BEGIN:VCALENDAR VERSION:2.0 PRODID:-//linuxsoftware.nz//NONSGML Joyous v1.4//EN BEGIN:VEVENT SUMMARY:Optimization of the local reconstruction in a high granular calori meter using a heterogenous computing model DTSTART:20250703T100000Z DTEND:20250703T120000Z DTSTAMP:20260730T182300Z UID:5ba3883d-e899-4ecc-bec1-0083604da67a SEQUENCE:2 CREATED:20250626T134941Z DESCRIPTION:Password: 561232The High-Luminosity phase of the Large Hadron Collider (HL-LHC) at the European Organisation for Nuclear Research (CERN) will deliver an unprecedented dataset of proton-proton collisions at the highest centre-of-mass energies to date. With over 140 simultaneous intera ctions per bunch crossing and luminosity of around 1034 cm−2 s∠’1 \, both the CMS detector and its computing infrastructure face signif icant challenges. These include severe radiation damage\, high particle fl uxes\, and the need for fast and precise reconstruction to isolate physics signals of interest\, particularly for precision measurements. To meet th ese demands\, the CMS experiment is undergoing major upgrades\, including the replacement of the endcap calorimeters with a high-granularity samplin g calorimeter (HGCAL). HGCAL will provide combined energy and time measure ments from approximately six million channels\, enabling accurate particle flow reconstruction under extreme pileup. The upgrade features a silicon- based sampling structure with fine spatial segmentation\, enhancing both s patial and temporal resolution. This thesis explores the development and v alidation of a local reconstruction and calibration framework using data f rom HGCAL beam tests. A key contribution is an automated method to extract the most probable value (MPV) of energy deposits from minimum ionising pa rticles (MIP) across individual silicon sensors\, a critical step in calor imeter energy calibration. Essential processing steps include pedestal sub traction\, noise correction\, and timing alignment. The calibration algori thms were tested and validated under real beam test conditions. This work contributes to a per-channel calibration method that will be essential for the accurate calibration of HGCAL in preparation for its deployment in th e HL-LHC era. LAST-MODIFIED:20250626T135007Z LOCATION:Online URL:http://df.vps.tecnico.ulisboa.pt/pt/eventos/optimization-of-the-local- reconstruction-in-a-high-granular-calorimeter-using-a-heterogenous-computi ng-model/ X-ALT-DESC;FMTTYPE=text/html:

Password: 561232

The High-Luminosity phase of the Large Hadron C ollider (HL-LHC) at the European Organisation for Nuclear Research (CERN) will deliver an unprecedented dataset of proton-proton collisions at the h ighest centre-of-mass energies to date. With over 140 simultaneous interac tions per bunch crossing and luminosity of around 1034 cm−2 s− 1 \, both the CMS detector and its computing infrastructure face significa nt challenges.

These include severe radiation damage\, high part icle fluxes\, and the need for fast and precise reconstruction to isolate physics signals of interest\, particularly for precision measurements. To meet these demands\, the CMS experiment is undergoing major upgrades\, inc luding the replacement of the endcap calorimeters with a high-granularity sampling calorimeter (HGCAL).

HGCAL will provide combined energy and time measurements from approximately six million channels\, enabling accurate particle flow reconstruction under extreme pileup. The upgrade fe atures a silicon-based sampling structure with fine spatial segmentation\, enhancing both spatial and temporal resolution. This thesis explores the development and validation of a local reconstruction and calibration frame work using data from HGCAL beam tests.

A key contribution is an automated method to extract the most probable value (MPV) of energy deposi ts from minimum ionising particles (MIP) across individual silicon sensors \, a critical step in calorimeter energy calibration. Essential processing steps include pedestal subtraction\, noise correction\, and timing alignm ent. The calibration algorithms were tested and validated under real beam test conditions. This work contributes to a per-channel calibration method that will be essential for the accurate calibration of HGCAL in preparati on for its deployment in the HL-LHC era.

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