Granular Calorimeter Research Articles

The CMS High Granularity Calorimeter for HL-LHC

Calorimetry in high-energy physics is rapidly evolving, with new challenges and a wide variety of technologies being employed, both for signal creation and detection. Advances in large-area highly-segmented detectors are providing possibilities for high-granularity calorimetry. The CMS HGCAL, being designed to replace the existing CMS endcap calorimeters for the HL-LHC era, is one example. It is a sampling calorimeter, featuring unprecedented transverse and longitudinal readout segmentation for both electromagnetic (CE-E) and hadronic (CE-H) compartments. This will facilitate particle-flow calorimetry, where the fine structure of showers can be measured and used to enhance pileup rejection and particle identification, whilst still achieving good energy resolution. The CE-E and a large fraction of CE-H will use hexagonal silicon sensors as active detector material. The lower-radiation environment will be instrumented with scintillator tiles with on-tile SiPM readout. An overview of the HGCAL project will be presented, covering motivation, engineering design, readout and trigger concepts, and performance in simulation.

FoCal: A highly granular digital calorimeter

This contribution discusses the recent progress in the development of a highly granular digital electromagnetic calorimeter proposed as an upgrade to the ALICE detector. This forward electromagnetic calorimeter (FoCal) must be able to discriminate decay photons from direct photons at very high energy, which requires extremely high granularity and a small Molière radius. A dedicated R&D program is ongoing to develop the technology needed for such a high-granularity device. Within this program we have constructed a prototype of a digital electromagnetic calorimeter based on CMOS monolithic active pixel sensors (MAPS). This prototype has demonstrated the unique capabilities of such a highly granular digital calorimeter, providing unprecedented shower profile measurements and good linearity and energy resolution. The prototype was based on the MIMOSA chip, which is however not fast enough for application in a full detector at the LHC. As a next step, the ALPIDE chip developed for the ALICE Inner Tracker Upgrade is being investigated for performance with high occupancy. This contribution presents results from the current prototype, the performance of the ALPIDE and plans for the next prototype.

Beam-tests of prototype modules for the CMS High Granularity Calorimeter at CERN

As part of its HL-LHC upgrade program, CMS is developing a High Granularity Calorimeter (HGCAL) to replace the existing endcap calorimeters. The HGCAL will be realised as a sampling calorimeter, including 36 layers of silicon pads and 16 layers combining both silicon+scintillator detectors interspersed with metal absorber plates. Starting from 2016, prototype modules, based on 6-inch hexagonal silicon pad sensors with pad areas of 1.0 cm2, have been constructed. In 2017 and 2018, beam tests of different sampling configurations made from these modules have been conducted at CERN's SPS using beams of charged hadrons and electrons with momenta from 20 to 350 GeV/c. The setup was complemented with CALICE's AHCAL prototype, a scintillator-based sampling calorimeter, mimicking the proposed design of the HGCAL's scintillator part. Most importantly, the new Skiroc2-CMS readout ASIC has been used in the silicon modules, facilitating the study of its timing capabilities in practice. This talk summarises the test beam efforts in 2017 and 2018. Preliminary results, including gain characterisation, calibration with minimum ionising particles and energy reconstruction performance of electron induced showers are shown.

ARRAY: An open source, modular and probe-card based system with integrated switching matrix for characterisation of large area silicon pad sensors

Silicon pad sensors are proposed as active material in highly granular sampling calorimeters of future collider experiments such as the Compact Linear Collider (CLIC) or the International Linear Collider (ILC). The electromagnetic section of these designs often include O(1000 m$^2$) of silicon pad sensors. For the luminosity measurement, a dedicated forward calorimeter called LumiCal is foreseen. More recently, the CMS experiment has decided to adopt the same concept in its endcap calorimeter upgrade for the HL-LHC. The sensors are typically produced from 6- or 8-inch wafers and consist of a few hundred smaller cells, each with an area of O(0.1 to 1 $\text{cm}^2$). For the prototyping phase of these projects, several design choices have to be evaluated while for mass production, thousands of sensors have to be tested for quality control. For the electrical characterisation of these sensors, it is important to bias them under realistic conditions. To fulfil these requirements, ARRAY, a compact, modular and cost efficient system for large area silicon pad sensor characterisation has been developed and successfully commissioned. It consists of two plugin printed circuit boards: an active switching matrix with 512 input channels that holds all controls and a passive probe card that connects to the sensor. The latter can then be adapted to any sensor geometry. All design files are open source. The system has been used to measure currents ranging from 500 pA to 5 $\mu$A and capacitances between 5 pF and 100 pF. A precision of better than 0.2 pF on capacitance measurements in that range can be achieved. Examples of calibration and measurement results for leakage current and capacitance are presented.

A simulation study to distinguish prompt photon from π0 and beam halo in a granular calorimeter using deep networks

In a hadron collider environment identification of prompt photons originating in a hard partonic scattering process and rejection of non-prompt photons coming from hadronic jets or from beam related sources, is the first step for study of processes with photons in final state. Photons coming from decay of π0's produced inside a hadronic jet and photons produced in catastrophic bremsstrahlung by beam halo muons are two major sources of non-prompt photons. In this paper the potential of deep learning methods for separating the prompt photons from beam halo and π0's in the electromagnetic calorimeter of a collider detector is investigated, using an approximate description of the CMS detector. It is shown that, using only calorimetric information as images with a Convolutional Neural Network, beam halo (and π0) can be separated from photon with 99.96% (97.7%) background rejection for 99.00% (90.0%) signal efficiency which is much better than traditionally employed variables.

A highly granular calorimeter concept for long baseline near detectors

Future long baseline neutrino experiments such as the DUNE experiment under construction at Fermilab will perform precision measurements of neutrino oscillations, including the potential for the discovery of CP violation in the lepton sector. These measurements require an understanding of the unoscillated neutrino beam with unprecedented accuracy. This will be provided by complex near detectors which consist of different subsystems including tracking elements and electromagnetic calorimetry. A high granularity in the calorimeter, provided by scintillator tiles with SiPM readout as used in the CALICE analog hadron calorimeter, provides the capability for direction reconstruction of photon showers, which can be used to determine the decay positions of neutral pions. This can enable the association of neutral pions to neutrino interactions in the tracker volume, improving the event reconstruction of the near detector. Beyond photon and electron reconstruction, the calorimeter also provides sensitivity to neutrons. In this presentation, we will discuss a simulation study exploring the potential of high granularity for the electromagnetic calorimeter of the DUNE near detector. Particular emphasis will be placed on the combination with a high pressure TPC as tracking detector, which puts particularly stringent requirements on the calorimeter. The dependence of the projected detector performance on granularity, absorber material and absorber thickness as well as geometric arrangement satisfying the constraints of the TPC are explored.

Current and Future Performance of the CMS Simulation

The CMS full simulation using Geant4 has delivered billions of simulated events for analysis during Runs 1 and 2 of the LHC. However, the HL-LHC dataset will be an order of magnitude larger, with a similar increase in occupancy per event. In addition, the upgraded CMS detector will be considerably more complex, with an extended silicon tracker and a high granularity calorimeter in the endcap region. Increases in conventional computing resources are subject to both technological and budgetary limitations, so novel approaches are needed to improve software efficiency and to take advantage of new architectures and heterogeneous resources. Several projects are in development to address these needs, including the vectorized geometry library Vec-Geom and the GeantV transport engine, which uses track-level parallelization. The current computing performance of the CMS simulation will be presented as a baseline, along with an overview of the various optimizations already available for Geant4. Finally, the progress and outlook for integrating VecGeom and GeantV in the CMS software framework will be discussed.

Design and performance of the CMS High Granularity Calorimeter Level 1 trigger

The high luminosity (HL) LHC will pose significant detector challenges for radiation tolerance and event pileup, especially for forward calorimetry, and this will provide a benchmark for future hadron colliders. The CMS experiment has chosen a novel high granularity calorimeter (HGCAL) for the forward region as part of its planned Phase 2 upgrade for the HL-LHC. Based largely on silicon sensors, the HGCAL features unprecedented transverse and longitudinal readout segmentation, which will be exploited in the upgraded Level 1 (L1) trigger system. Together with the tracking information, which will also be available at L1, this will open the possibility of pioneering particle-flow-based techniques in the L1 trigger. The high channel granularity results in around one million trigger channels in total and so presents a significant challenge in terms of data manipulation and processing for the trigger, to be compared with the 2000 channels in the endcaps of the current detector. In addition, the high luminosity will result in an average of 140 interactions per bunch crossing that give a huge background rate in the forward region and these will need to be efficiently rejected by the trigger algorithms. Furthermore, 3-dimensional reconstruction of the HGCAL clusters, which will be used for particle-flow, in events with high hit rates is also a complex computational problem for the trigger, unprecedented with the 2-dimensional reconstruction in the current CMS calorimeter trigger. The status of the trigger architecture and design, as well as the concepts for the algorithms needed in order to tackle these major issues and their impact on trigger object performance, are presented here.

ATLAS LAr calorimeter performance in LHC Run-2

Abstract The Liquid-argon (LAr) sampling calorimeters are employed by ATLAS for all electromagnetic calorimetry in the pseudo-rapidity region | η | 3 . 2 , and for hadronic and forward calorimetry in the region 1 . 5 | η | 4 . 9 . In the first LHC run a total luminosity of 27 fb − 1 has been collected at centre-of-mass energies of 7 − 8 TeV . After detector consolidation during a long shutdown, Run-2 started in 2015 and 86 . 4 fb − 1 of data at a centre-of-mass energy of 13 TeV have been recorded. In order to realise the level-1 acceptance rate of 100 kHz in Run-2 data taking, the number of readout samples recorded and used for the energy and the time measurement has been modified from five to four while keeping the expected performance. The well calibrated and highly granular LAr calorimeter reached its design values both in energy measurement as well as in direction resolution. This contribution will give an overview of the detector operation, hardware improvements, changes in the monitoring and data quality procedures required to cope with increased pileup, as well as the achieved performance, including the calibration and stability of the electromagnetic scale, noise level, response uniformity and time resolution.

Calorimeter prototyping for the iMPACT project pCT scanner

The iMPACT project aims at building a novel pCT scanner for protons of medical energies in the range between 200 and 300 MeV, a proton tracking system that provides accurate information to create a map of the tissue density of human organs. Such information is crucial for an accurate aiming of proton-therapy beams and is currently provided by X-rays CT scans, with an accuracy lower than the one which could be achieved by using protons. One of its core elements is a high-granularity scintillator-based range calorimeter , designed to measure the proton residual energy after it travels the patient’s body. Here we review the design features of the iMPACT calorimeter, together with an all-around qualification of prototypes of its core components through test-bench measurements and proton beam data. We focus, in particular, on the qualification of the calorimeter elements towards a large-scale prototype, and a calibration study which will eventually allow to operate such a high granularity calorimeter with a fully digital readout at the target proton rate.

The CMS high granularity calorimeter for the high luminosity LHC

The CMS (Compact Muon Solenoid) experiment at CERN will undergo significant improvements during the Phase-II Upgrade to cope with a 10-fold increase in integrated luminosity with the HL-LHC (High Luminosity Large Hadron Collider) era. The forward calorimetry faces very high radiation levels and pileup in the detectors. The CMS collaboration is designing a highly granular calorimeter to replace the existing endcap calorimeters (CE). It features unprecedented transverse and longitudinal segmentation for both electromagnetic (CE-E) and hadronic (CE-H) parts. This will facilitate Particle Flow Algorithms (PFAs), where the structure of showers can be measured and used to enhance pileup rejection and particle identification, whilst still achieving good energy resolution. The CE-E and a large fraction of CE-H will use hexagonal silicon sensors produced from 200 mm (8 inch) wafers, with 192 (432) cells of 1 cm 2 (0.5 cm 2 ) size. The rest of the CE-H uses highly-segmented scintillator tiles with on-tile SiPM (Silicon Photomultiplier) readout. An overview of the HGCal (High Granularity Calorimeter) project is presented in this paper with a focus on the silicon sensors. We cover motivation, engineering design, expected performance and the current status of prototypes.

Study of the Response Uniformity of Scintillator Tiles for Highly Granular Calorimeters

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.

Generative models for fast simulation

Machine Learning techniques have been used in different applications by the HEP community: in this talk, we discuss the case of detector simulation. The need for simulated events, expected in the future for LHC experiments and their High Luminosity upgrades, is increasing dramatically and requires new fast simulation solutions. We will present results of several studies on the application of computer vision techniques to the simulation of detectors, such as calorimeters. We will also describe a new R&D activity, within the GeantV project, aimed at providing a configurable tool capable of training a neural network to reproduce the detector response and replace standard Monte Carlo simulation. This represents a generic approach in the sense that such a network could be designed and trained to simulate any kind of detector and, eventually, the whole data processing chain in order to get, directly in one step, the final reconstructed quantities, in just a small fraction of time. We will present the first three-dimensional images of energy showers in a high granularity calorimeter, obtained using Generative Adversarial Networks.

Three dimensional Generative Adversarial Networks for fast simulation

We present the first application of three-dimensional convolutional Generative Adversarial Network to High Energy Physics simulation. We generate three-dimensional images of particles depositing energy in high granularity calorimeters. This is the first time such an approach is taken in HEP where most of data is three-dimensional in nature but it is customary to convert it into two-dimensional slices. The present work proves the success of using three dimensional convolutional GAN. Energy showers are well reproduced in all dimensions and show a good agreement with standard techniques (Geant4 detailed simulation). We also demonstrate the ability to condition training on several parameters such as particle type and energy. This work aims at proving that deep learning techniques represent a valid fast alternative to standard Monte Carlo approaches. It is part of the GeantV project.

Construction and beam-tests of silicon and scintillator-SiPM modules for the CMS High Granularity Calorimeter for HL-LHC

A High Granularity Calorimeter (HGCAL) is being designed to replace the existing endcap calorimeters in CMS for the HL-LHC [1] era. It features unprecedented transverse and longitudinal segmentation for both electromagnetic (CE-E) and hadronic (CE-H) compartments, with silicon sensors being chosen for the high-pseudorapidity regions due to their radiation tolerance. The remainder of the HGCAL, in the lower radiation environment, will use plastic scintillator with on-tile SiPM readout. Prototype hexagonal silicon modules, featuring a new Skiroc2-CMS front-end chip, together with a modified version of the scintillator-SiPM CALICE AHCAL, have been built and tested in beams at CERN in 2017. In this paper, we present measurements of noise, calibration, shower shapes and performance with electrons, pions and muons.

Studies of detector cells for a hadronic calorimeter based on plastic scintillators

In this paper, we study variations of a plastic scintillator tile coupled to silicon photomultiplier via a dome-shaped cavity originally developed in the CALICE collaboration. Four kinds of plastic scintillator detector cells with different sizes based on the structure were studied for applications in analog readout highly granular hadronic calorimeter (AHCAL) in future circular electron positron collider (CEPC) project. The responses to cosmic rays of the detector cells could reach 33.89 p.e./MIPs (minimum ionizing particles). The good results of both response uniformity and MIP detection efficiency (above 95%) show that the detector cells with larger sizes ( $$40\times 40\times 3$$ and $$50\times 50\times 3\,\hbox {mm}^{3}$$ ) could provide an option for AHCAL detector cells of CEPC detectors.

Tests of Scintillator Tiles for the Technological Prototype of Highly Granular Hadron Calorimeter

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Design and performance of an electromagnetic calorimeter for a FCC-hh experiment

The physics reach and feasibility of the Future Circular Collider are currently under investigation. The goal is to collide protons with centre-of-mass energies up to 100 TeV, extending the research carried out at the current HEP facilities. The detectors designed for the FCC experiments need to tackle harsh conditions of the unprecedented collision energy and luminosity. The baseline technology for the calorimeter system of the FCC-hh detector is described. The electromagnetic calorimeter in the barrel, as well as the electromagnetic and hadronic calorimeters in the endcaps and the forward regions, are based on the liquid argon as active material. The detector layout in the barrel region combines the concept of a high granularity calorimeter with precise energy measurements. The calorimeters have to meet the requirements of high radiation hardness and must be able to deal with a very high number of collisions per bunch crossings (pile-up). A very good energy and angular resolution for a wide range of electrons' and photons' momentum is needed in order to meet the demands based on the physics benchmarks. First results of the performance studies with the new liquid argon calorimeter are presented, meeting the energy resolution goal.

Latest R&D news and beam test performance of the highly granular SiW-ECAL technological prototype for the ILC

High precision physics at future colliders as the International Linear Collider (ILC) require unprecedented high precision in the determination of the energy of final state particles. The needed precision will be achieved thanks to the Particle Flow algorithms (PF) which require highly granular and hermetic calorimeters systems. The physical proof of concept of the PF was performed in the previous campaign of beam tests of physic prototypes within the CALICE collaboration. One of these prototypes was the physics prototype of the Silicon-Tungsten Electromagnetic Calorimeter (SiW-ECAL) for the ILC. In this document we present the latest news on R&D of the next generation prototype, the technological prototype with fully embedded very front-end (VFE) electronics, of the SiW-ECAL. Special emphasis is given to the presentation and discussion of the first results from the beam test done at DESY in June 2017. The physics program for such beam test consisted in the calibration and commissioning of the current set of available SiW ECAL modules; the test of performance of individual slabs under 1T magnetic fields; and the study of electromagnetic showers events.

Electronics and triggering challenges for the CMS High Granularity Calorimeter

The High Granularity Calorimeter (HGCAL), presently being designed by the CMS collaboration to replace the CMS endcap calorimeters for the High Luminosity phase of LHC, will feature six million channels distributed over 52 longitudinal layers. The requirements for the front-end electronics are extremely challenging, including high dynamic range (0.2 fC–10 pC), low noise (∼2000 e− to be able to calibrate on single minimum ionising particles throughout the detector lifetime) and low power consumption (∼20 mW/channel), as well as the need to select and transmit trigger information with a high granularity. Exploiting the intrinsic precision-timing capabilities of silicon sensors also requires careful design of the front-end electronics as well as the whole system, particularly clock distribution. The harsh radiation environment and requirement to keep the whole detector as dense as possible will require novel solutions to the on-detector electronics layout. Processing the data from the HGCAL imposes equally large challenges on the off-detector electronics, both for the hardware and incorporated algorithms. We present an overview of the complete electronics architecture, as well as the performance of prototype components and algorithms.