1. BH  bb and BH  uu Using Version 12 Training Monica Dunford FTK Monthly Meeting February 21, 2007

2. 2 Summary of Cuts Studying WH->bb and WH->uu samples For all samples, the following are applied –-1.0 < Cot(  ) < 1.0 –-0.3 < curvature(GeV -1 ) < 0.3 –No cuts on truth track association

3. 3 Athena v10 FTK Results Reprocessed Meena’s v10 samples –Number of tracks is much improved –Not much improvement in bb vs. uu impact parameter Remainder of slides focuses on v12

4. 4 Athena v12 Data Sets Using CSC Digitization processing –misal1_csc11.005850.WH120bb_pythia.digit.RDO.v12003103 –misal1_csc11.005851.WH120uu_pythia.digit.RDO.v12003103 Have approximately 48,000 WHbb events and 32,000 WHuu events currently processed Currently running WHbb and WHuu samples with TRT disabled in iPat –Will be done in a few days

5. 5 Athena v12 Number of Tracks Fewer FTK tracks expected due to incomplete training

6. 6 WHbb Impact Parameter New training has removed ‘features’ in v10 FTK distribution Better agreement with iPat distribution –Test this against iPat with no TRT

7. 7 bb and uu Discrimination FTK’s impact resolution is worse than iPat, especially in WHuu FTK iPat

8. 8 iPat Differences Between v10 and v12 iPat Impact parameter resolution has worsen But discrimination in v12 looks better with higher statistics (compared to last week)

9. 9 iPat and FTK Differences FTK’s Pt vs. Impact distribution much different than iPat and truth FTK WHuu FTK WHbb iPat WHbb iPat WHuu Truth track distr. looks similar to iPat

10. 10 iPat and FTK Differences Impact parameters distribution for two Pt ranges FTK WHbb FTK WHuu iPat WHbb iPat WHuu

11. 11 Next Ideas Associate tracks to jets –Promised code from Meena Compare FTK to iPat with no TRT –Jobs are currently running Compare offline b-tagging algorithms between FTK and iPat