Presentation is loading. Please wait.

Presentation is loading. Please wait.

Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 1 Back Ground Rejection Status for DC2 a la Ins. Miner Analysis.

Published by Modified over 9 years ago

Similar presentations

Presentation on theme: "Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 1 Back Ground Rejection Status for DC2 a la Ins. Miner Analysis."— Presentation transcript:

1 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 1 Back Ground Rejection Status for DC2 a la Ins. Miner Analysis

2 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 2 First Look at glast-ts production 3-Oct-2005 Series 1: 409160 in tuple / 123556 after RF (only FilterStatus _HI == 0 used by TB) (This series does not have the single tile energy vars) after Act.Dist&SSDVeto: 82306 after GoodEnergyProb >.1: 81674 Series 2: 408151 in tuple / 123120 after RF after Act.Dist&SSDVeto: 82440 after GoodEnergyProb >.1: 81795 Series 3: 409098 in tuple / 123110 after RF after Act.Dist&SSDVeto: 82349 after GoodEnergyProb >.1: 81746 Each series equals.01 days or ~ 864 sec. on orbit with 744 per series live time due to the SAA – the 3 together represent 2232 sec. The following is from Toby's e-mail dated 4-Oct-05 5:33 pm Series incoming triggers downlink 1 38191926 6100518 409281 2 38053681 6078677 409415 3 38130276 6093686 409221 4 37845955 6054390 406189 total 152221838 24327271 1634106 Rates 8177 Hz 549 Hz Note: that the numbers I see are a little different in the incoming ntuples – Toby says this is due to him taking numbers from the logs rather then the tuples and failed jobs don't get counted properly. Total live time = 2976 sec. for the 4 series

3 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 3 Vtx Topologies, THICK Radiators, CalEnergyRaw < 350 MeV (Note I'm trying breaking the lowest energy bin into THICK & THIN radiators at Steve's suggestion) Prefilter: Exclude AcdUpperTileCount > 0 | AcdLowerTileCount > 1 | AcdRibbonActDist > -1999 where UpperTileCount = Top + 0 + 1 + 2 and LowerTileCount = 3 By Varying the # of AGs used to train the CT, the relative efficiency of the selection of Bkg and AGs changes. These are for Prob(  ) >.50 The nominal rate for Bkg. in each channel must be kept to <.03 Hz 100 200 300 400 500 700 1000 #AGs as indicated 1547 Bkg. Events By changing the number of AGs - its equivalent (? similiar at least) to weighting the events – except for the statistical fluctuations.

4 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 4 500 AGs  Bkg All397892 Pr >.525857 Eff.65.064 BestEnergy > 100 MeV 300 AGs  Bkg All249892 Pr >.514439 Eff.58.044 BestEnergy > 100 MeV 1000 AGs  Bkg All812892 Pr >.5721150 Eff.89.168 BestEnergy > 100 MeV This is what the CT vars. and probs. look for 3 different mixes of AGs

5 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 5 Try Training CTs using BestEnergy > 100 MeV PreFilter as before  Bkg All200892 Pr >.59836 Eff.49.040 This is marginally worse... so I will inculded all events to train CTs  Bkg All400892 Pr >.528963 Eff.72.071 The event mix changes with cos(  ) as well. We'll probably de-select on events near the edge of the FoV (e.g. cos(  ) < -.3 rather going out to cos(  ) < -.2) PreFilter as before cos(  ) < -.3 BestEnergy > 100 MeV No cut case Prob. >.5 AG eff = 129/235 =.54 Bkg. eff = 25/792 =.03 CT Variables and Prob for Vtx, Thick, < 350 MeV

6 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 6 PreFilter as before VTX, THIN, CalEnergyRaw < 350 MeV, cos(  ) < -.3 This is much worse in terms of efficiencies – THICK  AG :.87  Bkg :.46 THIN  AG :.73  Bkg :.63 PreFilter AcdActiveDist > -199 | AcdRibbonActDist > -1000 THIN  AG :.92  Bkg :.84 Still its bad - but???? This PreFilter is considerably worse for the THICK events then the one dev. for it. THICK and THIN seem to be just DIFFERENT Prob>.5 THIN  AG :.67  Bkg :.02 cos(  ) 100 MeV

7 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 7 VTX, All Layers, 350 < CalEnergyRaw < 3500, cos(  ) < -.3 PreFilter AcdActiveDist > -199 & AcdRibbionActDist > -1990 All Layers  AG :.97  Bkg :.55 This  ineff. is consistent with conversions in blanket and tiles All events now have BestEnergy > 100 and cos(  ) < -.3

8 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 8 VTX, All Layers, 3500 < CalEnergyRaw, cos(  ) < -.3 PreFilter AcdActiveDist > -10 | CalTrackAngle >.5 | CalTrackDoca > 40 The Remaining Bkg Event e - (e - Splash) Event Well Reconstructed This is NUTS! The event clearly has to be pointing at an ACD Side tile and there is no SSD Veto. The Doca Calc. says the event had a track well within a tile – so why is the ActiveDistance set to its rogue value? This is a glast-ts generated event. Can Toby find it? (It comes from either series 2 or 3) We NEED a picture of it!

9 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 9 Prob. >.50 All Gamma Background PreFilters Background Rejection Path (BR.Path) not yet determined Background Source Breakdown HeavyIons have gone away Vtx Topology Summary ( All numbers for BestEnergy > 100 MeV & BestZDir < -.3 ) Level NameCounts VTX&CAL_Hi2541/108 VTX&CAL_Med5080/1050 VTX&CAL_Low6273/3175 (  /Bkg) Loss.013.120.465 MIP Finder Failure

10 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 10 1Tkr, THICK layers, CalEnergyRaw < 350 MeV PreFilter cos(  ) < -.3 AcdActiveDist > -199 | AcdRibbonActDist > -1999 | AcdDoca 200 | EvtECalTransRms > 2.5 | CalMaxXtalRatio >.8 | Tkr1FirstChisq > 2.5 | Tkr1ToTTrAve > 2 THIN  AG :.68  Bkg :.03 Desperation: This is the toughest subclass. In DC1 we had to through all these away. This is better but clearly not there yet. Prob>.5 Note that ~ 50% of the events are below BestEnergy < 100 MeV cos(  ) 100 MeV

11 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 11 1Tkr, THIN layers, CalEnergyRaw < 350 MeV PreFilter cos(  ) < -.3 AcdActiveDist > -199 | AcdRibbonActDist > -1999 | CalTrackDoca > 200 | EvtECalTransRms <.8 THIN  AG :.72  Bkg :.04 cos(  ) 100 MeV Desperation: This is the 2 nd toughest subclass. Prob>.5 Note that ~ 40% of the events are below BestEnergy < 100 MeV

12 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 12 1Tkr, All layers, 350 MeV < CalEnergyRaw < 3500 MeV cos(  ) < -.3 PreFilter AcdActiveDist > -199 | AcdRibbonActDist > -1900 | CalTrackDoca > 40 | CalTrackAngle >.5 | CalXtalRatio >.85 All Layers  AG :.73  Bkg :.04 cos(  ) 100 MeV Prob>.5

13 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 13 1Tkr, All layers, CalEnergyRaw > 3500 MeV cos(  ) < -.3 PreFilter CalTrackDoca > 30 | CalTrackAngle >.3 All Layers  AG :.98  Bkg :.015 cos(  ) 100 MeV Prob>.5 This PreFilter was not done properly first time around. Here's a re-do Re-Make of 1Tkr Cal_Hi Leaving out all ACD vars. in PreFilter Note however that the CTs insist on using the ACD.

14 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 14 Prob. >.50 All Gamma Background PreFilters Background Rejection Path (BR.Path) not yet determined Background Source Breakdown 1Tkr Topology Summary ( All numbers for BestEnergy > 100 MeV & BestZDir < -.3 ) Level NameCounts 1Tkr&CAL_Hi15098/8932 1Tkr&CAL_Med5944/17242 1Tkr&CAL_Low4891/33163 (  /Bkg) Loss.075.394.641 Note how much larger the Bkgs are w.r.t. Vtx except for CalEnergyRaw > 3500 MeV MIP Finder Failure 2 nd Time Around

15 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 15 v7r2 SLAC 2M All Gamma Run Pr(GAM) >.50 62/bin x 50 bins = 3100 3100/(2x10 6 / 100) x 6 m 2 * 150 = A eff (cm 2 ) or N >1GeV * 5.36 = A eff (cm2) A eff = 9300 cm 2 2469/bin (2531) x 50 Bins = 113500 113500/2x10 6 x 37.7 m 2 -str *.943x10 -3 = A eff x  (m 2 -str) or N >1GeV *3.37x10 -5 =A eff x  (m 2 -str) A eff x  = 2.39m 2 -str Fall-off past 10 GeV improved – however this results from the CTs using AcdActiveDist to kill the high energy cosmic electron component in the background – it may be a fact of life for now... Number > 1 GeV = 1726 in 28 bins Number > 1 GeV = 70883 in 28 bins SRD Limit Background: 319 Events or.16 Hz (SRD ~.03 Hz)

16 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 16 cos(  ) < -.9 cos(  ) > -.6 These basically meet the SRD Near On-Axis Edge of FoV

17 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 17 Prob.GAM >.3 (relaxed cut) 1151 Events Direction Correlated events: 175 Events PSF Class Direction Anti-Correlated events: 416 Events Come in through the corners and there is a definite handedness this suggest a ERROR IN THE ACD CODE / GEOMETRY These are dominated by upward moving protons. This is what the MIP Finder was suppose to identify PSF Class Residual Background Dissection No Correlation: 560 Events – large component of Limb  s Location of First Hit on Found Track

18 Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 18 Event Spectra both MC Truth and as Reconstructed After PreFilter Stage No Prob.GAM Cut Prob.GAM >.7 (Meets Aeff and Background rate req.) 61 Events Rate =.03 Hz 62352 events > 1 GeV A eff x  = 2.1 m 2 -str

Download ppt "Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 1 Back Ground Rejection Status for DC2 a la Ins. Miner Analysis."

Similar presentations

STAR Status of J/  Trigger Simulations for d+Au Running Trigger Board Meeting Dec5, 2002 MC & TU.

STAR Status of J/  Trigger Simulations for d+Au Running Trigger Board Meeting Dec5, 2002 MC & TU.
UK egamma meeting, Sept 22, 2005M. Wielers, RAL1 Status of Electron Triggers Rates/eff for different triggers Check on physics channels Crack region, comparison.

UK egamma meeting, Sept 22, 2005M. Wielers, RAL1 Status of Electron Triggers Rates/eff for different triggers Check on physics channels Crack region, comparison.
Bill Atwood, Dec. 2002 GLAST 1 GLAST Energy or Humpty-Dumpty’s Revenge A Statement of the Problem Divide and Conquer strategy Easiest: Leakage (Depth)

Bill Atwood, Dec GLAST 1 GLAST Energy or Humpty-Dumpty’s Revenge A Statement of the Problem Divide and Conquer strategy Easiest: Leakage (Depth)
LHCb PatVeloTT Performance Adam Webber. Why Upgrade?  Currently we de-focus the beams o LHCb Luminosity ~ 2x10 32 cm -2 s -1 o ~ 1 interaction per bunch.

LHCb PatVeloTT Performance Adam Webber. Why Upgrade?  Currently we de-focus the beams o LHCb Luminosity ~ 2x10 32 cm -2 s -1 o ~ 1 interaction per bunch.
Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 1 Tracker SAS Analysis Objective: To expose the tools and an approach to understanding the GLAST Tracker Initially.

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 1 Tracker SAS Analysis Objective: To expose the tools and an approach to understanding the GLAST Tracker Initially.
Bill Atwood, August, 2003 GLAST 1 Covariance & GLAST Agenda Review of Covariance Application to GLAST Kalman Covariance Present Status.

Bill Atwood, August, 2003 GLAST 1 Covariance & GLAST Agenda Review of Covariance Application to GLAST Kalman Covariance Present Status.
Bill Atwood, SCIPP/UCSC, May 8, 2006 GLAST 1 Partial validation of v9r3 - Bkg. Rej. Comparison 2000 sec. of backgrounds were run using v9r3 (heros: Tom.

Bill Atwood, SCIPP/UCSC, May 8, 2006 GLAST 1 Partial validation of v9r3 - Bkg. Rej. Comparison 2000 sec. of backgrounds were run using v9r3 (heros: Tom.
Status of the MICE SciFi Simulation Edward McKigney Imperial College London.

Status of the MICE SciFi Simulation Edward McKigney Imperial College London.
Assessment and Proposal W. B. Atwood UCSC, April 6, 2005.

Assessment and Proposal W. B. Atwood UCSC, April 6, 2005.
Analysis Meeting 24Oct 05T. Burnett1 UW classification: new background rejection trees.

Analysis Meeting 24Oct 05T. Burnett1 UW classification: new background rejection trees.
Bill Atwood, SCIPP/UCSC, Apr. 3, 2006 GLAST 1 Pass 4 and Preparing for the LAT Handoff to NASA Why we can't go with the DC2 Analysis (Pass 3) 1) Background.

Bill Atwood, SCIPP/UCSC, Apr. 3, 2006 GLAST 1 Pass 4 and Preparing for the LAT Handoff to NASA Why we can't go with the DC2 Analysis (Pass 3) 1) Background.
Bill Atwood, July, 2003 GLAST 1 A GLAST Analysis Agenda Overarching Approach & Strategy Flattening Analysis Variables Classification Tree Primer Sorting.

Bill Atwood, July, 2003 GLAST 1 A GLAST Analysis Agenda Overarching Approach & Strategy Flattening Analysis Variables Classification Tree Primer Sorting.
S. Ritz1 Checking Out What is Checked In  Need to optimize balance of checking between users and developers. –infuse more of a culture of detailed checking.

S. Ritz1 Checking Out What is Checked In  Need to optimize balance of checking between users and developers. –infuse more of a culture of detailed checking.
Bill Atwood, SCIPP/UCSC, Jan. 30, 2006 GLAST 1 Closer to Reality From Last Talk ( 7-Jan-06) – things seemed Great! However... 1) In estimating the SRD.

Bill Atwood, SCIPP/UCSC, Jan. 30, 2006 GLAST 1 Closer to Reality From Last Talk ( 7-Jan-06) – things seemed Great! However... 1) In estimating the SRD.
Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 1 DC2 Discussion – What Next? 1)Alternatives - Bill's IM analysis - ???? 2)Backing the IM Analysis into Gleam.

Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 1 DC2 Discussion – What Next? 1)Alternatives - Bill's IM analysis - ???? 2)Backing the IM Analysis into Gleam.
David WrenDC1 Closeout, 13 February 20041 OnboardFilter Update Work done by: Navid Golpayegani J.J. Russell David Wren Data Challenge I Closeout Meeting,

David WrenDC1 Closeout, 13 February OnboardFilter Update Work done by: Navid Golpayegani J.J. Russell David Wren Data Challenge I Closeout Meeting,
GLAST LAT ProjectTrigger Scheduler, Engines, and Rates 6 Feb 2006 J. Eric Grove Naval Research Lab Washington DC Trigger Scheduler, Engines, and Rates.

GLAST LAT ProjectTrigger Scheduler, Engines, and Rates 6 Feb 2006 J. Eric Grove Naval Research Lab Washington DC Trigger Scheduler, Engines, and Rates.
Analysis Meeting 31Oct 05T. Burnett1 Classification, etc. status at UW Implement “nested trees” Generate “boosted” trees for all of the Atwood categories.

Analysis Meeting 31Oct 05T. Burnett1 Classification, etc. status at UW Implement “nested trees” Generate “boosted” trees for all of the Atwood categories.
Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 1 Background Files Available Processed 500M v7r2 Bkg. events run at SLAC Processed 2M v7r2 All Gammas Processed.

Bill Atwood, SCIPP/UCSC, Oct, 2005 GLAST 1 Background Files Available Processed 500M v7r2 Bkg. events run at SLAC Processed 2M v7r2 All Gammas Processed.
Hardware Failure Impacts Exercises S. Ritz. Issues Recent results from design reliability analysis (system engineering, Thurston et al.) Probabilities.

Hardware Failure Impacts Exercises S. Ritz. Issues Recent results from design reliability analysis (system engineering, Thurston et al.) Probabilities.

Similar presentations

Ads by Google