This project focuses on developing a graph neural network (GNN) to classify b-jets at the LHCb experiment. Accurate identification of jet flavours is crucial for event reconstruction. Utilizing deep learning, specifically GNNs, will improve the accuracy and efficiency of this classification process. Additionally, this GNN will be applied for classification of c-jets and fat jets.
Vector boson scattering (VBS) is an important test to experimentally probe the electroweak symmetry breaking mechanism. In order to measure the boson polarisation in VBS signal, there is a need to optimize the event and the selection to maximize the sensitivity. In this poster, we report the first result of the analysis and the current modelings.
This poster focuses on improving vertex reconstruction in high-pile-up scenarios at the HL-LHC using hit-time information. The study compares algorithms with and without time data, demonstrating improved accuracy and reduced CPU usage. The findings highlight the benefits of integrating time data into vertex-finding processes.
Status of 3D tracking with the Downstream Stations of the SND@LHC detector
An overview of the ATLAS Trigger System and the Trigger Menu, focusing on some of the operational tasks that ensure high-quality data and the different procedures used to optimise the system.
Crystal collimation is a type of advanced beam cleaning where bent silicon crystals are used to steer beam halo particles toward an absorber. Crystals are materials with a highly organized atomic structure, so when charged particles interact with a crystal at the right impact conditions, they become trapped in the potential well generated by neighboring crystalline planes. These particles are...
In this project, I optimized our approach by parallelizing the execution of test without having to rebuild the Docker image in every run. The Docker image we build contains all necessary dependencies, GPU drivers (if applicable), and the Xsuite packages in the versions we need to test. Previously, Docker images were built separately on each test runner machine, a process that was inefficient...
Using ZFit indirect constraint of the Charm-Yukawa coupling strength by using a maximum likelihood fit to analyse the Higgs Gamma Gamma decay. Higgs Production depends on the Charm-Yukawa coupling strength explicitly, which will affect the shape of the differential cross-section. The Likelihood is modelled using a Multivariate Gaussian which depends on the Charm-Yukawa coupling strength.
This poster investigates AtlFast3 (AF3) and Geant4 (FullSim) Monte Carlo simulations for charged and doubly charged Higgs boson searches in the same-sign WW and WZ channels. The validity of AF3 is investigated, with the final aim of the project being to optimize the analysis as a charged Higgs boson search in the vector-boson fusion (VBF) channel.
Discover the critical role of time in enhancing the LHCb ECAL Upgrade II Clustering. Explore innovative machine learning techniques for precise photon reconstruction, energy measurement, and improved particle identification. Learn about advancements in scintillating modules and radiation tolerance.
The Standard Model predicts Lepton Flavour Universality (LFU), where all lepton flavors should interact with equal strength. Testing LFU involves comparing the ratios of branching fractions in leptonic and semileptonic decays, with any deviation suggesting new physics beyond the Standard Model. This project aims to explore how LFU can be tested using semileptonic baryon decays. By generating...
The Search for Hidden Particles (SHiP) experiment aims to investigate hidden particles beyond the Standard Model of particle physics. One of the critical components of this experiment is the decay vessel, where particles decay into measurable products. Designing and optimizing this decay vessel is crucial to ensure its structural integrity, efficiency, and effectiveness in the experiment. This...
This project consists of developing a web application for the LAr Operations team of the ATLAS detector at the LHC.
The purpose is to to facilitate real-time visualisation of data allowing the team to predict problems in the front-end hardware, perform preventive replacements and avoid data loss. The application is developed using Django (Python), Bootstrap, AJAX and is also integrated with...
