LHCb Simulation Commissioning, Validation, and Data Quality: Key Insights from May 2013
This document provides a comprehensive overview of the simulation commissioning, validation, and data quality processes used by LHCb during the simulation days held on May 23rd and 24th, 2013. It discusses tools and methodologies for testing various software versions, including Gauss and Geant4, and highlights the need for systematic validation of outputs to ensure they meet expected performance criteria. The presentation also emphasizes strategies for managing changes in physics models and detector configurations, and the importance of utilizing proper data quality measures in Monte Carlo simulations.
LHCb Simulation Commissioning, Validation, and Data Quality: Key Insights from May 2013
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Presentation Transcript
LHCb Simulation Day 23rd & 24th May 2013 Simulation Commissioning, Validation, Data Quality A brain dump to prompt discussion Many points applicable to any of LHCb software but some simulation specificities Gloria Corti
What is what? Commissioning Validation Data Quality t = Before releasing t = with productions that could be PRODUCTIONS To adopt a new version of Gauss FOR PRODUCTION is a long process with a set of tests at different levels We have tools but what is the best tool and what should be do?
My definitions - Commissioning • Commissioning of the software per-se, i.e. make a new version of Gauss compile and run • New compilers, new Gaudi version, new (version of) generators, new Geant4 version • For some of these changes the outcome of the application should not change • For the geometry for example checking overlaps are part of this
Commissioning Gauss (and Boole) • … Once things that are suppose to work are committed • Not always possible • Gauss is in the nightlies but is the winner for red squares! • Even when it is successful …. Part of it because Gauss relies on random numbers • We (us Gauss managers) need to review what we want to test • Each test should look at one thing only, for example we just test that a new event type can run • We can customize tests • Need to disentangle reference tests that should give identical output and those for evolution • We have been using many slots recently • Support for various Sim05, Sim06, Sim08 • Exploring new versions of Geant4
My definitions – Validation of simulation • Checking that only changes in physics and detector modeling as expected are there or Physics validation • Checking output with special productions • Need at least few 1000 events • Particle guns productions • Productions with different simulation settings of few 100k events • Checking that performance is ‘as expected’ and ‘acceptable’ or Software validation – and keep track of its evolution • Again need at least few 1000 events • Check that the whole simulation processing chain works • Integration tests with old and new conditions • ‘Commissioning’ with smallish samples, few 1000 events • Validating that the ‘final(s)’ configurations are not worse than
Recent validation of Sim08 • In Sim08 we did change a lot in Gauss and simulation conditions • New version of Pythia6, Pythia8 at production quality, new EvtGen, new Gaudi version, new compilers, new version of Geant4, new hadronicphyics list used • Start out with building in the nightlies • As usual compilation errors (new Gaudi, new Geant4, new compiler…) • Made private test productions for new interesting features and understand how to use new functionalities • Gauss stand alone studies • To investigate new Pythia8, new EvtGen, new hadronic physics list cross sections, dE/dx for various EM physics lists • Central productions for systematic studies and effect on physics and verify calibrations • Particle guns studies (Gauss and Gauss+Boole) • Check effects of dE/dx on tracking and calorimetry • Check effect of hadronic physics on asymmetries
Data Quality for MC • But still things slip through! • Some things can only be caught in production • Jobs getting stuck • All reconstruction distributions make sense • Need Data Quality for the MC • See Marco A.’s slides • Investigated in the past how to use Data Quality tools for Validation and Regressions tests • Far from ideal for MC as not really a single reference • See Ben’s slides on tools for validation test infrastructure