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We consider the factorized groomed jet mass distribution in inclusive jet processes using modified mass drop tagger (mMDT), corresponding to soft drop with the angular exponent $\beta =0$. A grooming procedure is implemented rather than…

High Energy Physics - Phenomenology · Physics 2019-03-27 Junegone Chay , Chul Kim

Machine learning enables unbinned, highly-differential cross section measurements. A recent idea uses generative models to morph a starting simulation into the unfolded data. We show how to extend two morphing techniques, Schr\"odinger…

High Energy Physics - Phenomenology · Physics 2025-06-25 Anja Butter , Sascha Diefenbacher , Nathan Huetsch , Vinicius Mikuni , Benjamin Nachman , Sofia Palacios Schweitzer , Tilman Plehn

We study top-tagging from an analytical QCD perspective focusing on the role of two key steps therein : a step to find three-pronged substructure and a step that places constraints on radiation. For the former we use a recently introduced…

High Energy Physics - Phenomenology · Physics 2021-10-27 Mrinal Dasgupta , Jack Helliwell

We construct a procedure to separate boosted Higgs bosons decaying into hadrons, from the background due to strong interactions. We employ the Lund jet plane to obtain a theoretically well-motivated representation of the jets of interest…

High Energy Physics - Phenomenology · Physics 2021-10-04 Charanjit K. Khosa , Simone Marzani

Multidisciplinary design optimization methods aim at adapting numerical optimization techniques to the design of engineering systems involving multiple disciplines. In this context, a large number of mixed continuous, integer and…

The performance of taggers for hadronically decaying top quarks and $W$ bosons in $pp$ collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape…

High Energy Physics - Experiment · Physics 2019-06-05 ATLAS Collaboration

We present the results of a model independent analysis, which systematically scans the data taken by CMS for deviations from the Standard Model predictions. Due to the minimal theoretical bias this approach is sensitive to a variety of…

High Energy Physics - Experiment · Physics 2015-06-03 Shivali Malhotra , Md. Naimuddin , Thomas Hebbeker , Arnd Meyer , Holger Pieta , Paul Papacz , Stefan Antonius Schmitz , Mark Olschewski

We investigate the consequences of models where dark sector quarks could be produced at the LHC, which subsequently undergo a dark parton shower, generating jets of dark hadrons that ultimately decay back to Standard Model hadrons. This…

High Energy Physics - Phenomenology · Physics 2023-08-16 Timothy Cohen , Jennifer Roloff , Christiane Scherb

We propose a robust method to identify anomalous jets by vetoing QCD-jets. The robustness of this method ensures that the distribution of the proposed discriminating variable (which allows us to veto QCD-jets) remains unaffected by the…

High Energy Physics - Phenomenology · Physics 2020-08-11 Tuhin S. Roy , Aravind H. Vijay

Multiple interactions between parton showers and the surrounding QCD matter are expected to underlie the strong medium-modifications of jet observables in ultra-relativistic heavy ion collisions at RHIC and at the LHC. Here, we note that…

High Energy Physics - Phenomenology · Physics 2017-08-23 A. Beraudo , J. G. Milhano , U. A. Wiedemann

In many prediction problems, we have extra information during training (for example, measurements that are expensive or slow to collect) that will not be available when the model is deployed. A common strategy is to first train a model that…

Machine Learning · Statistics 2026-05-25 Jiahao Shi , Omar Hagrass , Jason M. Klusowski

Studying heavy-flavor jets in pp collision is important since they can test pQCD calculations and be used as a reference for heavy-ion collisions. Jets in this analysis are reconstructed from charged particles using the…

High Energy Physics - Phenomenology · Physics 2025-04-28 Hadi Hassan , Neelkamal Mallick , D. J. Kim

Jet substructure has emerged as a critical tool for LHC searches, but studies so far have relied heavily on shower Monte Carlo simulations, which formally approximate QCD at leading-log level. We demonstrate that systematic higher-order QCD…

High Energy Physics - Phenomenology · Physics 2012-09-18 Ilya Feige , Matthew D. Schwartz , Iain W. Stewart , Jesse Thaler

We briefly review common tools and methods to identify boosted, hadronically decaying top quarks at the LHC experiments. This includes generic jet substructure variables, specific top identification algorithms, and recent developments in…

High Energy Physics - Phenomenology · Physics 2018-01-15 Gregor Kasieczka

This paper explores unsupervised learning of parsing models along two directions. First, which models are identifiable from infinite data? We use a general technique for numerically checking identifiability based on the rank of a Jacobian…

Machine Learning · Statistics 2012-06-15 Daniel Hsu , Sham M. Kakade , Percy Liang

We describe a method to measure and subtract the incoherent component of energy flow arising from multiple interactions from jet shape/substructure observables of ultra-massive jets. The amount subtracted is a function of the jet shape…

High Energy Physics - Phenomenology · Physics 2013-05-29 Raz Alon , Ehud Duchovni , Gilad Perez , Aliaksandr P. Pranko , Pekka K. Sinervo

Several boosted jet techniques use jet shape variables to discriminate the multi-pronged signal from Quantum Chromodynamics backgrounds. In this paper, we provide a first-principles study of an important class of jet shapes all of which put…

High Energy Physics - Phenomenology · Physics 2016-09-23 Mrinal Dasgupta , Lais Schunk , Gregory Soyez

At the LHC, tagging boosted heavy particle resonances which decay hadronically, such as top quarks and Higgs bosons, can play an essential role in new physics searches. In events with high multiplicity, however, the standard approach to tag…

High Energy Physics - Phenomenology · Physics 2015-07-21 Koichi Hamaguchi , Seng Pei Liew , Martin Stoll

Model merging has achieved significant success, with numerous innovative methods proposed to enhance capabilities by combining multiple models. However, challenges persist due to the lack of a unified framework for classification and…

Machine Learning · Computer Science 2025-03-13 Wei Ruan , Tianze Yang , Yifan Zhou , Tianming Liu , Jin Lu

ML models have errors when used for predictions. The errors are unknown but can be quantified by model uncertainty. When multiple ML models are trained using the same training points, their model uncertainties may be statistically…

Machine Learning · Statistics 2025-09-23 Xiaoping Du
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