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Ahmed Abdelmotteleb

Publications and source records attributed to Ahmed Abdelmotteleb.

2 recordsLinked to original sources

The LHCb Sprucing and Analysis Productions

The LHCb detector underwent a comprehensive upgrade in preparation for the third data-taking run of the Large Hadron Collider (LHC), known as LHCb Upgrade I. The increased data rate of Run 3 not only posed data collection (Online) challenges but also significant Offline data processing and analysis ones. The offline processing and analysis model was consequently upgraded to handle the factor 30 increase in data volume and the associated demands of ever-growing analyst-level datasets, led by the LHCb Data Processing and Analysis (DPA) project. This paper documents the LHCb "Sprucing" - the centralised offline processing, selections and streaming of data - and "Analysis Productions" - the centralised and highly automated declarative nTuple production system. The DaVinci application used by analysis productions for tupling spruced data is described as well as the apd and lbconda tools for data retrieval and analysis environment configuration. These tools allow for greatly improved analyst workflows and analysis preservation. Finally, the approach to data processing and analysis in the High-Luminosity Large Hadron Collider (HL-LHC) era - LHCb Upgrade II - is discussed.

hep-ex↗

A fast and stable approximate maximum-likelihood method for template fits

Barlow and Beeston presented an exact likelihood for the problem of fitting a composite model consisting of binned templates obtained from Monte-Carlo simulation which are fitted to equally binned data. Solving the exact likelihood is technically challenging, and therefore Conway proposed an approximate likelihood to address these challenges. In this paper, a new approximate likelihood is derived from the exact Barlow-Beeston one. The new approximate likelihood and Conway's likelihood are generalized to problems of fitting weighted data with weighted templates. The performance of estimates obtained with all three likelihoods is studied on two toy examples: a simple one and a challenging one. The performance of the approximate likelihoods is comparable to the exact Barlow-Beeston likelihood, while the performance in fits with weighted templates is better. The approximate likelihoods evaluate faster than the Barlow-Beeston one when the number of bins is large.

stat.ME↗