This page provides a list of selected topics to work and discuss during
the SLAC physics analysis retreat, as well as basic documentation, and links
to datasets. The goal is to be able to produce results in each area, by the
end of the workshop.
More topics may be added after the general physics meetings on Monday,
motivated by everyone's interests.
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Proposed topics
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Documentation
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Data Samples
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Example of CBNT Analysis
Proposed topics:
Jet Algorithms
- Compare different jet clustering algorithms (Cone, kT) in different data samples
(multijets, W/Z+jets, ttbar, susy)
- Understand differences in algorithms by the study of the cluster composition of jets.
Contact person: Peter Loch
Jet Calibration
- Gamma+Jet and dijet balance studies.
Contact person: Peter Loch
Jet Energy Resolution
- Study of data-driven techniques to measure the jet energy resolution: dijet and kT balance.
- Understand the difference in treatment of soft gluon radiation between both approaches.
- Study the effect of the event topology in the estimation of jet resolution.
- Monte Carlo closure tests.
Contact person: Ariel Schwartzman
Event Shapes
- Event shape studies in different samples.
Contact person: Peter Loch
Jets with Tracks
Jet energy resolution can be improved by the use of track information. For instance,
jets with different fraction of track energy have different energy response. Thus, track-based
jet energy response corrections result in additional improvements in jet resolution. A tentative
list of projects is listed bellow:
- Evaluate the current algorithm performance after jet energy scale correction.
- Explore the use track variables other than ftrk, such track-multiplicity, sum(pt), leading track pT,
etc., to improve jet energy resolution.
- Explore the use of correlations between track-based variables. For instance by deriving a
2-Dimensional response correction R(ftrk,f1trk).
- Evaluate the performance of the existing track+jet algorithm in different data samples, and
in particular in b-jets.
- Study the effect of track-jet corrections in MET.
Contact person: Ariel Schwartzman
Jet-Vertex Association
At high luminosity, events will contain soft jets associated to additional minimum bias
interactions. It is important to develop techniques to identify (and remove) jets
not produced in the hard scatter interaction.
DZero developed a Jet-Vertex association algorithm based on tracks, that associates to each jet,
a probability that it originates from a particular vertex interaction.
- Implementation of a Jet-Vertex association algorithm.
- Study the performance of the algorithm in different samples.
Contact person: Ariel Schwartzman
Comparison of MET calculation using Clusters/Objects
Several studies of MET using clusters and physics objects can be made using a special
version of CBNT root tuples containing topological clusters and their link to physics objects.
Projects in this area include:
- Impact of soft particles in MET resolution.
Contact person: Peter Loch
Unclustered Energy Resolution and Calibration
- Develop a data-driven method to measure unclustered energy resolution using Zee events.
- Understand -at the cluster level- the sources of unclustered energy (ISR/underlying
event/out-of-cone showering)
Contact person: Ariel Schwartzman
MET Significance
The MET significance algorithm computes, in an event-by-event basis, what is the probability
that the observed MET arises from instrumental effects taking into account the resolution
of the measured physics objects, the unclustered energy, and the topology of the event.
This idea, developed at DZero, was shown to be very effective to reject QCD background.
There are several areas to contribute to the development of this technique in ATLAS:
- Performance studies of signal/background discrimination in different data samples.
- Include effects not yet modeled in the current algorithm implementation.
- Improvements in each of the different components of the METsig algorithm.
Contact person: Ariel Schwartzman
Jet/Met Documentation:
Data Samples:
All data samples are located in $ATLROOT/data/jetmet/
This is the list of steps to be able to analyze CBNT root tuples:
- Generate a skeleton class for analysis:
root [mysample.root]
_file0->cd("CBNT");
t3333->MakeClass("Analysis");
.q
- Insert your analysis code in the Loop method of Analysis.C
- Compile
Create the following script called run.csh
{
gSystem->Load("libPhysics.so");
gSystem->CompileMacro ("Analysis.C", "k");
TTree* tree = 0;
TFile *f = new TFile("mysample.root");
f->cd("CBNT"); tree = (TTree*)gDirectory->Get("t3333");
cout << "Number of events = " << tree->GetEntries() << endl;
Analysis* a = new Analysis(tree);
}
- Run:
root run.csh
root [0] > a->Loop();