3.3 Physics object reconstruction in ATLAS
3.3.4 E miss T reconstruction
configur-3.3 Physics object reconstruction in ATLAS
ation (labeled as “2016 config”) and the MV2c20 tagger (“2015 config”). While theb-tagging efficiency is similar between the two configurations, the c-tagging rejection is significantly improved across the whole pTspectrum.
b-jet efficiency
0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95
b=77%
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ATLASSimulation Preliminary t
= 13 TeV, t s
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0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 1.06 1.08
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ATLASSimulation Preliminary t
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Figure 3.9:b-tagging efficiency (left) andc-jet rejection (right) evaluated intt simulated events. The MV2c10 and MV2c20 vaersions of the tagger are compared. [76].
3 The LHC and the ATLAS experiment
The direction is specified by the corresponding azimuthal angle,φmiss, defined as:
φmiss =tan−1(Eymiss/Emissx ).
The performance of reconstructingEmissT is evaluated both in data and MC simulation. This consists of evaluating the resolution and response for the reconstructedEmissT . Samples with and without real missing energy are used. This includeW→eνandZ →µµevents respectively.
The response gives an impression about how much the reconstructed EmissT differs from the expect-ation value. For events with low activity, the response is non-linear9 due to observation biases. These occur because the experimental conditions do not always allow for thepT reconstruction of all objects coming from the hard scatter and, additionally, all reconstructed pT contributions suffer from limited resolution. This effectively leads to a non-vanishing EmissT calculation even for events in which no un-detected particles were present.
TheEmissT resolution is defined as the width of the distribution ofEmissx(y) and the difference with respect to the true missing transverse momentum components. It was observed that the resolution worsens with increasing pile-up and also increases for events with highP
ET[78].
9A non-linear response depends on the truthEmissT or other quantities related to the hard scatter activity.
CHAPTER 4
Data and Monte Carlo Simulated Samples
In order to extract information from ppcollision data and test SM predictions, reliable MC simulated samples that reflect our knowledge of particle interaction and production must be used. By comparing the recorded data with these simulations, one can test the SM hypothesis, as well as search for new physics. This chapter starts with details about the dataset that was used for this analysis. The second half of the chapter is dedicated to MC simulations. Firstly, a brief overview of how MC simulation works is included. Details about the samples used in this analysis for modelling the signal and background processes are given in the last section.
4.1 Data sample
This analysis was performed on ppdata collected by the ATLAS detector during its 2015 and 2016 operations. In this time, a dataset larger than the full Run 1 dataset was collected. Figure4.1shows the total LHC delivered luminosity as well as the amount recorded by the ATLAS experiment. An efficiency of 93 % and 92 % was achieved for 2015 and 2016, respectively.
Each ATLAS dataset consists of severalruns. These are uninterrupted periods of time in which the detector is recording data. A unique run number is assigned at the start of the respective run. Typically an ATLAS run corresponds to one LHC cycle. After the beams that are circulating through the accelerator are dumped (safely terminated) and the energy is ramped down, a setup period follows in order to prepare for the next beam injection. A probe beam is circulated before the beams that will be used for physics. Once the physics beams are injected, their intensities are gradually increased until they reach the nominal operation point. Afterwards, the energy is ramped up until it reaches 6.5 TeV per beam. In preparation for the collisions, the beams are squeezed and adjusted. At this point, the LHC declares the physics beams as stable and proton–proton collision data can be recorded by the detector. In figure4.1, the LHC delivered luminosity is measured from the moment when stable beams are declared until a request is made to the experiments to switch to safe mode and prepare for beam dump.
An ATLAS run is usually started when the physics beam are injected and ends when the physics beams are dumped. However, the inner detectors undergo a warm-start procedure after stable beams are declared. This is needed for ramping up the high-voltage on the tracking detectors and turning on the pre-amplifiers of the pixel detectors. This procedure is one of the reasons why ATLAS records less luminosity than the amount delivered by the LHC. Another reason is the inefficiency of the data acquisition system.
4 Data and Monte Carlo Simulated Samples
Figure 4.1: Total integrated luminosity for the 2015 (left) and 2016 (right) operations [79].
The luminosity measurement in ATLAS is done by several dedicated detectors, such as the LUminos-ity measurement using a Cherenkov Integrating Detector (LUCID) or the Beam Control Monitor (BCM).
These measure the luminosity bunch-by-bunch. This can be done by event counting or hit counting. In event counting, every bunch crossing is scanned through a set of criteria in order to check if it is consist-ent with the occurrence of at least one inelastic collision and is categorised accordingly. Hit counting algorithms identify the number of detector signals that pass a preset threshold. An alternative method of determining the luminosity is the counting of well reconstructed events coming from processes that have a very precisely known cross-section, such asZ →µµ. Details about these procedures, along with descriptions of the ATLAS luminosity detectors can be found in [80] and [81].
However, the amount of data recorded by ATLAS is not the total luminosity used for physics analyses.
Agood run list(GRL) is compiled by data quality experts in order to identify the runs (and luminosity blocks1inside a run) for which the detector was fully operational. This analysis was performed on data passing all recommended quality criteria and selected based on the GRL for physics analysis. This corresponds to a total integrated luminosity of 36.1 fb−1, out of which 3.3 fb−1 have been recorded in 2015 and 32.8 fb−1in 2016.