Pattern Recognition in OPERA Tracking A.Chukanov, S.Dmitrievsky, Yu.Gornushkin OPERA collaboration meeting, Mizunami, Japan, 20-22 of January 2009 JINR,

Slides:



Advertisements
Similar presentations
QR Code Recognition Based On Image Processing
Advertisements

Efforts to Improve the Reconstruction of Non-Prompt Tracks with the SiD Lori Stevens UCSC ILC Simulation Reconstruction Meeting May 15, 2007 Includes contributions.
Computing EVO meeting, January 15 th 2013 Status of the Tracking Code Gianluigi Boca, Pavia University.
Giuseppe Roselli (CMS-RPC) Università degli Studi di Bari – INFN RPC Efficiency with Track Reconstruction Giuseppe Roselli.
A New Approach to Cluster Finding and Hit Reconstruction in Cathode Pad Chambers and its Development for the Forward Muon Spectrometer of ALICE A.Zinchenko,
12 th CBM Collaboration Meeting October 13-18, 2008, JINR, Dubna A. Zinchenko 1 (L.Naumann 2, D.Peshekhonov 1, V.Peshekhonov 1 ) 1 VBLHEP, JINR, Dubna.
MICE TPG RECONSTRUCTION Tracking efficiency Olena Voloshyn Geneva University.
Pattern Recognition in OPERA Tracking A.Chukanov, S.Dmitrievsky, Yu.Gornushkin OPERA collaboration meeting, Ankara, Turkey, 1-4 of April 2009 JINR, Dubna.
Localization of Piled Boxes by Means of the Hough Transform Dimitrios Katsoulas Institute for Pattern Recognition and Image Processing University of Freiburg.
Muon Identification Antoine Cazes Laboratoire de l’ Accelerateur Lineaire OPERA Collaboration Meeting in Frascatti Physics coordination meeting. October.
Emulsion scanning: present status and plans for the coming run Giovanni De Lellis.
Off-axis Simulations Peter Litchfield, Minnesota  What has been simulated?  Will the experiment work?  Can we choose a technology based on simulations?
Sci Fi Simulation Status Malcolm Ellis MICE Meeting Osaka, 2 nd August 2004.
Robust estimation Problem: we want to determine the displacement (u,v) between pairs of images. We are given 100 points with a correlation score computed.
Simulation of a Magnetised Scintillating Detector for the Neutrino Factory Malcolm Ellis & Alan Bross Fermilab International Scoping Study Meeting KEK,
October 8, 2013Computer Vision Lecture 11: The Hough Transform 1 Fitting Curve Models to Edges Most contours can be well described by combining several.
Pion test beam from KEK: momentum studies Data provided by Toho group: 2512 beam tracks D. Duchesneau April 27 th 2011 Track  x Track  y Base track positions.
Measurement of through-going particle momentum by means of Multiple Scattering with the T600 TPC Talk given by Antonio Jesús Melgarejo (Universidad de.
October 14, 2014Computer Vision Lecture 11: Image Segmentation I 1Contours How should we represent contours? A good contour representation should meet.
Tracking within hadronic showers in the SDHCAL Imad Laktineh.
1 Tracking Reconstruction Norman A. Graf SLAC July 19, 2006.
Tracking at LHCb Introduction: Tracking Performance at LHCb Kalman Filter Technique Speed Optimization Status & Plans.
Intelligent Vision Systems ENT 496 Object Shape Identification and Representation Hema C.R. Lecture 7.
Track Reconstruction: the trf & ftf toolkits Norman Graf (SLAC) ILD Software Meeting, DESY July 6, 2010.
Hough Transform : A preliminary study Indranil Das HEP Devn., SINP.
Workshop on B/Tau Physics, Helsinki V. Karim ä ki, HIP 1 Software Alignment of the CMS Tracker V. Karimäki / HIP V. Karimäki / HIP Workshop.
OPERA Experiment, Brick Finding Program A. Chukanov Joint Institute for Nuclear Research ISU, 12 th February, 2007.
STS track recognition by 3D track-following method Gennady Ososkov, A.Airiyan, A.Lebedev, S.Lebedev, E.Litvinenko Laboratory of Information Technologies.
TRD and Global tracking Andrey Lebedev GSI, Darmstadt and LIT JINR, Dubna Gennady Ososkov LIT JINR, Dubna X CBM collaboration meeting Dresden, 27 September.
STAR Sti, main features V. Perevoztchikov Brookhaven National Laboratory,USA.
The Pattern Recognition issue for the Mu2e experiment Giovanni F. Tassielli - G. Marconi University.
Track reconstruction and pattern recognition V.V. Ivanov Laboratory of Information Technologies Joint Institute for Nuclear Research,
Updates on the P0D reconstruction
STAR STAR VMC tracker V. Perevoztchikov Brookhaven National Laboratory,USA.
What is in my contribution area Nick Sinev, University of Oregon.
Matthew Reid 1 st Year PhD University of Warwick 1.
V0 analytical selection Marian Ivanov, Alexander Kalweit.
Ring Recognition and Electron Identification in the RICH detector of the CBM Experiment at FAIR Semeon Lebedev GSI, Darmstadt, Germany and LIT JINR, Dubna,
Brick Finding Package – Status Report A. Chukanov, S. Dmitrievsky, Yu. Gornushkin Joint Institute for Nuclear Research, Dubna LNGS 11 th October, 2006.
Methods for fast reconstruction of events Ivan Kisel Kirchhoff-Institut für Physik, Uni-Heidelberg FutureDAQ Workshop, München March 25-26, 2004 KIP.
Fast Tracking of Strip and MAPS Detectors Joachim Gläß Computer Engineering, University of Mannheim Target application is trigger  1. do it fast  2.
Track reconstruction in TRD and MUCH Andrey Lebedev Andrey Lebedev GSI, Darmstadt and LIT JINR, Dubna Gennady Ososkov Gennady Ososkov LIT JINR, Dubna.
Global Tracking for CBM Andrey Lebedev 1,2 Ivan Kisel 1 Gennady Ososkov 2 1 GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany 2 Laboratory.
Adam Blake, June 9 th Results Quick Review Look at Some Data In Depth Look at One Anomalous Event Conclusion.
OPERA Experiment, Brick Finding Program A. Chukanov Joint Institute for Nuclear Research Dubna, 25 th January, 2007.
Status of OpRec Antoine Cazes Laboratoire de l’ Accelerateur Lineaire OPERA Collaboration Meeting in Frascatti Physics coordination meeting. October 28.
Giuseppe Ruggiero CERN Straw Chamber WG meeting 07/02/2011 Spectrometer Reconstruction: Pattern recognition and Efficiency 07/02/ G.Ruggiero - Spectrometer.
Localization of a Neutrino Interaction Vertex in the OPERA Experiment S.Dmitrievsky, Yu.Gornushkin, G.Ososkov (JINR, Dubna) Gran Sasso, Italy, November.
BESIII offline software group Status of BESIII Event Reconstruction System.
Emulsion Test Beam first results Annarita Buonaura, Valeri Tioukov On behalf of Napoli emulsion group This activity was supported by AIDA2020.
Object-Oriented Track Reconstruction in the PHENIX Detector at RHIC Outline The PHENIX Detector Tracking in PHENIX Overview Algorithms Object-Oriented.
Pattern recognition with the triplet method Fabrizio Cei INFN & University of Pisa MEG Meeting, Hakata October /10/20131 Fabrizio Cei.
Mitglied der Helmholtz-Gemeinschaft Hit Reconstruction for the Luminosity Monitor March 3 rd 2009 | T. Randriamalala, J. Ritman and T. Stockmanns.
Track Reconstruction in MUCH and TRD Andrey Lebedev 1,2 Gennady Ososkov 2 1 Gesellschaft für Schwerionenforschung, Darmstadt, Germany 2 Laboratory of Information.
Part 5 pattern recognition. ● track pattern recognition: associate hits that belong to one particle nature or GEANT track finding + fitting ● will discuss.
Torino, June 15 th, 2009 Status of the Pattern Recognition with the Hough transform and the STT system alone. Gianluigi Boca 1.
STT pattern recognition improvements since last December meeting and
Tracking results from Au+Au test Beam
Status of the Offline Pattern Recognition Code GSI, December 10th 2012
Localization of a Neutrino Interaction Vertex in the OPERA Experiment
Track Finding.
Tracking Pattern Recognition
HARPO Analysis.
GLAST Large Area Telescope:
Status of the Offline Pattern Recognition Code Goa, March 12th 2013
Status and Plans of the Belle-II Tracking Software Martin Heck
Fitting Curve Models to Edges
Individual Particle Reconstruction
Silicon Tracking with GENFIT
Reconstruction and calibration strategies for the LHCb RICH detector
Presentation transcript:

Pattern Recognition in OPERA Tracking A.Chukanov, S.Dmitrievsky, Yu.Gornushkin OPERA collaboration meeting, Mizunami, Japan, of January 2009 JINR, Dubna

Outline Problem of pattern recognition in standard OPERA tracking Method of Hough transform for straight track recognition Simple tracing method for curved track reconstruction Method of spanning tree tracing for curved track candidate selection Status of proposed pattern recognition package.

Standard track Mushower extrap Pictures are taken from Dario’s report of 29/10/2008 Problem of standard OPERA tracking originates in fact from incorrect pattern recognition. Mushower procedure doesn’t eliminate the reason of the problem but just serves as a patch for tracking algorithm. It simply makes a linear extrapolation of found track direction through a shower without taking into account hit positions in the beginning part of an event.

Hence the OPERA pattern recognition needs to be improved. The effective pattern recognition method widely used in HEP experiments (e.g. MINOS, ALICE, CBM, etc) is Hough transform (HT).

For each of given point iteration through different angles gives us corresponding values of. Points are saved in a 2D histogram. If there are some straight tracks (or parts of tracks) in an event there should exist distinct pikes in the histogram. By determining of centers of gravity of that pikes it is possible to reconstruct parameters of track lines by the following formulas: Hough transform uses representation of a line in normal form: This equation specifies a line passing through point. That line is perpendicular to the line drawn from the origin to point in polar space. It can be shown that in case of points belonging to the same line and are constants. Hough Transform for Straight Track Recognition

Example of HT Track Recognition: event and give track parameters: Proposed HT track finding Found OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation.

Example of HT Track Recognition: event OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation. and give track parameters: Proposed HT track finding Found

Example of HT Track Recognition: event and give track parameters: Proposed HT track finding Found OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation.

Example of HT Track Recognition: event and give track parameters: Proposed HT track finding Found OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation.

Example of HT Track Recognition: event and give track parameters: Proposed HT track finding Found OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation.

As shown in the given examples the muon track is easily distinguished by a pike in HT histogram. Moreover, the result of HT recognition coincides with Mushower extrapolation while Hough transform can be performed just at the stage of pattern recognition.

Simple Tracing Method for Curved Track Finding After the initial straight part of a track is determined by a Hough transform in the beginning of an event it is possible to find the rest tail part of the track with help of proposed tracing method (which in fact is a simplified kind of a Kalman filter): 1) Finding a search direction Linear fit on 7 last found hits of a track; 2) Setting of search angle range Its own angle range for each detector is used taking into account its geometry and uncertainties. 3) Finding hits in the following detector planes inside the search angle range Inefficiency of detectors (2 empty TT planes, 8 empty RPC planes) is taken into account. If there are more than 1 candidates to track hits only the hit accepted that is the nearest to the search direction. 4) Including found hit to the TrackElement and iterating steps 1-3 for next planes or stop procedure in case of no hits found

Example of Forward Tracing Procedure Event TT1TT2 RPC1 RPC2 Y, cm Z, cm Simple tracing along the beam direction works easily (as shown on the picture) because there are no background hits far away of the vertex.

Backward Tracing with Background When particle’s momentum is small the track can be curved already in its beginning part. The curved tracks are difficult for HT reconstruction and even the simple tracing method can fail within the shower environment. On the picture below such a specific case is shown. Y, cm Z, cm T T planes Line found by a Hough transform wrong hits track hits There are no more sequential hits in the search area Event

To solve such a problem it is useful to iterate on all possible chains of the hits to select among them the best chain. It can be done with help of method of spanning tree tracing. It finds different reliable track trajectories and than consider the longest and most smooth chain of hits to be the best track candidate. Spanning Tree Tracing Method for Track Selection Event Y, cm Z, cm T T planes As a result the longest and most smooth track will be selected

Resolution of Tracking Preliminary Preliminary results of tracking resolution for XZ and YZ projections have been obtained with help of tracks found in CS. is comparable with standard tracking resolution.

Status of Proposed Pattern Recognition Package 1)Event cleaning (removing of CT and isolated hits): done 2) Method of Hough Transform to find straight part of a track: done 3) Tracing method to find curved tail part of a track: under test 4) Method of Spanning Tree Tracing to select the best track candidate within a shower: not yet in OPERA release