CERN Accelerating science

Article
Report number	arXiv:2309.13213
Title	The LHCb ultra-fast simulation option, Lamarr design and validation
Related title	The LHCb ultra-fast simulation option, Lamarr: design and validation
Author(s)	Anderlini, Lucio (INFN, Florence) ; Barbetti, Matteo (INFN, Florence ; U. Florence (main)) ; Capelli, Simone (INFN, Milan Bicocca ; Milan Bicocca U.) ; Corti, Gloria (CERN) ; Davis, Adam (Manchester U.) ; Derkach, Denis (Higher Sch. of Economics, Moscow) ; Kazeev, Nikita (Unlisted) ; Maevskiy, Artem (Unlisted) ; Martinelli, Maurizio (INFN, Milan Bicocca ; Milan Bicocca U.) ; Mokonenko, Sergei (Unlisted) ; Siddi, Benedetto Gianluca (Ferrara U.) ; Xu, Zehua (LPC, Clermont-Ferrand)
Collaboration	LHCb Simulation Project
Publication	2024
Imprint	2023-09-22
Number of pages	9
Note	Under review in EPJ Web of Conferences (CHEP 2023)
In:	EPJ Web Conf. 295 (2024) 03040
In:	26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023, pp.03040
DOI	10.1051/epjconf/202429503040
Subject category	physics.ins-det ; Detectors and Experimental Techniques ; cs.LG ; Computing and Computers ; hep-ex ; Particle Physics - Experiment
Accelerator/Facility, Experiment	CERN LHC ; LHCb
Abstract	Detailed detector simulation is the major consumer of CPU resources at LHCb, having used more than 90% of the total computing budget during Run 2 of the Large Hadron Collider at CERN. As data is collected by the upgraded LHCb detector during Run 3 of the LHC, larger requests for simulated data samples are necessary, and will far exceed the pledged resources of the experiment, even with existing fast simulation options. An evolution of technologies and techniques to produce simulated samples is mandatory to meet the upcoming needs of analysis to interpret signal versus background and measure efficiencies. In this context, we propose Lamarr, a Gaudi-based framework designed to offer the fastest solution for the simulation of the LHCb detector. Lamarr consists of a pipeline of modules parameterizing both the detector response and the reconstruction algorithms of the LHCb experiment. Most of the parameterizations are made of Deep Generative Models and Gradient Boosted Decision Trees trained on simulated samples or alternatively, where possible, on real data. Embedding Lamarr in the general LHCb Gauss Simulation framework allows combining its execution with any of the available generators in a seamless way. Lamarr has been validated by comparing key reconstructed quantities with Detailed Simulation. Good agreement of the simulated distributions is obtained with two-order-of-magnitude speed-up of the simulation phase.
Copyright/License	publication: © 2024 The Authors (License: CC-BY-4.0) preprint: (License: CC BY 4.0)

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