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POWHEG Adaptation of the Baur Zγ Generator. Lindsey Gray University of Wisconsin at Madison Weekly Meeting 3 June, 2009. Action Items. Show plots of pythia based CMSSW analysis, scaled by appropriate factors. Resurrect and show plots from RCT Calibration Routines
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POWHEG Adaptation of the Baur Zγ Generator Lindsey Gray University of Wisconsin at Madison Weekly Meeting 3 June, 2009
Action Items • Show plots of pythia based CMSSW analysis, scaled by appropriate factors. • Resurrect and show plots from RCT Calibration Routines • Status of POWHEG adaptation of Baur’s MC Generator • Draft for Multi-boson group talk in 2 weeks! Lindsey Gray, UW Madison
Getting Back to Zγ Analysis • Original analysis had a flaw in normalization • Calculate event yield was actually too small! • To show: • Results of using production Zγ sample (Pythia 6) • Use same set of fiducial, photon id and kinematics cuts, but with proper normalization • Initial results from using Mike’s multivariate photon id Lindsey Gray, UW Madison
Summary of Signal & Background Signal Background 200pb-1 Lindsey Gray, UW Madison
Output of TMVA-based Photon ID • Fisher discriminant works properly • Good separation between signal and background • Small cross section of Zγ signal implies tight cut on Fisher output • Fisher > .2 Lindsey Gray, UW Madison
Draft of Multi-boson talk 2 weeks from now
Outline • Overview of POWHEG • Motivation & Definition • Current Results of Adapting Baur’s MC • Development Strategy & Status • Born Level Results & Comparison to Baur’s MC • Including Anomalous Couplings • Conclusions & Next Steps Lindsey Gray, UW Madison
Shower MCs & NLO Generators Shower Monte Carlo NLO MC Generator Take 2 -> n process Determine virtual and collinear corrections Divergent! Calculate full 2 -> n+1 cross section Divergent! Sum of all contributions is finite! Accurate normalizations but bad shapes at low pT • Take 2 -> n process and determine probability for no QCD radiation • Sudakov form factor • Collinear factorization • Reconstruct n+1 body process in collinear limit • Accept or reject radiation • Iterate until emission energy is below some threshold • Normalizations wrong, bad shapes at high pT Lindsey Gray, UW Madison
Combining Shower MC with NLO • It is natural to want to combine NLO calculations with Shower MCs (SMC)! • However there are issues: • Double counting • Simply interfacing an NLO generator directly to a SMC will cause the SMC to generate events the NLO generator has already produced! • Matching NLO matrix elements to Shower MC emissions • Make sure QCD emission has correct probability in hard, soft and collinear regimes! • Many solutions exist: • MC@NLO, POWHEG, CKKW, MLM Lindsey Gray, UW Madison
The POWHEG Method • POsitive Weight Hardest Event Generator • One of the many solutions to interfacing a NLO event generator with a shower monte carlo. • Independent of the Shower Monte Carlo used for hadronization • Hence independent of CMSSW • Do not allow SMC to generate radiation harder than the radiation from the POWHEG event. • As the name says, it generates events with all positive weights. • Produce unweighted events through well established methods. Lindsey Gray, UW Madison
Applying POWHEG to Baur’s MC • To implement any process using the POWHEG method you need: • The Born level phase space • A list of Born and Real subprocesses • Born squared amplitude • Real squared amplitude • Finite part of the virtual amplitude contribution • All of these are available in Baur’s Zγ cross section calculation (though not explicitly labeled!) • Plan to extract and adapt necessary pieces from Baur’s code into existing POWHEG W/Z production code Lindsey Gray, UW Madison
What’s in Baur’s MC • Baur’s MC really consists of three MCs where the results of each are summed • 1 MC for pp -> l+l-γ process to generate Born, finite virtual and collinear pieces • Soft/Collinear IR divergence is regulated by cutoffs • 1 MC for pp -> l+l-γ+jet process • “Real” process, regulated by the same cutoffs • 1 MC for pp -> l+l-jet+γ • Contribution from Z+jet events where the jet brems • Can be safely ignored if ΔRγ,jet cut is applied • 1% Effect for ΔR > .7 confirmed with Dr. Baur Lindsey Gray, UW Madison
What’s Different in POWHEG • Baur’s cutoff regulator is replaced with Catani-Seymour or FKS regulator • Physical observables must independent of the regulator chosen • Collinear and Real contributions will change, total and differential cross sections should be unaffected • Collinear contribution ~ to Born level result • Just “paste” Born level Zγ result into POWHEG’s collinear contribution calculation • Baur’s code uses narrow width approximation, POWHEG code has finite Z width Lindsey Gray, UW Madison
Current Status of Development • All necessary portions of Baur’s NLO calculation have been extracted • Testing is in progress: • Born matrix element result is fully tested • 2.5% normalization difference relative to Baur LO • Shapes match • Results to be shown • Collinear & Virtual corrections implemented • Currently debugging & testing • Real matrix element result is implemented • Currently debugging & testing Lindsey Gray, UW Madison
Shape Comparison: Diboson Mass & Lepton PT • All plots are area normalized. • 2.5% normalization difference • All Born level shapes agree! • With the exception of the diboson mass. • Known effect since Baur’s code uses narrow width approx. and POWHEG code has finite Z width. • Using narrow width approx. in POWHEG code doesn’t fix 2.5% normalization difference. Baur POWHEG Lindsey Gray, UW Madison
Shape Comparison:Photon PT, Lepton η & Photon η Baur POWHEG Lindsey Gray, UW Madison
Shape Comparison:Photon PT + Anomalous Coupling • ACs are automatically included in the routines from Baur’s code. • Scaling is the same between Baur MC and POWHEG. Lindsey Gray, UW Madison
Conclusions and Next Steps • All of the necessary components for NLO Zγ cross section calculation are in place in POWHEG • What remains now is extensive testing, debugging and comparison to Baur’s NLO code • Determine source of 2.5% normalization difference • Once NLO calculation is fully ported and tested • Test event generation • Compare unweighted event kinematics distributions to NLO differential cross sections • Run trials interfacing POWHEG lhe-event file to Pythia, Herwig, et al. and cross check results. Lindsey Gray, UW Madison