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ILC.BreveDescripcionDelSoftwareDeILCMokkaYMarlinr1.2 - 22 Sep 2009 - 13:36 - Main.iglesiastopic end

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1. Intalacion del software de ILC

1.0. Breve descripcion del Software en ILC: Mokka and Marlin

The software framework developed by the LDC concept is based on the LCIO persistency format and event data model. The detailed simulation of the detector response is performed by the GEANT4 based Mokka application. The detailed subdetector geometries and component materials are stored in a MySQL+ database. The overall detector is then built from individual subdetectors, making it relatively straightforward to compare different technology choices. The corresponding *C++ code instantiating the subdetector geometry in memory is written such that the whole detector model can be scaled in length and radius; this feature proved invaluable in optimising the detector geometry. The GEAR package provides access to these geometrical detector properties at the reconstruction and analysis level.

The Mokka generated events are processed in Marlin. Marlin is a modular C++ application framework which supports plug-in modules (called processors) which can be loaded at runtime. This plug-in-based design supports the distributed development of reconstruction algorithms and also allows comparison of different algorithms at runtime, e.g. it is possible to run two tracking algorithms producing parallel collections of reconstructed tracks.

Event reconstruction is performed with the MarlinReco package. This consists of a set of modules for digitisation, track finding, track fitting, particle flow reconstruction, and flavour tagging. The hit smearing for the tracking detectors is implemented at the digitisation stage using the same parameterisation as used for Satellites, except that resolutions for the intermediate silicon tracker (SIT) are taken to be 4 micras for sigma_r-phi and 50 micras for sigma_z.


The pattern recognition processors use Kalman Filter techniques and code developed for the LEP experiments. Tracks from standalone pattern recognition in the silicon trackers and in the TPC are combined and refitted. Reconstruction of the individual particles in the event is performed with the particle flow algorithm in the PandoraPFA package, currently the best algorithm available. The LCFIVertex package provides sophisticated code for vertex finding/fitting and for the identification of heavy flavour jets using a neural network approach. It also provides jet charge estimation. In addition to reconstruction algorithms, MarlinReco includes a set of analysis tools such as algorithms for jet finding and kinematic fitting. The RAVE toolkit , also available within Marlin, provides an alternative set of vertex reconstruction based on linear and non-linear estimators. tools such as algorithms for jet finding and kinematic fitting.

Usefull Bibliography:

- F. Gaede, T. Behnke, N. Graf, and T. Johnson, “LCIO: A persistency framework for linear collider simulation studies” Proceedings of CHEP 03, La Jolla, California,24-28 Mar 2003, TUKT001 (2003) , arXiv:physics/0306114.

- F. Gaede et al., “MarlinReco webpage”.

- M. A. Thomson, “Progress with Particle Flow Calorimetry” arXiv:0709.1360 [physics.ins-det].

- P. Mora de Freitas and H. Videau, “Detector simulation with MOKKA / GEANT4: Present and future”. Prepared for International Workshop on Linear Colliders (LCWS 2002), Jeju Island, Korea, 26-30 Aug 2002.

- “GEAR - a geometry description toolkit for ILC reconstruction software”.

- F. Gaede, “Marlin and LCCD: Software tools for the ILC” Nucl. Instrum. Meth.A559 (2006) 177–180.

- F. Gaede and J. Engels, “Marlin et al - A software Framework for ILC detector R&D”. EUDET-Report-2007-11.

- LCFI Collaboration, S. Hillert, “The LCFIVertex Package: vertex detector-based Reconstruction at the ILC” Proceedings LCWS07, Hamburg, Germany, 30 May - 3 Jun 2007, pp SIM25 (2007) , arXiv:0708.2622 [physics.ins-det].

- R. Fruhwirth, W. Waltenberger, and P. Vanlaer, “Adaptive vertex fitting” J. Phys.G34 (2007) N343.

-- Main.iglesias - 18 Sep 2009
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