Searching for dark jets with displaced vertices using weakly supervised machine learning

Abstract

If "dark quarks" from a confining hidden sector are produced at the LHC, they will shower and hadronize to dark sector hadrons, which may decay back to Standard Model particles within the detector, possibly resulting in a collimated spray of particles resembling a QCD jet. In this work we address scenarios in which dark hadrons decay with a measurable small displacement, such that the relevant background is dominated by heavy-flavor jets. Since dark sector parameters are largely unconstrained, and the precise properties of a dark QCD-like theory are difficult to compute or simulate reliably in any case, model-independent, data-based searches for such scenarios are desirable. We explore a search strategy employing weakly supervised machine learning to search for anomalous jets with displaced vertices. The method is tested on several toy signals, demonstrating the feasibility of such a search. Our approach has potential to outperform simple cut-based methods in some cases and has the advantage of being more model-independent.

arXiv comment30 pages, 14 figures; v2: minor improvements of presentation; published version

References in corpus (41)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations
• The anti-k_t jet clustering algorithm
• An Introduction to PYTHIA 8.2
• DELPHES 3, A modular framework for fast simulation of a generic collider experiment
• Echoes of a Hidden Valley at Hadron Colliders
• Description and performance of track and primary-vertex reconstruction with the CMS tracker
• Parton distributions with QED corrections
• Classification without labels: Learning from mixed samples in high energy physics
• Searching for New Physics with Deep Autoencoders
• Extending the Bump Hunt with Machine Learning
• Emerging Jets
• 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
• Semi-visible Jets: Dark Matter Undercover at the LHC
• QCD or What?
• Dijet resonance search with weak supervision using $\sqrt{s}=13$ TeV $pp$ collisions in the ATLAS detector
• The Scale of Dark QCD
• Visible Effects of Invisible Hidden Valley Radiation
• Learning to Classify from Impure Samples with High-Dimensional Data
• LHC Searches for Dark Sector Showers
• Autoencoders for unsupervised anomaly detection in high energy physics
• Tag N' Train: A Technique to Train Improved Classifiers on Unlabeled Data
• Weakly Supervised Classification in High Energy Physics
• Variational Autoencoders for Anomalous Jet Tagging
• Simulation-Assisted Decorrelation for Resonant Anomaly Detection
• Tagging a jet from a dark sector with Jet-substructures at colliders
• Strongly interacting dark sectors in the early Universe and at the LHC through a simplified portal
• (Machine) Learning to Do More with Less
• Search for new particles decaying to a jet and an emerging jet
• Search for diboson resonances with boson-tagged jets in $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector
• Casting a graph net to catch dark showers
• Autoencoders for Semivisible Jet Detection
• Search for massive resonances decaying into WW, WZ or ZZ bosons in proton-proton collisions at sqrt(s) = 13 TeV
• Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection
• Dark matter in Hidden Valley models with stable and unstable light dark mesons
• Search for resonant production of strongly coupled dark matter in proton-proton collisions at 13 TeV
• Topological Obstructions to Autoencoding
• Jet Substructure from Dark Sector Showers
• Classification of dark pion multiplets as dark matter candidates and collider phenomenology
• Measurement of the flavour composition of dijet events in pp collisions at sqrt{s}=7 TeV with the ATLAS detector
• Exploring Jet Substructure in Semi-visible jets

Cited by in corpus (6)

• Dark Sector Glueballs at the LHC
• Emerging jet probes of strongly interacting dark sectors
• Equivariant, Safe and Sensitive -- Graph Networks for New Physics
• Search for new physics in final states with semi-visible jets or anomalous signatures using the ATLAS detector
• Learnable cut flow for high energy physics
• Trials Factor for Semi-Supervised NN Classifiers in Searches for Narrow Resonances at the LHC