1. Introduction Advantages/ disadvantages Code examples Speed Summary Running on the AOD Analysis Platforms 1/11/2007 Andrew Mehta

2. Introduction: AOD is the basic data repository for physics analysis at ATLAS Analysis frameworks generally take information from the AOD and make a copy (e.g. Liverpool NTUPLE), or make some modifications (e.g. EVENTVIEW) and make a new NTUPLE Other possibility is to use AOD itself and run analyses directly on that Possible either by using `Analysis Tools’ within ATHENA or by direct ROOT access My aim is to produce code a la Liverpool NTUPLE for high Pt analyses with intelligent overlap removal and simple instructions for new users including working examples Next aim would be to set up a common framework to incorporate systematic errors, histogram managers etc. Would be great if we could all use same software. Probably only possible with direct AOD access

3. Running on AOD Code easily portable between different people even if they use different analysis models All the variables are always there. No need to remake NTUPLES if extra information needed Only one set of code. No separate NTUPLE production code and analysis code One format for all analyses. No multiple copies of same data with slightly different NTUPLE formats. Could save disk space in long run. Access to low level objects and reconstruction code much easier e.g. rerunning b tagging algorithms possible Particle masking to avoid double counting done non-persistently so easily adaptable if cuts change Code all written in c++ not in PYTHON/c++ mixture Advantages:

4. Running on AOD Disadvantages: Code needs to be run in ATHENA environment even in RootAccess mode Not very straight forward to set up code from scratch even following ‘help’ pages More disk space needed for the AOD than an NTUPLE dedicated to a specific analysis Each new class seems to require an abstract base class in which each function must be implemented Compile time rather slow 1.5 m In RootAccess mode a very long wait running PYTHON scripts to set up root Run time slower?

5. Find Electrons Get Good Electrons Make Mass User Code Z Mass:

6. Electrons on AOD Select electron categories Basic Code: e Selection

7. Steering: List of input AOD files Must list modules used in code Histogram output file Can change selection cuts without rerunning Change debug level

8. Speed Version 12 is supposed to be slow, but we can run jobs of 1M events in 30m CPU, 1h real time At Liverpool we seem to have slower real times for unknown reasons This presumably affects all analyses not just ATHENA Version 13 should be quicker still Can also speed jobs up even further with use of the TAG database Obviously for quick test jobs at present direct AOD access much slower than NTUPLE based analyses due to long compile and setup times

10. Summary Direct analysis on AOD has several advantages over derived NTUPLE code Some annoying teething problems at present, but none that means analysis can’t be done now Fast enough for most analyses at present if disk access problems overcome Future software versions should make this approach faster and more user friendly