11 November 2010 Rudi Frühwirth Physics algorithms and data analysis HEPHY Evaluation.
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Transcript of 11 November 2010 Rudi Frühwirth Physics algorithms and data analysis HEPHY Evaluation.
11 November 2010
Rudi Frühwirth
Physics algorithmsand data analysis
HEPHY Evaluation
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Physics algorithmsand data analysis
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Mission
► Participation in projects, with focus on– Event reconstruction software
Pattern recognition for track and vertex findingRobust and adaptive estimation in track and vertex fitting
– Detector related softwareGeometrical alignment, detector design and optimization
– Physics analysis software and statistical consulting for analysis groups
► Generic developments– Methods and software tools that are of general interest
to particle physics experiments
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Department members
• Rudi Frühwirth (senior scientist) B,C, I
• Jakob Lettenbichler (diploma student) B
• Winni Mitaroff (senior scientist) B,I
• Moritz Nadler (doctoral student) B
• Manfred Valentan (former diploma student) I
• Wolfgang Waltenberger (junior scientist) C
• Edmund Widl (postdoc) C
B…Belle/Belle II, C…CMS, I…ILD
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Past activities
► DELPHI experiment (LEP)– Pattern recognition and geometrical alignment
for the forward drift chambers built at HEPHY ►
– Track fit in the forward region
– Vertex fit
► CMS experiment (LHC)– Adaptive track fit and multi-track fit
– Electron track fit with Gaussian-sum filter
– Linear and adaptive vertex fit ►
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Tracks
Outlying track
Adaptive fitter
Linear fitter
Linear and adaptive vertex fitter
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Past activities
► Generic developments– Fast track fitting on the Riemann sphere– Mixture approximations of electron
bremsstrahlung and multiple scattering ►– Robust mode estimation– Analytical formulas for track resolution
► Generic Software– LicToy: Fast simulation and reconstruction tool– JDOT: Detector optimization package– RAVE: Vertex reconstruction toolkit
Solid line – true pdf, dashed line – semi-Gaussian mixture, dotted line – Gaussian mixture, dashed-dotted line – single Gaussian (Highland)
Mixture models of multiple scattering
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Current activities
► CMS tracker alignment– Kalman alignment algorithm
– Validated on collision data
– Two-track constraints being adapted to other CMS alignment algorithms ►
► CMS physics analysis– Semi-leptonic SUSY search and OSETs
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Current activities
Effect of alignment on momentum resolution, simulated data
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Current activities
► Belle II tracking– Contribution to the Technical Design Report– Track finding in the Silicon Vertex Detector– Precision track fitting in the Silicon Vertex
Detector for low momentum tracks– Methods for determination of the material
distribution
► Belle II vertexing– Vertex toolkit (RAVE) to be introduced into the
new framework
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Current activities
► ILD tracking– Detector studies with LicToy tool completed,
contribution to Letter of Intent
– Responsibility for the forward track fit
– EU funds available for a student
► ILD vertexing– Vertex toolkit (RAVE) ported to framework
– Validated sucessfully
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Recently finished theses
• E. Widl (Vienna UT, PhD)Global alignment of the CMS tracker (2008)Victor Hess-Prize 2009 of the Austrian Physical Society for the best thesis in nuclear and particle physics ►
• S. Federmann (Univ. Vienna, Diploma)Optimization of the Multi-Vertex Fitter for CMS Inner Tracker (2009)
• M. Valentan (Vienna UT, Diploma)Tracking detector optimization for collider experiments with fast simulation and by analytical methods (2009)
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Theses in progress
• M. Nadler (Vienna UT, PhD)Precision track fit in the Belle II SVD (working title)
• J. Lettenbichler (Univ. Vienna, Diploma)Track finding in the Belle II SVD (working title)
Lectures
• R. Frühwirth (Vienna UT):
Statistik (Lecture, 2h, summer term)
Statistische Methoden der Datenanalyse (Lecture, 2h, winter term)
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CERN School of Computing
• 2003: Organization of the school in Krems (AT)• Since 2004: Convener for Physics Computing• Since 2004: Lecturer “Introduction into Physics
Computing”• Since 2007: Chairman of the Advisory
Committee
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External Collaborations
► Track and vertex reconstruction– A. Strandlie (Gjøvik University College, Norway)
– Adaptive filters in track and vertex estimation
– Long and fruitful collaboration
– Recent summary in Rev. Mod. Phys. 82 (2010) 1419 ►
► Clustering of proteomics data– S. Pyne, D. Mani (Broad Institute of MIT & Harvard, USA)
– Adapt vertex finder to 2D-clustering of peptides
– Gives better cluster quality, faster than current method by at least an order of magnitude
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External Collaborations
► Markov chain Monte Carlo for generalized linear models– S. Frühwirth-Schnatter (JKU Linz, Austria)– Mixture models for various distributions
► Variational Bayes methods– M. Wand (University of Wollongong, Australia)– Mixture models of intractable distributions
► Imaging of ultra-cold atoms– J. Schmiedmayer (Institute of Atomic and Subatomic
Physics, Vienna UT)– Improve statistical analysis of CCD images of ultra-cold
atoms
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Journal papers 2005-2010
• Group-specific papers in refereed journals– Nucl. Instrum. Meth. A: 10
– J. Instrumentation: 2
– J. Phys. G: 2
– IEEE Trans. Nucl. Sci.: 2
– Comput. Stat. Data Anal.: 2
– Comput. Phys. Commun: 1
– Austrian J. of Statistics: 1
– Rev. Mod. Phys.: 1
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Book contributions
• R. Frühwirth, A. Strandlie: “Pattern recognition and reconstruction”In: Landolt-Börnstein New Series I/21B1, Springer, to appear in 2011
• M. Krammer, W. Mitaroff:“Tracking Detectors”In: Handbook of Particle Detection and Imaging, Springer, to appear in 2011
• S. Frühwirth-Schnatter, R. Frühwirth: “Data Augmentation and MCMC for Binary and Multinomial Logit Models”In: Statistical Modelling and Regression Structures, Physica Verlag, 2010
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Conference Contributions 2005 – 2010
• Advanced Computing and Analysis Techniques: 2010, 2005
• Computing in High Energy Physics:2009, 2008, 2007, 2006
• IEEE Nuclear Science Symposium: 2008, 2006• Vienna Conference on Instrumentation: 2007• Various smaller conferences and workshops• Published in respective Proceedings and
J. Phys. Conf. Ser.
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Outlook
► CMS– Alignment: maintenance of Kalman Alignment
Algorithm, further development of two-track constraint formalism
– Vertex fit: maintenance, further tuning with collision data
– Electron fit: maintenance
– Physics analysis: continue participation in SUSY searches and OSETs, technical support for quarkonia analysis
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Outlook
► Belle II– High-precision tracking:
start implementation phase now, in collaboration with Munich and Karlsruhe
– Track finding in the Silicon Vertex Detector: continue exploration phase
► ILD – Forward Tracking:
ready for implementation phase
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Thank you!
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Backup slides
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Publications 2010
• A. Strandlie, R. Frühwirth: Track and vertex reconstruction: From classical to adaptive methods.Review of Modern Physics 82, 1419-1458
• S. Frühwirth-Schnatter, R. Frühwirth: Data Augmentation and MCMC for Binary and Multinomial Logit Models.In: Kneib, Thomas; Tutz, Gerhard (Eds.), Statistical Modelling and Regression Structures, Physica Verlag, Heidelberg, 2010.
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Conferences, Workshops and Seminars
• ACAT 2010 (Jaipur): invited talk (RF)
• Workshop for Future Challenges in Tracking and Trigger Concepts (GSI): invited talk (RF)
• Workshop on Topologies for Early LHC Searches (SLAC): 2 CMS talks (WW)
• MPI Munich Kolloquium: invited seminar (RF)
• Belle II Tracking Workshop (Munich): 3 talks (MN,WW,RF)
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CMS Global Alignment
Hit residuals from three track-based algorithms: HIP (solid), Millepede (dashed), and Kalman alignment algorithm (dotted).
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Material Estimation
► Optimization of material description– Started beginning 2010, part of PhD thesis (MN)
– Estimate amount and possibly location of material along a track
– Similar to alignment, but mathematically more challenging
– First results with simulated tracks available
– Best case scenario (perfect alignment, perfect knowledge of resolution, perfect track finding)
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Material Estimation
► Methods– Global optimization of probability distributions
• Slow, poor scalability
– Estimation of energy loss and multiple scattering distributions in regression model • Limited sensitivity to material
– Estimation of energy loss and multiple scattering distributions by forward/backward Kalman filter; material estimation by maximum likelihood fit • Maximal sensitivity
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Evolution of χ2 probability distributions (energy loss only)
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Evolution of χ2 probability distributions (energy loss+multiple scattering)
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Development of χ2 probabilities (energy loss only)
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Development of χ2 probabilities (MS only)