Missing Transverse Energy

In ATLAS there are different ways for calculating the missing transverse energy (E_T^miss).

The most used method associates the calorimeter topo-clusters to reconstructed objects, such as jets, electrons, muons, taus, and photons, and calibrates them accordingly. In the next chapters we will use a E_T^miss made with a simpler calibration scheme, called

“Local Cluster Weighting” (LCW) [68], that is more suitable for the analyses described in this thesis.

The LCW calibration method classifies the topo-clusters as either electromagnetic or hadronic, using the energy density and the shape of the cluster. Based on this clas-sification energy corrections are derived from single pion MC simulations. Dedicated corrections are derived for the effects of non-compensation, signal losses due to noise threshold effects, and energy lost in non-instrumented regions. They are applied to calorimeter clusters and are defined without reference to a given reconstructed object.

They are therefore called local corrections. A special correction is made for the energy lost in the cryostat between the LAr electromagnetic calorimeter and the Tile calorime-ter, which at a thickness of about half an interaction length can lead to signicant energy losses in hadronic showers.

After the topo-cluster four-momenta are calibrated theE_T^miss is calculated form the vectorial sum of the p_T of all cells belonging to topo-clusters:

E_x^miss = −

Ncell

!

i=1

E_i^cellsin(θ_i)cos(φ_i) E_y^miss = −

Ncell

!

i=1

E_i^cellsin(θ_i)sin(φ_i) (3.9) The E_T^miss performance can be studied by measuring theE_x,y^miss resolutions as func-tion of the total transverse energyΣE_T, which is reconstructed from the calorimeters as the scalar sum of the transverse energy of all cells. Figure3.9(left) shows theE_T^miss resolution in minimum-bias events at 7 TeV. The E_T^miss resolution is expressed as the root mean square of theE_x,y^miss distributions, and follows approximately a k×√

ΣE_T function, with k being a parameter to be fitted. Three calibration schemes are com-pared in the figure: the LCW, the EM (topo-cluster four-momenta are used at the EM scale), and the “Global Cell Weighting”, or GCW (see reference [69]). The lat-ter applies cell-level weights that are based on the comparison between reconstructed and truth jets in MC. The figure shows how the LCW and GCW calibration schemes improve theE_T^miss resolution. Figure3.9 (right) compares instead theE_T^miss resolution

in data and MC events, showing a good agreement. For the simulation, samples of PYTHIA minimum-bias events have been used.

(EM) [GeV]

ET

Σ

0 50 100 150 200 250

[GeV]T EΣ(EM)/T EΣ Resol*miss y,Emiss xE

0 1 2 3 4 5 6 7 8 9 10

ET

Σ EM scale: fit 0.41

ET

LCW: fit 0.37 Σ ET

GCW: fit 0.39 Σ

ATLASPreliminary

= 7 TeV s Data 2010

Ldt=0.34 nb-1

∫η|<4.5

|

[GeV]

ET

Σ

0 50 100 150 200 250 300

Resolution [GeV]miss y,Emiss xE

0 1 2 3 4 5 6 7 8 9 10

LCW

ET

Σ Data: fit 0.49

ET

Σ MC Minbias: fit 0.51

ATLASPreliminary

= 7 TeV s Data 2010

Ldt=0.34 nb-1

∫η|<4.5

|

Figure 3.9: The figure on the left-hand side shows theET^missresolution in minimum-bias events for the EM scale ET^miss, and for LCW and GCW calibrated ET^miss. Results are shown as a function of the EM scaleΣET. The figure on the left-hand side campares the resolution of the LCWET^missin data and MC events. Figures are taken from reference [69].

The LCW E_T^miss calibration scheme has been used successfully in W inclusive and W+jets cross section measurements [70,71], providing a good understanding of these processes. Figure 3.10 (taken from reference [70]) shows the E_T^miss distributions in an inclusive sample of events with one electron (left) or one muon (right) withpT >20 GeV.

The figure shows how the distributions in data and MC are in reasonable agreement, both in the low E_T^miss region (E_T^miss <30 GeV) dominated by QCD multi-jet events, and for higher E_T^miss values dominated by W production.

[GeV]

Figure 3.10: The figure on the left-hand side shows ET^miss distributions in an inclusive sample of events with one electron (left) or one muon (right) withpT>20 GeV. The figures are taken from reference [70].

Search for new phenomena in the mono-jet final state at √

s =7 TeV

This chapter describes the mono-jet analysis performed with the full 2011 dataset of p-p collisions at√

s=7 TeV. The analysis has been published in JHEP [72], and follows other two publications that made use of lower integrated luminosity: 33 pb⁻¹ of data collected in 2010 [73], and the first 1 fb⁻¹ of data collected in 2011 [74]. The analysis performed with√

s=8 TeV data collected in 2012 is the subject of the next chapter.

This chapter is organized as follows. Sections4.1and4.2present the various aspects of the ATLAS recorded dataset and simulated MC samples used for this analysis. The definition of the physics objects and the event selection criteria are detailed in sections 4.3 and 4.4, respectively. The background estimation is described in section 4.5, and results are presented in section 4.6. Section 4.7 discusses the interpretation of the results in the context of Large Extra Dimension models and WIMP pair production.

For the analysis of the full 2011 dataset, two alternative methods for Z/W+jet BG estimation have been developed within the ATLAS collaboration. The first method, presented in this chapter, follows closely the procedures used in the other ATLAS publications on searches in the mono-jet final state. The second method, detailed in appendixE, makes use of slightly different proceedings, mainly regarding the selection of events to be used for control samples. The estimation of the BG processes and the level of systematic uncertainties are in good agreement between the two procedures.

Finally, the second method was adopted for the nominal results in the paper [72], while the method previously used was employed as a cross check.

4.1 Data sample

This analysis makes use of the full 7 TeV dataset recorded by ATLAS in 2011. This corresponds to an integrated luminosity of 5.2 fb⁻¹. After applying basic data quality requirements on the data-taking conditions the remaining datasets consist of 4.7 fb⁻¹. The maximum instantaneous luminosity increased from 1.3·10³⁰cm⁻²s⁻¹to 3.6·10³³cm⁻²s⁻¹ along the year. This translated into an increase of the mean number of collisions per bunch crossing from 2.6 to 17.5.

Trigger selection. Events are collected with the lowest unprescaled E_T^miss trigger item, called “EF xe60 verytight noMu”, which has the following thresholds at the three trigger levels :

• E_T^miss(L1)>50 GeV

• E_T^miss(L2)>55 GeV

• E_T^miss(EF)>60 GeV

Details about the implementation of the E_T^miss trigger can be found in reference [75].

The trigger algorithms use only calorimeter-based quantities with no corrections for identified muons.

LAr hole. The detector conditions have also been changing during the year. The biggest detector problem that affected this analysis was the failure of 6 front-end boards (FEB) that correspond to adjacent areas of the barrel LAr calorimeter (see section 3.2.2). This dead region of the calorimeter will be referred as the “LAr hole”. Due to this problem it was not possible to reconstruct the energy deposited in the second and third layer of the calorimeter in the region with−0.8< φ <−0.6 and 0< η <1.4. This problem concerned only a part of the dataset that corresponds to 1 fb⁻¹ of integrated luminosity. During a LHC technical stop in July 2011, 4 out of the 6 non-functioning FEBs were recovered. After this fix only the energy in the third layer was unmeasured, resulting in a much smaller impact in the analysis. Dedicated cleaning requirements have been implemented in order to remove events affected by the LAr hole. This is described in the section4.4.