Increasing Multilingualism in ATLAS’ Science Communication

Despite modern particle physics being an international endeavour, the vast majority of its educational material is only published in English. By making material available in other languages, physicists can make inroads with new audiences – especially those very young or very old – in their home countries. The ATLAS Collaboration has published colouring books, a teaching guide, activity sheets, fact sheets and cheat sheets aimed at communicating science to a non-expert audience. An effort is underway to translate this content into as many languages as possible, taking advantage of the countless multilingual members of the collaboration. Currently, all of this content is available in at least two languages other than English, with the ATLAS Colouring Book being the one available in the most languages (21 so far). The reach of this multilingual content is presented

Search for di-jet resonances along with an isolated charged lepton at sqrt(s)=13 TeV pp collision with the ATLAS detector

A search for dijet resonances in events with identified leptons has been performed using the full Run 2 data collected in pp collisions at sqrt(s)=13 TeV with the ATLAS detector, corresponding to an integrated luminosity of 139 fb^-1. The dijet invariant-mass (mjj) distribution from events with at least one isolated electron or muon was probed in the range of 0.22<mjj<6.3 TeV. The analysis probes much lower mjj than traditional inclusive dijet searches and is sensitive to a large range of new physics models in association with a final-state lepton. As no statistically significant deviation from the Standard Model background hypothesis was found, limits were set on contributions from generic gaussian signals and on various beyond-the-Standard Model (BSM) scenarios including the Sequential Standard Model, a charged Higgs boson model, a simplified Dark Matter model etc. It has also been studied that the multi-body invariant masses such as three- and four-body invariant mass distributions constructed from jets and leptons while following the same analysis strategy provide sensitivity to wide ranges of Physics, including many BSM scenarios

Summer Project Report

In this project we mainly prepared and classified several materials, important links for understanding accelerators for different age group. Accelarators now-a-days are very much important tool for not only particle physics laboratories but also for the common people for its extended applications. So, it is very much important to make people know the basics of accelerators, its basic principles, objectives and different varieties. As different age group of people have different level of understandings, so it was necessary to develop materials differently for categories based on age group. Hence, for three different categories we have separately prepared different presentations and collected important all the useful weblinks, videos, animations, games etc. related to accelerators and put them to our new webpage : https://twiki.cern.ch/twiki/bin/view/Main/Materia

Search for new physics in multi-body invariant masses in dijet events with an isolated lepton in pp collisions at sqrt(s)=13 TeV with the ATLAS detector

A search for resonances in events with at least one isolated charged lepton (electron or muon) is performed using 139 fb^-1 of sqrt(s)=13 TeV proton-proton collision data recorded by the ATLAS detector at the LHC. Deviations from Standard Model predictions are tested in three- and four-body invariant mass distributions constructed from jets and leptons. The study reports first model-independent limits on generic resonances characterized by cascade decays of particles leading to multiple jets and leptons in the final state. Model-independent limits are calculated using Gaussian shapes with different widths. The multi-body invariant masses are then used to set upper limits at a 95% confidence level on various beyond the standard model physics scenarios

Search for new phenomena in two-body invariant mass distributions using unsupervised machine learning for anomaly detection with the ATLAS detector

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb−1 of collisions at √ = 13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or -jet and either one lepton (, ), photon, or second light jet or -jet in the anomalous regions. No significant deviations from the background hypotheses are observed

Searches for new physics with leptons using the ATLAS detector

Many different theories beyond the Standard Model (SM) predict that new physics will manifest itself by decaying into final states involving leptons. Leptoquarks are predicted by many new physics theories to describe the similarities between the lepton and quark sectors of the SM. Right-handed Ws and heavy-neutrinos are also predicted by many extensions of the SM in the gauge sector, and lepton flavour violation could manifest itself by decays of new gauge bosons into leptons of different flavours. This talk will present the most recent 13 TeV results on the searches for leptoquarks with the ATLAS detector, covering flavour-diagonal and cross-generational final states, as well as the latest searches for lepton-flavour violating Z' and heavy neutrinos arising from left-right symmetric models

ADFilter&mdash;A Web Tool for New Physics Searches with Autoencoder-Based Anomaly Detection Using Deep Unsupervised Neural Networks

A web-based tool called ADFilter (short for Anomaly Detection Filter) was developed to process collision events using autoencoders based on a deep unsupervised neural network. The autoencoders are trained on a small fraction of either collision data or Standard Model (SM) Monte Carlo simulations. The tool calculates loss distributions for input events, helping to determine the degree to which the events can be considered anomalous with respect to the SM events used for training. Therefore, it can be used for new physics searches in collider experiments. Real-life examples are provided to demonstrate how the tool can be used to reinterpret existing results from the Large Hadron Collider (LHC), with the goal of significantly improving exclusion limits. This tool is expected to mitigate the &ldquo;reproducibility crisis&rdquo; associated with various machine learning techniques, as it can incorporate machine learning approaches from third-party publications, making them accessible to the general public