ECAL software development Yuri Kharlov IHEP Protvino.

Slides:



Advertisements
Similar presentations
CBM Calorimeter System CBM collaboration meeting, October 2008 I.Korolko(ITEP, Moscow)
Advertisements

Particle identification in ECAL Alexander Artamonov, Yuri Kharlov IHEP, Protvino CBM collaboration meeting
LC Calorimeter Testbeam Requirements Sufficient data for Energy Flow algorithm development Provide data for calorimeter tracking algorithms  Help setting.
Parameterized Shower Simulation in Lelaps: a Comparison with Geant4 Daniel Birt, Amy Nicholson.
W. Clarida, HCAL Meeting, Fermilab Oct. 06 Quartz Plate Calorimeter Prototype Geant4 Simulation Progress W. Clarida The University of Iowa.
Testbeam Requirements for LC Calorimetry S. R. Magill for the Calorimetry Working Group Physics/Detector Goals for LC Calorimetry E-flow implications for.
Introduction to Hadronic Final State Reconstruction in Collider Experiments Introduction to Hadronic Final State Reconstruction in Collider Experiments.
March 31, Status of the TOF, Ckov and Virtual Detector Packages in G4Mice Steve Kahn Brookhaven National Laboratory Mice Collaboration Meeting March.
Introduction to Hadronic Final State Reconstruction in Collider Experiments Introduction to Hadronic Final State Reconstruction in Collider Experiments.
PFA Development – Definitions and Preparation 0) Generate some events w/G4 in proper format 1)Check Sampling Fractions ECAL, HCAL separately How? Photons,
Introduction to Hadronic Final State Reconstruction in Collider Experiments Introduction to Hadronic Final State Reconstruction in Collider Experiments.
CMS Full Simulation for Run-2 M. Hildrith, V. Ivanchenko, D. Lange CHEP'15 1.
General Trigger Philosophy The definition of ROI’s is what allows, by transferring a moderate amount of information, to concentrate on improvements in.
Introduction to Hadronic Final State Reconstruction in Collider Experiments Introduction to Hadronic Final State Reconstruction in Collider Experiments.
Application of Neural Networks for Energy Reconstruction J. Damgov and L. Litov University of Sofia.
Michele Faucci Giannelli TILC09, Tsukuba, 18 April 2009 SiW Electromagnetic Calorimeter Testbeam results.
Photon reconstruction and calorimeter software Mikhail Prokudin.
ALCPG October 25 th 2007 Hans Wenzel Calorimetry in slic How-to Motivation for dual readout Calorimeter What are our requirements Why did we choose SLIC.
Irakli Chakaberia Final Examination April 28, 2014.
The CALICE Si-W ECAL - physics prototype 2012/Apr/25 Tamaki Yoshioka (Kyushu University) Roman Poschl (LAL Orsay)
CALORIMETER system for the CBM detector Ivan Korolko (ITEP Moscow) CBM Collaboration meeting, October 2004.
BeamCal Simulations with Mokka Madalina Stanescu-Bellu West University Timisoara, Romania Desy, Zeuthen 30 Jun 2009 – FCAL Meeting.
Summary of Simulation and Reconstruction Shaomin CHEN (Tsinghua University)  Framework and toolkit  Application in ILC detector design Jupiter/Satellites,
Fabiola Gianotti, 31/8/’99 PHYSICS and SOFTWARE ATLAS Software Week 31/8/’99 Fabiola Gianotti Software requirements of physics groups What should Detector.
CHEP06, Mumbai-India, Feb 2006V. Daniel Elvira 1 The CMS Simulation Validation Suite V. Daniel Elvira (Fermilab) for the CMS Collaboration.
Event Reconstruction in SiD02 with a Dual Readout Calorimeter Detector Geometry EM Calibration Cerenkov/Scintillator Correction Jet Reconstruction Performance.
Pion Showers in Highly Granular Calorimeters Jaroslav Cvach on behalf of the CALICE Collaboration Institute of Physics of the ASCR, Na Slovance 2, CZ -
Geant4 in production: status and developments John Apostolakis (CERN) Makoto Asai (SLAC) for the Geant4 collaboration.
16-Nov-2002Konstantin Beloous1 Digital Hadron Calorimeter Energy Resolution.
1 Calorimetry Simulations Norman A. Graf for the SLAC Group January 10, 2003.
UTA GEM DHCAL Simulation Jae Yu * UTA DoE Site Visit Nov. 13, 2003 (*On behalf of the UTA team; A. Brandt, K. De, S. Habib, V. Kaushik, J. Li, M. Sosebee,
Pandora calorimetry and leakage correction Peter Speckmayer 2010/09/011Peter Speckmayer, WG2 meeting.
The CMS Simulation Software Julia Yarba, Fermilab on behalf of CMS Collaboration 22 m long, 15 m in diameter Over a million geometrical volumes Many complex.
Positional and Angular Resolution of the CALICE Pre-Prototype ECAL Hakan Yilmaz.
ECAL PID1 Particle identification in ECAL Yuri Kharlov, Alexander Artamonov IHEP, Protvino CBM collaboration meeting
Results from particle beam tests of the ATLAS liquid argon endcap calorimeters Beam test setup Signal reconstruction Response to electrons  Electromagnetic.
CBM ECAL simulation status Prokudin Mikhail ITEP.
Development of Digital Hadron Calorimeter Using GEM Shahnoor Habib For HEP Group, UT Arlington Oct. 12, 2002 TSAPS Fall ’02, UT Brownsville Simulation.
PFAs – A Critical Look Where Does (my) SiD PFA go Wrong? S. R. Magill ANL ALCPG 10/04/07.
13 July 2005 ACFA8 Gamma Finding procedure for Realistic PFA T.Fujikawa(Tohoku Univ.), M-C. Chang(Tohoku Univ.), K.Fujii(KEK), A.Miyamoto(KEK), S.Yamashita(ICEPP),
Photon reconstruction and matching Prokudin Mikhail.
CALOR April Algorithms for the DØ Calorimeter Sophie Trincaz-Duvoid LPNHE – PARIS VI for the DØ collaboration  Calorimeter short description.
1 D.Chakraborty – VLCW'06 – 2006/07/21 PFA reconstruction with directed tree clustering Dhiman Chakraborty for the NICADD/NIU software group Vancouver.
Rare decay Opportunities at U-70 Accelerator (IHEP, Protvino) Experiment KLOD Joint Project : IHEP,Protvino JINR,Dubna INR, Moscow, RAS.
Calice Meeting Argonne Muon identification with the hadron calorimeter Nicola D’Ascenzo.
Test Beam: Calorimetric Wishes… Steve Magill, Jose Repond, Andre Turcot, Jae Yu* Jan. 10, 2003 Goals for calorimeter test beam What’s needed for EFA? Requirements.
7/13/2005The 8th ACFA Daegu, Korea 1 T.Yoshioka (ICEPP), M-C.Chang(Tohoku), K.Fujii (KEK), T.Fujikawa (Tohoku), A.Miyamoto (KEK), S.Yamashita.
09/06/06Predrag Krstonosic - CALOR061 Particle flow performance and detector optimization.
V. Pozdnyakov Direct photon and photon-jet measurement capability of the ATLAS experiment at the LHC Valery Pozdnyakov (JINR, Dubna) on behalf of the HI.
Geant4-based detector simulation activities at NICADD Guilherme Lima for the NICADD simulations group December 2003.
Durham TB R. Frey1 ECal R&D in N. America -- Test Beam Readiness/Plans Silicon-tungsten SLAC, Oregon, Brookhaven (SOB) Scintillator tiles – tungsten U.
Simulation and reconstruction of CLAS12 Electromagnetic Calorimeter in GSIM12 S. Stepanyan (JLAB), N. Dashyan (YerPhI) CLAS12 Detector workshop, February.
HCAL Leakage Studies CLIC Physics & Detector Meeting 10. November 2008 Christian Grefe CERN.
L. Pandola INFN, Gran Sasso National Laboratories
SLAC: SiD AHCAL Status and Update Ross McCoy, Andrew Myers, Andy White.
Huagen Xu IKP: T. Randriamalala, J. Ritman and T. Stockmanns
Where are we? What do we want to do next? Some thoughts
Detector Configuration for Simulation (i)
Simulations of the response of the KLOE electromagnetic
Individual Particle Reconstruction
CMS-Bijing weekly meeting
Linear Collider Simulation Tools
Plans for checking hadronic energy
Reports for highly granular hadron calorimeter using software compensation techniques Bing Liu SJTU February 25, 2019.
Dual readout calorimeter for CepC
Status of CEPC HCAL Optimization Study in Simulation LIU Bing On behalf the CEPC Calorimeter working group.
Linear Collider Simulation Tools
Steve Magill Steve Kuhlmann ANL/SLAC Motivation
LC Calorimeter Testbeam Requirements
Presentation transcript:

ECAL software development Yuri Kharlov IHEP Protvino

Goals of simulations ECAL consists of O(10 4 ) channels of 3 different lateral sizes Each channel contains O(10 2 ) samples TSR geometry contains cells of 3x3 cm 2, 6448 cells of 6x6 cm 2, 5592 cells of 12x12 cm 2 : in total cells. Each cell contains layers of Lead+Tyvek+Scintillator Total 2  10 7 volumes ECAL performance strongly depends on the lateral and longitudinal segmentation Goal 1: optimize overall detector layout Goal 2: optimize detector granularity and sampling Goal 3: simulate ECAL performance for physics signal detection

TSR geometry

Why 10 9 volumes instead of 1? Main features of any calorimeter: Energy resolution  E/E Position resolution  x Shape of a shower produced by different particles Energy resolution depends on the cell sampling Position resolution is defined as a shower gravity center  E/E and  x affects the ECAL ability to measure particle spectra ( ,  0 ) The granularity determines the detector cost As long as final granularity is still a subject to study, we use 1  1-cm 2 cells  10 9 volumes

Shower shape ECAL response to particles is a shower Electromagnetic shower involves up to 25 cells Hadronic shower may fire 1-5 cells In high-multiplicity environment showers overlap Shower shape is used in the reconstruction algorithm for overlapped shower unfolding and correct calculation of electomagnetic component of a shower Although e.m. shower shape can be parametrized, such parameterization does not include fluctuations. Hadronic showers are not parameterized at all. Only full simulation can provide correct ECAL response and thus allows to study ECAL performance

Geometry: ascii file vs C++ code Description of sizes and positions of 10 9 volumes is useless Data base with such a straightforward description will slow down simulations Coding of geometry in C++ program using profits from geometry optimization tools provided by G3 and TGeo All 10 9 volumes are described in a very optimal geometry hierarchy of 5 volumes embedded one into another Performance test: 10 9 volumes vs 10 6 slow down simulation of 1 electron just in 4 times

Parameterized geometry vs current det.geo files Any technical drawing contains just basic sizes which allows to calculae the size and position of any element (e.g. array of elements can be described by one element size, step size and the number of elements) The same numbers should be stored in DCDB or ADB for further geometry versioning User code should read the basic geometry parameters and let a user to code the geometry based on these parameters

CbmEcalv2 CbmModule CbmDetector CbmEcal CbmEcalv2 class CbmEcalv2 : public CbmEcal public: virtual void ConstructGeometry(); virtual Bool_t ProcessHits(CbmVolume* vol = 0);

CbmEcalv2::ConstructGeometry() void CbmEcalv2::ConstructGeometry() {... gGeoManager->Mixture("Polystyrene",aP,zP,dP,nP,wP,kMatPoly); gGeoManager->Medium("Scintillator", kMedScin, kMatPoly, 1, 0, 0., 10.0, 0.1, 0.1, 0.1, 0.1); gGeoManager->Volume("ECAL1", "BOX", 1, par, 3); gGeoManager->Division("ECAL1column","ECAL1",1,-1,-par[0],cellSize,0,"S"); gGeoManager->Node("ECAL1", 1, "ECAL", 0.,+yPos,0.,0,kTRUE,buf,0);... }

CbmEcalv2::ProcessHits() ECAL MC point is stored each time when some energy is deposited: (gMC->Edep() != 0) MC point: trackId cellId eLoss where cellId = iEcalBlock* iColumn* iRow;

CbmEcalv2 volume hierarchy

Volumes One cell 1  1 cm 2, 300 sampling layers

Proposals for the framework Detectors should be able to create simple geometry as well as detailed one Simple geometry can be used just a material budget for simulations of other detectors, or for fast MC Detailed geometry is needed for optimizing the internal detector structure to provide a realistic response function Coding the geometry in C++ classes is inevitable for detailed geometry to profit from geometry optimization tools, and the framework should provide tools for it Coding the geometry should be virtualized from a particular geometry description (G3, G4, TGeo, Fluka) to be independent on it Geometry parameters stored in ascii files should be simular to the dimensions of the technical drawings

Possible solution AliModule may have methods Mixture Material Medium Volume Position Divide with similar signatures as those in G3 or TGeo