logging in or signing up DC1 Talk Brainy007 Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: Embed: Flash iPad Dynamic Copy Does not support media & animations Automatically changes to Flash or non-Flash embed WordPress Embed Customize Embed URL: Copy Thumbnail: Copy The presentation is successfully added In Your Favorites. Views: 299 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: June 18, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript DC1 Instrument Response: DC1 Instrument Response Agenda Where are we? V3R3P7 Classification Trees Covariance Scaled PSF Pair Energies Backgrounds Slide2: A Brief History of Resolution andamp; Rejection Preparing for DC1 is a LARGE TASK - Not likely to get right the 1st, or the 2nd, or the 3rd, or.... time! 1st Time: April-May Discover Mult-scattering in G4 'too good to believe!' Took till end of June to fix! 2nd Time: July (SAS Workshop) OOPS! The ACD geometry! 3rd Time: July-August Where did all the Run Numbers go? 4th Time: August Will Bill never stop changing variables - well at least he shouldn't make so many coding errors! Steve's variables added. 5th Time: August-September Data of the day! But it's certainly not 'The rest of the story!' 6th Time: .... IS A CHARM! Slide3: A Brief History Continues! 6th Time: NOT CHARMED! September: ToT's found to be effective at removing range-outs! Code added to explore this handle on Backgrounds 7th Time: October- November ACD ribbons added to seal up ACD cracks. Code added to analyze Ribbons. 5M All-Gammas produced over [18 MeV, 180 GeV] andamp; 2p str. 8th Time: November-December Ribbon andamp; Tile Geometry discoveries! 9th Time: December 3 Background Data delivery: 160M+ BGEs. Note: just the BGEs have been run. All-Gammas awaiting. Credit goes to Heather and Berrie. THANK YOU! Slide4: NoCal: andlt; 2 r.l. or andlt; 5 MeV LowCal: andlt; 350 MeV MedCal: andlt; 3500 MeV HighCal: andgt; 3500 MeV CAL Energy Def's and Good/Bad Breakdown Recall: 'Good': Energy CTs Slide5: Energy CT's Probability Evaluation Sci. Req. Cut for V3R3P7 (.2) All-Gamma Eff.: 92% Energy Tails: andlt; 10% All-Gamma Eff.: 78% Energy Tails andlt; 3% Slide6: DC1 Energy Post Good-Energy Cut: IMgoodCalProb andgt; .2 Energy s vs Energy Energy s vs cos(q) Meas. Energy vs M.C. Energy Meas. Phase Space Energy vs cos(q) Slide7: Rome: Thin PSF's - Integrated over FoV 4 Combinations of Cuts (CORE/Pred) Cuts: 1/1 Ratio 95/68 andgt; 3 Meets SR Events Eff.: 94.5% Cuts: 2/1 Cuts: 3/2 Events Eff.: 52.3% Cuts: 3/4 Events Eff.: 19.1% Slide8: DC1: Thin PSF's - Integrated over FoV 4 Combinations of Cuts (1-CORE/4-Pred) Cuts: 2/1 Cuts: 2/2 Cuts: 2/3 Cuts: 2/4 Slide9: Definitions: Where all the variables come from the Merit-ntuple. (See my covariance ppt for details on Tkr1ThetaErr and Tkr1PhiErr - these are derived from the covariance matrix elements, event-by-event) Covariance Scaled PSF's A bit of math then shows that: and (from Covariance.ppt presentation to Analysis Group, July, 2003) Slide10: 18 andlt; E andlt; 56 56 andlt; E andlt; 180 180 andlt; E andlt; 560 560 andlt; E andlt; 1800 1800 andlt; E andlt; 5600 Comment: Works well except in regions where energies fed to Kalman Filter are inaccurate. Specifically below 50 MeV and above 10 GeV 5600 andlt; E andlt; 18000 18000 andlt; E andlt; 56000 56000 andlt; E andlt; 180000 Scaled PSFs: Energy Dependence Slide11: -1andlt;cos(q)andlt;-.8 -.8andlt;cos(q)andlt;-.6 -.6andlt;cos(q)andlt;-.4 -.4andlt;cos(q)andlt;-.2 McEnergy andlt; 10000 MeV Scaled PSFs: Angle Dependence On Axis Edge of FoV Slide12: 1) Scale Factors adj. to 2.38 andamp; 3.36 Thin /Thick respectively 2) IMcoreProb andgt; .2 andamp; IMpsfErrPred andlt; 3. (SR cuts) Universal PSF Curve??? 3) Energy cut: .5 andlt;Tkr1ConEne/EvtEnergySumOpt andlt; 1. Note: This cuts out almost 1/2 the data !!!! (44.4%) Slide13: Pair Energies: The Missing Half Only Valid Region: [.5, 1.) Optimization done using: Slide14: Pair Energies: The Missing Half (2) Optimization done using andamp; Consraint to 'QED' Slide15: Backgrounds: A First Look Input: - 27 BGE Events Files - pruned - 168 MB/File 4.5 GB Total - 161.5 M BGE Generated Prune Step: AcdActiveDist andlt; -20 andamp; AcdRibbonActDist andlt; -20 OR Tkr1SSDVeto andgt; 2 Reduces BGE sample by 3.7X. This used SSD Tracking layers as 'back-up' Vetos. Tkr1SSDVeto Definition: # of live SSD back along trajectory from start of First Track to ACD. Adding Trk1SSDVeto saves 1/2 the killed g's allowing ~ +15% BGEs. Slide16: Yellow/Orange Bins: Cos(Mc-Theta) -1 to 1. All Gamma Sample only over cos(q) andlt; 0. This is close to the irreducible limit from conversions in the ACD andamp; Blanket AND it's ~ flat in energy. Events Lost Events lost due to Global Veto Cut 7.6% AG's Lost andamp; 73% BGE's 4.8% 6.1% ~ 78% BGE's get killed on axis Slide17: CT Pruner Step Event Sample much too large (410 Hz Orbit Average Rate) First allow only !NoCal Events: 3.7x BGE Reduction (107 Hz) Apply a CT based secondary pruner build on Reconstruction Primatives. 55 Hz 97% Slide18: Good Cal Energy andamp; Minimal PSF Cut Good Cal Energy ( Prob.GoodCal andgt; .2): Remaining Rate: 23 Hz All-Gamma Efficiency: 91.5% (Total so far: 82%) Efficiency vs Energy Cutting on PSF(CORE) (Kills PSF Tails - Prob. andgt; .2): Remaining 13.2 Hz All-Gamma Efficiency: 88% (Total so far: 73%) - 2.2 m2 - str. Efficiency vs Energy Slide19: Final CT Background Tree Processing Good Cal Energy ( Prob.GoodGam andgt; .5): Remaining Rate: 1.3 Hz All-Gamma Efficiency: 87.4% (Total so far: 63.4%) - 1.93 m2 - str. Now the 3 Problem classes are clear! Slide20: Conclusions and Future Work 1) We're NOT THERE YET! Stay tuned - for the Rest of the Story. 2) V3R3P7 CTs are in production version of GLAST Sim 3) An event-by-event PSF analysis seems to be achievable PROVIDED.... 4) We straighten out the energies used in the Kalman Fit. 5) Backgrounds - First look at statistically useable event samples. - Need to back the filtering up-stream to better manage local resources! GOAL: To have a Background Analysis in hand by DC1 Close-Out You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.