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A. Alpana

Publications and source records attributed to A. Alpana.

4 recordsLinked to original sources

An insight into the rare $Z\rightarrow b \bar{b}γ$ at the HL-LHC

Studies at the $Z$-pole have played an important role in developing our understanding of the Standard Model (SM). Continuing the explorations in this regime, we consider the possibility of the production of two $b$-quarks and a photon in proton-proton collisions at the HL-LHC. While such a final state is possible in the SM by means of the process $Z\rightarrow b\bar b$ decay with a radiated photon, the focus is on extracting its possible origins due to beyond Standard Model (BSM) physics. The signal topology can be broadly identified as $Z\rightarrow Φγ\rightarrow b\bar bγ$, where $ Φ$ can either be a spin-0 or spin-2 state with a mass less than that of the $Z$ boson.The analysis is characterised by two relatively low $p_T$ jets that are required to be $b$-tagged jets and an isolated photon. The study provides a quantitative framework for their identification and highlights the potential challenges associated with this final state. A range of machine learning architectures is employed to demonstrate the stability and reliability of the discriminating variables. This study highlights the importance of the low-$p_T$ objects in searches at the HL-LHC, hence the need to pay special attention to their identification and efficiencies.

hep-ph

Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter

A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated.

physics.ins-det

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

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