Experimental Particle Physics
Experimental particle physics is the practical way to look for the fundamental components of matter (like quarks). An important tool for the experimental particle physicist is the particle accelerator which speeds up the fundamental particles close to the light speed. Particles then collide together to reveal the mystery inside the matters. Other crucial tools in this field are detector/interaction simulators, data driven techniques, and statistical packages. The world’s major particle physics laboratories are: CERN, DESY, Fermilab, and SLAC.
Theoretical Particle Physics
Theoretical particle physics is the development of models for describing fundamental particles and their interactions. This includes testing and validating the Standard Model (SM) and the beyond Standard Models (like Supersymmetry). Particles are described as excitations of quantum fields in the Standard Model. Crucial tools in the arsenal of the theoretical particle physicist are group theory, quantum field theory, and effective field theory. In general, theorists attempt to construct a unified quantum mechanics and general relativity.
LHC accelerator and ATLAS detector
Using particle accelerators to produce and detect new particles
The Large Hadron Collider (LHC) is the world’s largest and highest-energy particle collider which was built by the European Organization for Nuclear Research (CERN). It is a circular hadron (like proton) accelerator, located in a 26.7 km long underground tunnel. ATLAS is the largest of the LHC detectors, measuring 44 meters in high, and 25 meters in height. The ATLAS physics program covers variety of topics such as discovery of Higgs boson, measuring the SM parameters, and studying of beyond the Standard Model physics. This collaboration includes over 10,000 scientists and hundreds of universities and laboratories, as well as more than 100 countries.
How it works:
Machine Learning model modifies its rules based on the errors it measures
Data Preprocessing
Summary of root to CSV file conversion
Model Training and Overfitting Check
Neural network and Random forest models
Model Comparison
Evaluating models and picking the model with the highest precision and recall
Machine Learning application in detecting Beyond the Standard Model signals
ATLAS Projects
SUSY Electroweak multi-B
The search is performed for Higgsino pair production, with decay to Higgs or Z boson, focusing on the final states with four bottom quarks and ETmiss. Data collected from 2015 to 2018 is used and Higgsino masses of less than 2.1 TeV are excluded at 95% confidence level.
Key words: Higgsino, Neutralino, Low and High mass regions, Exclusion fit
SUSY Strong multi-B
The search is performed for gluino pair production, leading to the final states with multiple top and/or bottom quarks and ETmiss. 139 fb-1 integrated luminosity in this analysis is collected with the ATLAS detector from 2015 to 2018. Gluino masses of less than 2.3 TeV are excluded at 95% confidence level.
Key words: Gluino, Neutralino, Cut-and -count, Neural net, Exclusion fit
ATLAS LAr Data Quality
To use the best quality LAr calo data, with the lowest possible level of data rejection in physics analyses, a data quality with advanced monitoring system is designed. In this method, flagging scheme are applied (at both offline and online level) to identify noisy channels.
Key words: Noisy channels, UPD soft, LTTNK package
Online Calo desk shift
The person on shift is the first person to determine if the data taking is good and the best person to correct the situation if the data is bad. It’s the kind of responsibility for the shifters in the ATLAS control room.