Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 1 Energy Method Selections Data Set: All Gamma (GR-HEAD1.615) Parametric Tracker Last Layer Profile 4 Methods.

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Presentation transcript:

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 1 Energy Method Selections Data Set: All Gamma (GR-HEAD1.615) Parametric Tracker Last Layer Profile 4 Methods 3 Only cover a part of Glast Phase Space Each describes its "quality" using different variables How to choose which to use for each event?

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 2 Method% Computed% Best Est. Parametric Profile Last Layer Tracker Only Parametric Available: 37.7% This tends to be the Local Land Fill (City Dump!) Unfortunately there are too many events here to simply throw out. Begin comparison by determining the Correction method that results in the energy closest to the MC Truth Results summarized in the following table:

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 3 Break into classes according to which Energy Corr. methods were calculated: 1) Param - Parametric only 2) Profile - Profile & Parametric 3) Tracker – Tracker & Parametric 4) Last Layer – Last Layer & Parametric 5) ProfLL – Profile, Last Layer & Param. 6) LLTracker – Last Layer, Tracker & Param. Perform a CT based selection independently for each catagory: 5 CTs Combine CTs to compute a BestEnergy for the event. MC Truth CT Prediction Intercomparison Method: For each event determine the Energy Correction Method that gives an energy closest to the MC Truth. Not all Methods report an energy for all events Then build 3 more CTs Clipped the tails....

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 4 Intercomparison & Best Energy Determination MeV MeV GeV GeV Prob: [0 -.25] [ ] [ ] [.75 – 1.00] Break Down by Energy & Prob Resolutions for Different Prob. Cuts "Best" Probability Distribution

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 5 Intercomparison Method Conclusions 1) The best energy resolution is achieved by combining all the results 2) The Last Layer / Tracker methods have the smallest overshoot problems - Cover the smallest phase-space - Based on observed correlations 3) Profile Fit demonstrates that a detailed fit to the 3D energy depositions works and accomplishes in a single approach both inter tower gaps and leakage corrections. 4) Parametric method provides a floor from which to improve. - Assumes a factorized model of inter tower gaps and leakage correction. 5) Intercomparison Method suffers from: - Irregularity of which methods are available event-to-event - Each Method has its own self description indicating how well it did ( e.g. Profile has a  2, Last Layer has a relative energy error, etc. ) - The above leads to ambiguities and complexity... total of 8 CT's!

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 6 Alternative: Direct Comparison Against an External Resolution Model Common Variables Second Method: Compare each Energy Correction Method against a common External model. Select Method with the highest probability in each event for both the energy & final probability of being "Good" Resolution Model: Parametric Rep. of Data

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 7 Added Variables: CalCfpChiSq CalCfpEffRLn Added Variables: CalLllEneErr Last Layer CT Profile CT Indicates Added Variables The Resulting 4 CTs

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 8 Added Variables: CalTklEneErr Added Variables: CalLeakCorr CalEdgeCorr CalTotalCorr CalCsIRLn CalGapFraction CalDeadTotRat CalDeltaT Parametric CT Tracker CT

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 9 E3: Balanced CTs - 2  on  = /(log(E)) MeV MeV GeV GeV Prob: [0 -.25] [ ] [ ] [.75 – 1.00] Break Down by Energy & ProbResolutions for Different Prob. Cuts "Best" Probability Distribution

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 10 E4: Unbalanced CTs - 2  on  = /(log(E)) 3

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 11 E5: Unbalanced CTs – 1.5  on  = /(log(E)) 3

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 12 Parametric Only Best (Combined) Parametric Only Best (Combined) E4: Unbalanced CTs - 2  on  = /(log(E)) 3 Hi E Tail greatly attenuated with No Cuts!

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 13 Eff. =.903 Eff. =.826 Prob. >.10 Prob. >.20

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 14 Eff. =.703 Prob. >.40 Conclusions The Direct Comparison Method Offers - Simplicity - Avoids the Ambiguities of the Intercomparison Method - Results in a smooth loss in efficiency as the Prob. Cut in increased - Overall – seems to be the Method of Choice (for now!)

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 15 E4: Unbalanced CTs - 2  on  = /(log(E)) 3 Data Set: AG1617-mod

Bill Atwood, SCIPP/UCSC, August, 2005 GLAST 16 And..... Previously Observed Fall-off at Hi Energy is GONE!!!! Conclusion: AG1617-mod results very similar to those gotten with AG1615 cos(  ) < -.9 Layers 2-5 Layers 6-9 Layers Layers 14-17