Search for new phenomena in two-body invariant mass distributions using unsupervised machine learning for anomaly detection at $\sqrt{s}=13$ TeV with the ATLAS detector

Abstract

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 $pp$ collisions at $\sqrt{s}=13$ 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 $b$-jet and either one lepton ($e$, $\mu$), photon, or second light jet or $b$-jet in the anomalous regions. No significant deviations from the background hypotheses are observed.

33 pages in total, author list starting page 16, 4 figures. All figures including auxiliary figures are available at: http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/EXOT-2022-07

References in corpus (34)

• The anti-k_t jet clustering algorithm
• An Introduction to PYTHIA 8.2
• FastJet user manual
• Asymptotic formulae for likelihood-based tests of new physics
• The ATLAS Simulation Infrastructure
• Performance of the ATLAS Trigger System in 2015
• Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1
• Performance of pile-up mitigation techniques for jets in $pp$ collisions at $\sqrt{s}=8$ TeV using the ATLAS detector
• Electron and photon performance measurements with the ATLAS detector using the 2015-2017 LHC proton-proton collision data
• Trial factors for the look elsewhere effect in high energy physics
• Dark Matter Benchmark Models for Early LHC Run-2 Searches: Report of the ATLAS/CMS Dark Matter Forum
• Jet reconstruction and performance using particle flow with the ATLAS Detector
• Performance of electron and photon triggers in ATLAS during LHC Run 2
• Muon reconstruction and identification efficiency in ATLAS using the full Run 2 $pp$ collision data set at $\sqrt{s}=13$ TeV
• Searching for New Physics with Deep Autoencoders
• Anomaly Detection for Resonant New Physics with Machine Learning
• Measurements of Higgs boson properties in the diphoton decay channel with 36 fb${}^{-1}$ of $pp$ collision data at $\sqrt{s}=13$ TeV with the ATLAS detector
• Learning New Physics from a Machine
• Search for new resonances in mass distributions of jet pairs using 139 fb${}^{-1}$ of $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector
• QCD or What?
• Novelty Detection Meets Collider Physics
• ATLAS flavour-tagging algorithms for the LHC Run 2 $pp$ collision dataset
• Dijet resonance search with weak supervision using $\sqrt{s}=13$ TeV $pp$ collisions in the ATLAS detector
• Guiding New Physics Searches with Unsupervised Learning
• Variational Autoencoders for New Physics Mining at the Large Hadron Collider
• The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider
• A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment
• Learning the latent structure of collider events
• LHC Signals from Cascade Decays of Warped Vector Resonances
• Measurements of inclusive and differential fiducial cross-sections of $t\bar{t}\gamma$ production in leptonic final states at $\sqrt{s}$ = 13 TeV in ATLAS
• On the behaviour of composite resonances breaking lepton flavour universality
• Event-based anomaly detection for new physics searches at the LHC using machine learning
• Imaging particle collision data for event classification using machine learning
• Search for new phenomena in multi-body invariant masses in events with at least one isolated lepton and two jets using $\sqrt{s}=13$ TeV proton-proton collision data collected by the ATLAS detector

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• Solving Key Challenges in Collider Physics with Foundation Models
• Search for new physics in final states with semi-visible jets or anomalous signatures using the ATLAS detector
• Semi-visible jets, energy-based models, and self-supervision
• Isolating Unisolated Upsilons with Anomaly Detection in CMS Open Data
• Foundations of automatic feature extraction at LHC--point clouds and graphs
• Weakly supervised anomaly detection for resonant new physics in the dijet final state using proton-proton collisions at $\sqrt{s}=13$ TeV with the ATLAS detector
• 1 Particle - 1 Qubit: Particle Physics Data Encoding for Quantum Machine Learning
• A note on blind technique for new physics searches in particle physics
• Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHC
• Anomaly preserving contrastive neural embeddings for end-to-end model-independent searches at the LHC
• Search for Beyond the Standard Model physics with anomaly detection in multilepton final states in $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector
• Search for resonances decaying to an anomalous jet and a Higgs boson in proton-proton collisions at $\sqrt{s}$ = 13 TeV
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• Weakly supervised anomaly detection with event-level variables