Christian Autermann

Hadronic Reference Analyses

The CMS SUSY search strategy for key final states: Reference Analyses (RA)CMS SUSY Hadronic group co-convenor:CMS SUSY Validation contact person:

The CMS-SUSY group strategy is to establish robust, if possible data-driven analyses, for the key-final states:

RA1: Exclusive N-jet searchRA2: Inclusive hadronic SUSY search with MET and 3 jetsRA3: GMSB di-photon and jets

● One analysis done as team effort ↔ advantage compared to many similar “small” analyses● Redundancy and cross checks essential for robustness● Foundation for more complex searches ● Eventually add b, t, τ,… to the list of RA signatures.The Hamburg University group strongly contributes to RA1 and RA2.

QCD Background Prediction

1. Factorization (“ABCD”) Method

tt / W - Background Prediction_

Christian Sander

Torben Schum

Jan Thomsen, Jula Draeger

MET Tail and Resolution

Ulla Gebbert

Cross-Cleaning

No correlation between V

1 and V

2:

With (known) correlation:

Publication in form of an CMS-Analysis note in preparation

Publication within the RA2 CMS-Analysis note in preparation

SignalPredictionPrediction with signal contaminationQCD truth

C/D

Publication within the RA2 CMS-Analysis note in preparation

Publication within the RA2 CMS-Analysis note in preparation

r

r

2. “Smearing” method

First, a control sample of well measured QCD events without MET is selected.Then, the jet-response function r is used to smear the jets, modelling the high MET tail.

The jet-response function r is determined in an unbinned fit on a di-jet sample. In the fit ɣ-jet and Z-jet samples could be used, simultaneously.

In each event i, the probability density P of a given di-jet configuration is given by:

The response function parameters b are determined by minimizing a log-likelihood function over all events

Matthias Schroeder

Semi-leptonic decaying tt-events for which the lepton is lost, are an important background for all-hadronic analyses. Reasons for the lepton-veto cut to fail are:

The tt → τ+jets events, where the τis decaying hadronically, are mo-delled by tt → μ+jets events. The muon's four-momentum is re-placed, using a hadronic tau res-ponse function and is then con-sidered as an additional jet.

Pt < 15 GeV Pt ≥ 15 GeV

Isolated Background C Control sample

Not Isolated Background B Background A (most relevant)

The reconstruction efficiencies are found on Z → ll samples, where as the isolation efficiency is obtained from top events. The tag & probe method is utilized for both.

The efficiencies are parametrized in Pt of the lepton and the distance ΔR to the nearest jet, to take kinematic effects on the efficiency into account.

Pt (

muo

n) / 

Pt (

clos

est j

et)

ΔR (muon, closest jet)M

uon 

isol

atio

n ef

ficie

ncy

ΔR (muon, closest jet)

Eve

nts 

per 

100 

pb­1

Dominant systematic uncertainties arise from the low event statistics in the control region.

Estimation: (preliminary) 12.7±6.1 eventsMonteCarlo: 11.6 events

Benedikt Mura, Friederike Nowak

Energy depositions in the detector are not uniquely assigned to one reconstructed physics object like electrons, photons, muons, taus, and jets, but can contribute to several of them. This leads to an overlap of the objects and a double counting of energy. A cross-cleaning package which provides algorithms to identify the overlap of any two objects has been developed. It provides a framework to correct objects for the multiple counted energy, to remove duplicates, therefore im-proving the MET resolution important for all SUSY analyses.

Example: electron ↔ jet cleaning

Published: CMS IN-2009/035 “A cross cleaning package”

After the cross­cleaning the recoil of all jets and electrons “MHT” agrees well with the calorimeter MET.

High energetic jets important for SUSY analyses can be mismeasured due to heavy flavor decays involving neutrinos and punch-through. The mismeasure-ment of these jets leads to tails in the MET distribution. Information from the muon system can be used to derive selection criteria from first data in order to identify and tag these jets. The implications for the MET distribution are investi-gated. A data-driven correction for these jets can be derived.

The plots show the punch-through and heavy-flavor tagged jets at low jet responses, and at hight MET.

MET [GeV]Jet response (Ptcalo – Ptgen) / Ptgen

Eve

nts 

per 

100 

pb­1

Num

ber 

of je

ts

Supersymmetry at CMS - Hamburg University Contributions -

Christian Autermann, Jula Draeger, Ulla Gebbert, Benedikt Mura, Friederike Nowak, Christian Sander, Matthias Schroeder, Torben Schum, Peter Schleper (project leader), Jan Thomsen

Hamburg University, Luruper Chaussee 149, 22761 Hamburg, Germany SFB Evaluation, Nov 25th 2009

Cross checks of this method can be performed ● By using multiple variable pairs, e.g. HT – Δφ(MET, nearest jet), MHT – ɳ, etc. ● Simulating effects of mismeasurements and/or systematic uncertainties● Studying effects on shape & correlation

This method has an advantage over plain MC, if the correlation is better understood than the effects leadings to MET in QCD-multijet events.

Under the assumption that the correlation between two variables is known, the amount of QCD in a control region and in the signal region can be factorized. For this, discriminating and well behaving variables are necessary, i.e. the scalar sum of hadronic energy HT, the vectorial sum MHT, missing transverse energy MET, angles Δφ, ...

Not identified or non-isolated leptons (e or μ) are modelled using a tt-control sample with well identified and isolated muons. The events are weighted according to their reconstruction or isolation inefficiency.

RA4 – RA7:Leptonic final states

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