Initiation to the Higgs to Dark Photon analysis

framework

Author: Abdulla Mahboub (United Arab Emirates University)

Supervisor: Dr. Rachik Soualah

Report submitted for the Online CERN Summer Student Program 2021

August 6, 2021

Dubai, United Arab Emirates

1 Introduction

In Physics, the Standard Model (SM) is a theory that aims to understand fun-

damental particles and how they interact. The model is successful in multiple

aspects as it helps in understanding three of the four fundamental forces (Elec-

tromagnetic, Strong Force, Weak Force). However, it fails to properly explain

gravity. Furthermore, the SM does not account for dark matter, which makes

up most of the universe (85%). The Large Hadron Collider (LHC) at CERN

aims to test the SM and develop a better understanding of what the universe is

made of. In 2012, the Higgs Boson, was detected at the LHC, providing a leap

in particle physics. The LHC provides a way to study dark matter through the

decay of the Higgs Boson. Since dark matter particles cannot be detected by

the detectors, the missing energy in collisions could be key to observing these

particles [1,2]. In this report a small description of the LHC and ATLAS detec-

tor (Section 2) is given along with a description of the framework setup of the

Higgs to Dark Photon Analysis (section 3). Finally, a conclusion of the results

is given (Section 4).

2 LHC and ATLAS2.1 LHC

The Large Hadron Collider (LHC) is a particle accelerator built underground

that has a circumference of 27 km. Within it stands two beam pipes used to

accelerate hadrons so that they can collide. These tubes are kept in an ultrahigh

vacuum and are subjected to a strong magnetic field kept at a temperature of

-271.3°C to provide more strength to the field and direct the beams properly.

Things are kept cool via a liquid helium system. These beams then collide at

four particle detectors, ATLAS, CMS, ALICE and LHCb [3]. Figure 1 shows a

LHC diagram.

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Figure 1: LHC diagram [4]

2.2 ATLAS

Located at the Large Hadron Collider at CERN, ATLAS (A Toroidal LHC Ap-

paratuS) is a general-purpose particle physics experiment that aims to detect

particles through collisions. It is 46 metres long and 25 metres in diameter, with

a weight of 7000 tonnes. Figure 2 below shows the detector design. Within the

detector, beams of particles that move up to 99.999999% of the speed of light

collide at the centre, with over a billion collisions per second. However, not all

these interactions are interesting to study.

The detector consists of multiple parts. These are the Inner Detector, Calorime-

ter, Magnet System, and Muon Spectrometer as shown in Figure 2. First, the

Inner Detector. This is a highly sensitive system of detectors that measures

the momentum, direction, and charge of particles produced in proton-proton

collisions. Second, the Calorimeter. This component measures the energy of

the particles as they go through the detector. It consists of an Electromag-

netic calorimeter, which measures the energy of electrons and photons, and

a Hadronic calorimeter, which measures energy of hadrons. Third, the Mag-

net System, which consists of solenoidal and toroidal magnet systems that are

cooled down to 4.5 K to enhance the magnetic field. This system bends the

charged particle trajectories to measure momentum and charge. Fourth, the

Muon Spectrometer. This component is used to detect Muons, which cannot

be detected via the calorimeter and inner detectors [5].

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Figure 2: ATLAS Detector diagram [5]

3 ZH Dark Photon Analysis Framework Setup3.1 Computing framework

The framework used for the analysis is ROOT based. The analysis framework

takes in xAODs (analysis object data). Next, appropriate cuts and data skim-

ming is done. Then, this is used to produce histograms and plot the data. In the

analysis done, the STAnalysisCode framework is used for MiniNtuples produc-

tion. Then the STPostProcessing framework is used to process the MiniNtuples

to produce MicroNtuples, histograms and plots used for the study.

It is important to note that we do not use MiniNtuples because of the large

file size (TB). However, we run them while they are on the GRID and produce

smaller files for the background and signal processes and data. These are the

MicroNtuples .

During the ZH dark photon analysis framework tutorial, the steps mentioned

in the above paragraphs were done. First, the framework setup was done, and

the ATLAS environment setup was called. Appropriate directories were created

for the analysis next. In this tutorial however, there was no need to produce

MiniNtuples and MicroNtuples because they were made available for us. The

remaining of the work went into appropriately plotting the data.

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3.2 Physics signal and background contributions

The signal we aim to look for in this analysis is the decay from Higgs boson

to dark Photon (H → γγd). Once we obtain the MiniNtuples containing the

branches and events, we skim the data to produce the MicroNtuples. The data

is processed using (ZHdarkPhAnalysisAlg) which does the skimming needed for

the study. The job is run using condor batch.

In this analysis we compare Monte Carlo samples and data obtained in order to

properly conduct the study. An important factor to consider is the background

events involved in this study, as they have an impact on it. Background events

are events that are similar to the signal we aim to study. In this specific study,

background events can be seen in the plots shown in the next section of this

report.

3.3 Plots

The final part of this analysis was to produce the plots. In this step, there are im-

portant macros that are used to obtain the final graphs. These are plotEvent.py,

CutsDef.py, Input.py, and drawStack.py. The first is the main macro used for

plotting (creates root file). The second is used to define the appropriate cuts for

the signal and background needed for the study. The third is used for reading

the microNtuples and defining the signal and background samples. The fourth

is the one used for producing the plots and labelling each axis. We obtain differ-

ent graphs while plotting the data against different variables, such as transverse

mass, to properly study the data. The graphs are shown below (Figure 3).

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Figure 3: Plots

4 ConclusionEach of the plots gives us an insight into the data. For example, towards the

bottom of each graph we see the ratio (Data/Bkg) which helps in identifying

any deviations to further interpret the result. In addition, the data is plotted

corresponding to an integrated luminosity of 36 inverse femtobarns. All in all,

this analysis framework tutorial has provide me as a summer student, a very

general overview and insight into some of the basics of how data analysis works,

how to use the terminal to achieve the required outcome, and how to understand

the plots.

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References

[1] DOE Explains...the standard model of particle physics. Energy.gov. (n.d.).

https://www.energy.gov/science/doe-explainsthe-standard-model-particle-physics.

[2] ATLAS probes dark matter using the Higgs boson. CERN. (n.d.).

https://home.cern/news/news/physics/atlas-probes-dark-matter-using-higgs-boson.

[3] The large hadron collider. CERN. (n.d.).

https://home.cern/science/accelerators/large-hadron-collider.

[4] Amos, J. (2016, April 20). Large hadron collider can be ’world’s biggest rain

meter’. BBC News.

https://www.bbc.com/news/science-environment-36094282.

[5] Detector amp; Technology. ATLAS Experiment at CERN. (n.d.).

https://atlas.cern/discover/detector.

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