Search arXivSearch

arXiv · 1712.05638

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

Abstract

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 an electromagnetic compartment comprising 28 layers of silicon pad detectors with pad areas of 0.5 - 1.0 cm2 interspersed with absorbers. Prototype modules, based on 6-inch hexagonal silicon pad sensors with 128 channels, have been constructed and include many of the features required for this challenging detector. In 2016, beam tests of sampling configurations made from these modules have been conducted both at FNAL and at CERN using the Skiroc2 front- end chip (designed for the CALICE experiment for ILC). In 2017, the setup has been extended with CALICEs AHCAL prototype, a scinitillator based sampling calorimeter, and it was further tested in dedicated beam tests at CERN. There, the new Skiroc2-CMS front-end ASIC was used for the first time. We highlight final results from our studies in 2016, including position resolution as well as precision timing-measurements. Furthermore, the extended setup in 2017 is discussed and first results from beam tests with electrons and pions are shown.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Thorben Quast. 2017-12-20. Construction and beam-tests of silicon-tungsten prototype modules for the CMS High Granularity Calorimeter for HL-LHC. https://doi.org/10.1088/1748-0221%2F13%2F02%2Fc02044

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

The Remote Analog to Digital Conversion DAQ System for the TRISTAN Detector Upgrade

The TRISTAN detector is an upgrade to the KATRIN experiment to enable a differential measurement of the tritium $β$-decay spectrum to search for sterile neutrinos with keV masses. This entails performing precision electron spectroscopy with over one thousand silicon drift detector pixels, each responsible for recording incident electron rates of $10^5$ counts per second. A project specific data acquisition (DAQ) system is developed to meet the experimental challenges through a remote analog to digital conversion (RADC) design. In this work, the conceptual design of the RADC DAQ is presented along with the built system for operating the TRISTAN detector upgrade. The system includes flexible signal processing logic and data management that is optimized for the high-rate precision measurement.

physics.ins-det

True Alternating Current Scanning Tunneling Microscope (ACSTM): tunneling on insulators

Scanning Tunneling Microscopy (STM) has revolutionized our atomic scale understanding of surfaces and accelerated progress in nanotechnology. This technique, however, is restricted to metal or semiconducting samples, as it requires a tiny current to stabilize the tip-sample distance with atomic scale precision. We developed a new imaging and feedback method that relies on true alternating current (AC) without any direct current (DC) component. This technique does not only enable the imaging on non-conducting surfaces with atomic step resolution, like (thin) glass and oxides, it provides also access to high-frequency electronic signal coming from the sample. We demonstrate that it is possible to measure on 25nm thick silicon oxide with 10 MHz tunneling current.

physics.ins-det

Charged-particle topology reconstruction with an in-liquid SiPM array

Liquid scintillator detectors instrumented with photosensors inside the scintillation volume preserve local optical information that is largely lost in conventional boundary-readout geometries. We demonstrate that this information is sufficient for charged-particle topology reconstruction using a sparse three-dimensional lattice of silicon photomultipliers. After validating the Geant4 detector response against measured photon-count distributions, a simulation-trained, time-informed convolutional neural network reconstructs the entry and exit points of through-going muons with median residuals of 1.91~cm and 2.39~cm, respectively. The reconstructed endpoints are geometrically consistent with acceptance regions defined by external trigger counters in cosmic-ray muon data. The same framework also reconstructs the production vertices of simulated positron starting-track events with a median residual of about 4.5~cm. These results establish the feasibility of topology-sensitive reconstruction using sparse in-liquid photosensor arrays in homogeneous liquid scintillator detectors.

physics.ins-det