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To sustain the harsher conditions of the high-luminosity LHC, the CMS collaboration is designing a novel endcap calorimeter system. The new calorimeter will predominantly use silicon sensors to achieve sufficient radiation tolerance and will maintain highly-granular information in the readout to help mitigate the effects of pileup. In regions characterised by lower radiation levels, small scintillator tiles with individual on-tile SiPM readout are employed. A unique reconstruction framework (TICL: The Iterative CLustering) is being developed to fully exploit the granularity and other significant detector features, such as particle identification and precision timing, with a view to mitigate pileup in the very dense environment of HL-LHC. The inputs to the framework are clusters of energy deposited in individual calorimeter layers. Clusters are formed by a density-based algorithm. Recent developments and tunes of the clustering algorithm will be presented. To help reduce the expected pressure on the computing resources in the HL-LHC era, the algorithms and their data structures are designed to be executed on GPUs. Preliminary results will be presented on decreases in clustering time when using GPUs versus CPUs. Ideas for machine-learning techniques to further improve the speed and accuracy of reconstruction algorithms will be presented. [ABSTRACT FROM AUTHOR]

The future High Luminosity LHC (HL-LHC) is expected to deliver about 5 times higher instantaneous luminosity than the present LHC, resulting in pile-up up to 200 interactions per bunch crossing (PU200). As part of the phase-II upgrade program, the CMS collaboration is developing a new endcap calorimeter system, the High Granularity Calorimeter (HGCAL), featuring highly-segmented hexagonal silicon sensors and scintillators with more than 6 million channels. For each event, the HGCAL clustering algorithm needs to group more than 105 hits into clusters. As consequence of both high pile-up and the high granularity, the HGCAL clustering algorithm is confronted with an unprecedented computing load. CLUE (CLUsters of Energy) is a fast fullyparallelizable density-based clustering algorithm, optimized for high pile-up scenarios in high granularity calorimeters. In this paper, we present both CPU and GPU implementations of CLUE in the application of HGCAL clustering in the CMS Software framework (CMSSW). Comparing with the previous HGCAL clustering algorithm, CLUE on CPU (GPU) in CMSSW is 30x (180x) faster in processing PU200 events while outputting almost the same clustering results. [ABSTRACT FROM AUTHOR]

The CMS experiment at the LHC features an electromagnetic calorimeter (ECAL) made of lead tungstate scintillating crystals. The ECAL energy response is fundamental for both triggering purposes and offline analysis. Due to the challenging LHC radiation environment, the response of both crystals and photodetectors to particles evolves with time. Therefore continuous monitoring and correction of the ageing effects are crucial. Fast, reliable and efficient workflows are set up to have a first set of corrections computed within 48 hours from data-taking, making use of dedicated data streams and processing. Such corrections, stored in relational databases, are then accessed during the prompt offline reconstruction of the CMS data. Twice a week, the calibrations used in the trigger are also updated in the database and accessed during the data-taking. In this note, the design of the CMS ECAL data handling and processing is reviewed. [ABSTRACT FROM AUTHOR]

Control and monitoring of experimental facilities as well as laboratory equipment requires handling a blend of different tasks. Often in industrial or scientific fields there are standards or form factor to comply with and electronic interfaces or custom busses to adopt. With such tight boundary conditions, the integration of an off-the-shelf Single Board Computer (SBC) is not always a possible or viable alternative. The availability of electronic schematics and PCBs with open-source Hardware license for various SBCs overcomes such integration problems, making feasible the implementation of a custom architecture composed by a central core inherited from a vendor reference design (most likely the microprocessor, static RAM and flash memory) augmented with application-specific integrated circuits and hardware resources, in order to handle the requirements of the specific environment. The user is then able to exploit most of the supported tools and software provided by opensource community, fulfilling all the constraints enforced by his environment. We have used such an approach for the design and development of the monitoring system of the endcap electromagnetic calorimeter of the Belle II experiment, presently running at KEK Laboratory (Tsukuba, Japan). Here we present and discuss the main aspects of the hardware architectures and noise performances tailored on the needs of a detector designed around CsI crystal scintillators. [ABSTRACT FROM AUTHOR]

Measurements of high energy cosmic rays in the "knee" region (about 1015 eV) are currently available only with ground detectors: new observations of cosmic particles up to these energies with direct measurements are one of the main goals of the next generation space experiments. To achieve those aims, a large acceptance, good energy resolution and particle identification are needed. CaloCube is the design of a space borne calorimeter which is capable to accept particles coming from any direction, increasing the acceptance with respect to traditional telescopes. A good performance for both hadronic and electromagnetic showers is achieved with a 3-D sampling capability: the basic picture of CaloCube is a cubic homogeneous calorimeter which consists of cubic scintillating crystals. MC simulations, concerning different materials and geometrical configurations, and several beam tests with different versions of the CaloCube prototype have been employed to optimize both the detector design and the data analysis method. Taking advantage of the CaloCube project, the space experiment HERD ("High Energy Cosmic Radiation Detection") will include a large acceptance cubic calorimeter with cubic LYSO crystals. It will be installed on-board of the Chinese space station around 2025. Beside the charged particle observations, high energy gamma-rays provide direct information about the galactic cosmic ray sources. A new project named "Tracker In Calorimeter" (TIC) was approved by INFN in 2017 with the main purpose of the optimization of the calorimeter design for the reconstruction of the gamma-ray direction, without the requirement of additional not homogeneous pre-shower detector. A TIC prototype was recently assembled and tested at the PS-CERN and SPS-CERN accelerators. [ABSTRACT FROM AUTHOR]

The core of the High-Energy Particle Detector (HEPD) on board of the China Seismo-Electromagnetic Satellite (CSES) is a segmented calorimeter, which is composed with an upper tower of plastic scintillator counters and a bottom array of LYSO large crystals. Electrons with energy below 100MeV, protons and light nuclei, below few hundreds ofMeV/nucleon are fully contained within this calorimeter. Mainly the LYSO array (density 7.3 g/cm3, thickness around 29.2 g/cm2) extends the HEPD energy range, allowing those measurements (solar energetic particles, low-energy cosmic rays) which are more related to astroparticle physics topics. Two identical copies of HEPD, and then of its calorimeter, exist: the Flight (FM) and the Qualification (QM) models. While the FM has achieved the orbit on board of the CSES satellite in February 2018, the Qualification Model, is used, at ground, for tests and calibrations. A report on the characterization of this compact particle space detector and on preliminary studies and results, will be given. [ABSTRACT FROM AUTHOR]

The performance of the CMS detector in Run 2 of the LHC, and in particular, with early 2017 data is presented. Special attention is given to the performance of the recently upgraded detector components. [ABSTRACT FROM AUTHOR]

The ATLAS Tile Calorimeter is the central section 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. This sampling calorimeter uses steel plates as absorber and scintillating tiles as active medium. The light produced by the passage of charged particles is transmitted by wavelength shifting fibres to photomultiplier tubes, located in the outer part of the calorimeter. Neutral particles may also produce a signal after interacting with the material and producing charged particles. The readout is segmented into about 5000 cells, each of them being read out by two photomultipliers in parallel. To calibrate and monitor the stability and performance of each part of the readout chain during the data taking, a set of calibration systems is used. This comprises Cesium radioactive sources, Laser, charge injection elements and an integrator based readout system. Information from all systems allows to monitor and equalise the calorimeter response at each stage of the signal production, from scintillation light to digitisation. Calibration runs are monitored from a data quality perspective and used as a cross-check for physics runs. The data quality efficiency achieved during 2016 was 98.9%. These calibration and stability of the calorimeter reported here show that the TileCal performance is within the design requirements and has given essential contribution to reconstructed objects and physics results. [ABSTRACT FROM AUTHOR]