Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques

AM Sirunyan, A Tumasyan, W Adam… - Journal of …, 2020 - iopscience.iop.org
At the CERN LHC [1], an efficient classification of hadronic decays of heavy standard-model
(SM) particles (objects) that are reconstructed within a single jet would provide a significant …

Identification techniques for highly boosted W bosons that decay into hadrons

CMS collaboration - arXiv preprint arXiv:1410.4227, 2014 - arxiv.org
In searches for new physics in the energy regime of the LHC, it is becoming increasingly
important to distinguish single-jet objects that originate from the merging of the decay …

[HTML][HTML] Towards an understanding of the correlations in jet substructure: Report of BOOST2013, hosted by the University of Arizona, 12th–16th of August 2013

D Adams, A Arce, L Asquith, M Backovic… - The European Physical …, 2015 - Springer
Over the past decade, a large number of jet substructure observables have been proposed
in the literature, and explored at the LHC experiments. Such observables attempt to utilize …

[HTML][HTML] Performance of top-quark and W W-boson tagging with ATLAS in Run 2 of the LHC

M Aaboud, G Aad, B Abbott, O Abdinov… - The European Physical …, 2019 - Springer
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks
and W bosons in pp collisions at ss= 13 TeV recorded by the ATLAS experiment at the Large …

Jet constituents for deep neural network based top quark tagging

J Pearkes, W Fedorko, A Lister, C Gay - arXiv preprint arXiv:1704.02124, 2017 - arxiv.org
Recent literature on deep neural networks for tagging of highly energetic jets resulting from
top quark decays has focused on image based techniques or multivariate approaches using …

Top tagging: a method for identifying boosted hadronically decaying top quarks

DE Kaplan, K Rehermann, MD Schwartz, B Tweedie - Physical review letters, 2008 - APS
A method is introduced for distinguishing top jets (boosted, hadronically decaying top
quarks) from light-quark and gluon jets using jet substructure. The procedure involves …

Jet flavor classification in high-energy physics with deep neural networks

D Guest, J Collado, P Baldi, SC Hsu, G Urban… - Physical Review D, 2016 - APS
Classification of jets as originating from light-flavor or heavy-flavor quarks is an important
task for inferring the nature of particles produced in high-energy collisions. The large and …

[HTML][HTML] Performance of jet substructure techniques for large-R jets in proton-proton collisions at TeV using the ATLAS detector

G Aad, T Abajyan, B Abbott, J Abdallah… - Journal of High Energy …, 2013 - Springer
A bstract This paper presents the application of a variety of techniques to study jet
substructure. The performance of various modified jet algorithms, or jet grooming …

A deep neural network to search for new long-lived particles decaying to jets

CMS collaboration - Machine Learning: Science and …, 2020 - iopscience.iop.org
A tagging algorithm to identify jets that are significantly displaced from the proton-proton (pp)
collision region in the CMS detector at the LHC is presented. Displaced jets can arise from …

[HTML][HTML] Optimisation of large-radius jet reconstruction for the ATLAS detector in 13 TeV proton–proton collisions

G Aad, B Abbott, DC Abbott, AA Abud, K Abeling… - The European Physical …, 2021 - Springer
Jet substructure has provided new opportunities for searches and measurements at the
LHC, and has seen continuous development since the optimization of the large-radius jet …