A Demonstrator module was inserted in ATLAS in 2019 for testing in actual detector conditions. The main features of the TileCal upgrade program and results obtained from the Demonstrator tests are discussed.

Plastic Scintillators and WLS Optical Fibers in Particle Physics - Characterization of Scintillators for the Future Circular Collider as a Function of Their Dimensions and Aging of WLS Optical Fibers

The calorimeters which will operate in experiments at the hadronic Future Circular Collider—FCC-hh—will be one of the key pieces for the complete exploration of collisions between hadrons. This is because the increasing of energy in proton collisions will require detectors that can work in environments under severe radiation, with high-energy rates, presenting a high resolution and low granularity. In this context, the choice of the hadronic calorimeter of the FCC-hh, the Hadronic Barrel (HB) and the extended barrel (HEB), will be inspired by the ATLAS Tile Calorimeter (TileCal). The HB will have 10 layers, with scintillating tiles that will be separated through a reflective material (e.g., Tyvek) and read by wavelength shifting fibers (WLS) of 1 mm in diameter connected to silicon photomultipliers (SiPMs). Our study focuses on the comparison of the luminous signal intensity in the tile in the first layer of the HB and the tile in the last layer of HB, taking into account the dimensions of the tile. A study on the optimization of the signal uniformity was made, by adding a light-absorbing black strip to the tile, and results were compared with similar experiments performed at CERN. The procedure was performed in the Tilemeter, in the Laboratory of Optics and Scintillating Materials (LOMaC) of the Laboratory of Instrumentation and Experimental Particle Physics, in Lisboa.

Exploitation of HPC Resources for data intensive sciences

The Large Hadron Collider (LHC) will enter a new phase beginning in 2027 with the upgrade to the High Luminosity LHC (HL-LHC). The increase in the number of simultaneous collisions coupled with a more complex structure of a single event will result in each LHC experiment collecting, storing, and processing exabytes of data per year. The amount of generated and/or collected data greatly outweighs the expected available computing resources. In this paper, we discuss effcient usage of HPC resources as a prerequisite for data-intensive science at exascale. First, we discuss the experience of porting CMS Hadron and Electromagnetic calorimeters reconstruction code to utilize Nvidia GPUs within the DEEP-EST project; second, we look at the tools and their adoption in order to perform benchmarking of a variety of resources available at HPC centers. Finally, we touch on one of the most important aspects of the future of HEP - how to handle the flow of petabytes of data to and from computing facilities, be it clouds or HPCs, for exascale data processing in a flexible, scalable and performant manner. These investigations are a key contribution to technical work within the HPC collaboration among CERN, SKA, GEANT and PRACE.

The ATLAS Tile Calorimeter Tools for Data Quality Assessment

The ATLAS Tile Calorimeter (TileCal) is the central part of the hadronic calorimeter of the ATLAS experiment and provides important information for reconstruction of hadrons, jets, hadronic decays of tau leptons and missing transverse energy. The readout is segmented into nearly 10000 channels that are calibrated by means of Cesium source, laser, charge injection, and integratorbased systems. The data quality (DQ) relies on extensive monitoring of both collision and calibration data. Automated checks are performed on a set of pre-defined histograms and results are summarized in dedicated web pages. A set of tools is then used by the operators for further inspection of the acquired data with the goal of spotting the origins of problems or other irregularities. Consequently, the TileCal conditions data (calibration constants, channel statuses etc) are updated in databases that are used for the data-reprocessing, or serve as an important input for the maintenance works during the shutdown periods. This talk reviews the software tools used for the DQ monitoring with emphasis on recent developments aiming to integrate all tools into a single platform.

The Data Acquisition System for the ATLAS Phase-II Tile Calorimeter Demonstrator

The Tile Calorimeter (TileCal) is the central hadronic calorimeter of the ATLAS experiment at Large Hadron Collider (LHC). The TileCal readout system consists of about 10,000 channels. In 2025, the LHC will be upgraded leading into the High Luminosity LHC (HL-LHC). The HL-LHC will be capable to deliver an instantaneous luminosity up to seven times compared to the LHC nominal luminosity. The TileCal Phase-II upgrade will replace the majority of the on-detector and off-detector electronics using a new readout schema for the HL-LHC era. The on-detector electronics will digitize and transmit calorimeter signals to the off-detector electronics at the bunch crossing frequency. In the counting rooms, the off-detector electronics will store the digitized samples in pipelined buffers and compute reconstructed trigger objects for the first level of trigger. The TileCal Phase-II upgrade project has undertaken an extensive R&amp;D program which includes the development of a Demonstrator module to evaluate the performance of the new clock and readout architecture for the HL-LHC. A Demonstrator module containing the upgrade on-detector readout electronics was built, tested during several test beam campaigns, and inserted into the ATLAS experiment. The Demonstrator module is operated and read out using a Tile PreProcessor (TilePPr) Demonstrator which enables backward compatibility with the present ATLAS Trigger and Data AcQuisition and the Timing, Trigger and Command systems. This contribution describes the components of the clock distribution and data acquisition system for the Demonstrator module, and its implementation in the ATLAS experiment.

Approaches in centrality measurements of heavy-ion collisions with forward calorimeters at MPD/NICA facility

The MPD/NICA heavy-ion experiment is now under construction at JINR, Dubna, Russia. The centrality is the global characteristic of the nuclear interactions and reflects the degree of the nuclei overlapping or the number of interacting nucleons. One of the methods to measure the centrality is the determination of the number of non-interacting projectile fragments (spectators) which will be detected by the hadron calorimeters (FHCal) placed at the opposite sides of the beam interaction point. Since the bound spectators escape in beam holes, the central and peripheral collisions have the same spectator’s energy deposition in FHCal. It leads to the ambiguity in the determination of the collision centrality. To resolve this ambiguity a few approaches are developed based on the Monte-Carlo simulations with a few fragmentation models. The methods are based on the combination of both the spatial and the energy distributions of the spectators in the FHCal modules. A few observables for the centrality determination are constructed. Calculation of the transverse/longitudinal energies and the two-dimensional fit of the energy distributions in the FHcal modules make possible the separation of the central and peripheral events. The accuracy of the centrality measurements for a few fragmentation models is estimated.

Determining the Centrality of a Nuclear Collision Using a Hadron Calorimeter

The determination of the centrality of nuclear collision or the value of the impact parameter of heavy nuclei is of great importance for the analysis of all experimental data and comparison with theory. One method is to measure the number of spectators using a hadron calorimeter located at a small angle to the nuclear beam. It is shown that with an achievable resolution of the hadron calorimeter in energy, the accuracy of determining the impact parameter is insufficient for using the calorimeter in the MPD / NICA and CBM / FAIR projects. The error reaches 35 % at a beam energy of 2.5 GeV even for peripheral collisions. Secondary processes during the passage of spectators through the nucleus give an additional contribution to the error for central collisions and at medium centralities.

Application of Machine Learning methods for centrality determination in heavy ion reactions at the BM@N and MPD@NICA

Forward hadron calorimeters in heavy ion experiments are used to determine the centrality and orientation of reaction plane in nucleus-nucleus collisions. In BM@N and MPD@NICA experiments hadron calorimeters with a beam hole in the center will be used, which is motivated by high radiation doses at the BM@N and by the design of the MPD collider experiment. This feature makes it impossible to determine centrality from only the total energy deposition in the calorimeters. Therefore, an approach using machine learning methods was developed to solve the centrality problem. This approach uses information on the energy distribution of particles over the calorimeter surface. The report is dedicated to the description of the new approach for centrality determination. The results of applying the approach to the simulation data of the BM@N and MPD@NICA experiments will be shown.

Development of readout chain for CBM Projectile Spectator Detector at FAIR

The Compressed Baryonic Matter (CBM) experiment at FAIR needs a detector to measure the nucleus-nucleus collision centrality and orientation of the reaction plane. The Projectile Spectator Detector (PSD) as a sampling lead/scintillator forward hadron calorimeter with transverse and longitudinal segmentation will be used for this purpose. The PSD consist of 44 modules with 10 longitudinal sections in each. Electronics of PSD consist of MPPCs boards mounted directly on detector and readout ADC interface with ADC FPGA board installed into crate distanced on 50m from detector part. ADC has 14-bit resolution and 125MHz digitization rate, Kintex-7 FPGA is placed on the board. Concept of PSD Front End Electronics (FEE) is already designed and most crucial parts including ADC FPGA board already tested and confirmed to be operational. One PSD module (”mini PSD” or mPSD) has been installed into the “mini CBM” (mCBM) assembled at SIS18 accelerator in GSI, Darmstadt, Germany in the framework of the FAIR Phase-0 program. ADC FPGA readout board has been integrated into common DAQ experiment and tested. Details of the mPSD FEE design and test results are shown.

Radiation hardness of the ATLAS Tile Calorimeter optical components

The Tile Calorimeter (TileCal) is a sampling hadronic calorimeter and an essential part of the ATLAS experiment at the LHC. Plastic scintillating tiles are the active material. The light produced in the scintillators is transmitted to the photomultiplier tubes by wavelength shifting fibres. During the High Luminosity LHC (HL-LHC) programme, the luminosity can reach a value several times higher than the one that TileCal was designed for. Two critical points that affect the detector performance are the increased exposure to radiation that does degrade the TileCal optics and natural ageing. Since the optical components of the TileCal cannot be replaced, the radiation hardness must be evaluated. The Laser and Cesium calibration systems are used to evaluate the robustness of the TileCal optical components. These systems combined allow to isolate the response of the tiles and fibres and evaluate the evolution of the light yield with the dose. Run 2 calibration data were analysed, indicating that cells in layer A, and B11 and C10 cells have lost about 5% of light yield. No significant changes were found for the other cells. This study constitutes an essential step for predicting the calorimeter performance in future HL-LHC runs. Nevertheless, the extrapolation uncertainty is large so more data needs to be explored to reach better precision on such extrapolation.