1. ATLAS Group Introduction + TriggerMasahiro Morii20’ Muon Spectrometer + Upgrades João Guimarães da Costa25’ Cosmic Ray AnalysisAlberto Belloni20’ Physics I + ComputingJohn Huth25’ Physics II + MonitoringMelissa Franklin25’ 8/21/2009 1 ATLAS Intro + Trigger, M. Morii

2. Harvard ATLAS Group PIs: Melissa Franklin, João Guimarães da Costa, John Huth, Masahiro Morii Postdocs: Kevin Black, Alberto Belloni, Corrinne Mills, Shulamit Moed + new hire Graduate Students: Lashkar Kashif (G7 in ’09–’10), Verena Martinez Outschoorn (G5), Srivas Prasad (G5), Ben Smith (G5), Michael Kagan (G4), Laura Jeanty (G3), Giovanni Zevi della Porta (G3), Kevin Mercurio (G2) + William Spearman (G1) Undergrads: Jack Kearney, Maria Baryakhtar, Jeewoo Park, Michael Fountaine, Curt Nehrkorn, Tomo Lazovich 8/21/2009 2 ATLAS Intro + Trigger, M. Morii

3. Physics First LHC run, E CM = 7 TeV –Crucial for understanding the machine, detector –Opportunities for early physics W, Z  Z + jets, WZ production Top quark production Future runs, E CM = 14 TeV –Link from early physics to discovery Z + Higgs, same-sign dilepton, multi-lepton BSM tt-bar resonance 8/21/2009 3 ATLAS Intro + Trigger, M. Morii

4. Muon Spectrometer Our primary responsibility and strength –Production of endcap MDT chambers and MDT front-end electronics –Vertical integration of MDT-related tasks Installation, commissioning, and operation DAQ software Online/offline data-quality monitoring Muon reconstruction software –Validate and debug using cosmic ray data Target: publication of μ + /μ − ratio 8/21/2009 4 ATLAS Intro + Trigger, M. Morii

5. ATLAS Trigger Developments Melissa Franklin, Corrinne Mills, Kevin Mercurio, Ben Smith, Masahiro Morii 8/21/2009 5 ATLAS Intro + Trigger, M. Morii

6. Introduction Goal: Give physics analysis access to detailed trigger information Harvard is a major contributor to the Trigger Core Software and Trigger Analysis Tools groups in ATLAS Physics Dataset Derived Dataset Trigger Efficiency Final Analysis Reduction Techniques Efficiency Measurement Database Access Trigger-Aware Analysis Navigation Slimming Trigger Offline Matching Efficiency Framework 8/21/2009 6 ATLAS Intro + Trigger, M. Morii

7. Navigation Slimming Trigger Navigation structure offers full information of the trigger decision process –Which algorithms were run, what their results were, and what algorithms they seeded –Backbone of trigger aware analysis –Represents large fraction (15%–30%) of total event size Ideal candidate for slimming –Derived dataset for each analysis needs only a subset of the Navigation tree Muon RoI Muon ID Muon MS Muon EF Muon RoI Muon ID Muon MS Calo RoI Tau Calo Tau Final Calo RoI egamma Calo egamma TRT Photon Final Initial Node 8/21/2009 7 ATLAS Intro + Trigger, M. Morii

8. Navigation Slimming — Status — Designed and implemented by B. Smith –Harvard will continue to develop & maintain the code Successfully tested by the Derived Physics Dataset (DPD) Group –In place for upcoming central DPD production for 7 TeV Monte Carlo samples –Will be used in the standard DPD production for colliding-beams data in 2010 8/21/2009 ATLAS Intro + Trigger, M. Morii 8

9. Trigger/Offline Matching Associate trigger and offline objects –Which trigger did this object pass? –Properties (e.g. P T ) of the object according to trigger algorithms More detailed than the traditional event-level trigger decision information –Necessary, e.g., for measuring trigger efficiencies by tag-and- probe Must parse the Navigation structure Z p T : 20 GeV μ1μ1 μ2μ2 TrigDecision mu10: mu20: mu40: ✓ ✓ X Matching mu10: μ 1, μ 2 mu20: μ 1 mu40: none 8/21/2009 9 ATLAS Intro + Trigger, M. Morii

10. Trigger/Offline Matching — Status — Designed and implemented by B. Smith –Examples, documentation, and limited testing complete Initial deployment in progress –High-Level-Trigger (HLT) monitoring –Trigger efficiency measurements H → 4 lepton. Z → μμ tag and probe –Trigger fake rate studies (K. Mercurio) –Analysis tools (PhotonAnalysisUtils) Backbone for all future trigger-aware analyses 8/21/2009 ATLAS Intro + Trigger, M. Morii 10

11. InsituPerformance Framework InsituPerformance Framework stores object measurements of general interest: –Trigger and particle ID efficiencies, resolutions, and fake rates –Globally accessible, centrally maintained database Harvard works on trigger-specific implementation of the framework –Flexible definition of trigger efficiency –Validation and debugging of tools –Implementation of slice-specific tools 8/21/2009 11 ATLAS Intro + Trigger, M. Morii

12. InsituPerformance Framework — Status — C. Mills coordinates experts for different trigger slices to develop efficiency measurement code –Missing E T, MinBias, and tau slices in progress –In contact with jet and b-jet experts –Muon and electron code developed separately Goal: Deploy for all slices with first colliding-beam data Remaining technical issues –Ideal database implementation –Validation/approval of entries into database –Linking entries with documentation C. Mills will take primary responsibility for the InsituPerformance Framework in September 8/21/2009 12 ATLAS Intro + Trigger, M. Morii

13. Summary and Future Plans Harvard Group focuses on making trigger-aware analysis possible in ATLAS –Navigation slimming –Trigger/offline matching –Trigger efficiency framework Active involvement in Trigger Core Software and Trigger Analysis Tools Groups –Incorporation of our tools in benchmark efficiency measurements for each slice –Development of user tools for quick access to trigger state and trigger configuration information in data 8/21/2009 ATLAS Intro + Trigger, M. Morii 13