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In this study, we introduce the More-Interaction Particle Transformer (MIParT), a novel deep learning neural network designed for jet tagging. This framework incorporates our own design, the More-Interaction Attention (MIA) mechanism, which…

High Energy Physics - Phenomenology · Physics 2024-09-27 Yifan Wu , Kun Wang , Congqiao Li , Huilin Qu , Jingya Zhu

A search is conducted for standard model Higgs bosons with large transverse momentum ($p_\mathrm{T}$) decaying to bottom quark pairs and produced in association with a hadronically decaying W or Z boson at the LHC. The result is based on a…

High Energy Physics - Experiment · Physics 2026-01-12 CMS Collaboration

This paper reports a detailed study of techniques for identifying boosted, hadronically decaying $W$ bosons using 20fb$^{-1}$ of proton-proton collision data collected by the ATLAS detector at the LHC at a centre-of-mass energy $\sqrt{s} =$…

High Energy Physics - Experiment · Physics 2016-03-24 ATLAS Collaboration

A new algorithm for the identification of boosted, hadronically decaying, heavy particles at the LHC is presented. The algorithm is based on the known procedure of jet clustering with variable distance parameter $R$ and adapts the jet size…

High Energy Physics - Phenomenology · Physics 2016-11-10 Tobias Lapsien , Roman Kogler , Johannes Haller

A search for new massive particles decaying into a pair of Higgs bosons in proton-proton collisions at a center-of-mass energy of 13 TeV is presented. Data were collected with the CMS detector at the LHC, corresponding to an integrated…

High Energy Physics - Experiment · Physics 2019-10-28 CMS Collaboration

We demonstrate that the classification of boosted, hadronically-decaying weak gauge bosons can be significantly improved over traditional cut-based and BDT-based methods using deep learning and the jet charge variable. We construct binary…

High Energy Physics - Phenomenology · Physics 2020-03-25 Yu-Chen Janice Chen , Cheng-Wei Chiang , Giovanna Cottin , David Shih

International Linear Collider (ILC) is a next-generation $e^+e^-$ linear collider to explore Beyond-Standard-Models by precise measurements of Higgs bosons. Jet flavor tagging plays a vital role in the ILC project by identification of $H\to…

High Energy Physics - Experiment · Physics 2024-11-13 Risako Tagami , Taikan Suehara , Masaya Ishino

A search for a heavy resonance decaying into a top quark and a W boson in proton-proton collisions at $\sqrt{s} =$ 13 TeV is presented. The data analyzed were recorded with the CMS detector at the LHC and correspond to an integrated…

High Energy Physics - Experiment · Physics 2022-08-09 CMS Collaboration

The distribution of particles inside hadronic jets produced in the decay of boosted $W$ and $Z$ bosons can be used to discriminate such jets from the continuum background. Given that a jet has been identified as likely resulting from the…

High Energy Physics - Experiment · Physics 2016-06-01 ATLAS Collaboration

Jet flavour tagging is crucial in experimental high-energy physics. A tagging algorithm, DeepJetTransformer, is presented, which exploits a transformer-based neural network that is substantially faster to train than state-of-the-art graph…

High Energy Physics - Experiment · Physics 2025-02-11 Freya Blekman , Florencia Canelli , Alexandre De Moor , Kunal Gautam , Armin Ilg , Anna Macchiolo , Eduardo Ploerer

Recently, there has been a growing focus on the search for anomalous objects beyond standard model (BSM) signatures at the Large Hadron Collider (LHC). This study investigates novel signatures involving highly collimated photons, referred…

High Energy Physics - Phenomenology · Physics 2024-01-30 Xiaocong Ai , William Y. Feng , Shih-Chieh Hsu , Ke Li , Chih-Ting Lu

A search for a massive resonance decaying into a pair of standard model Higgs bosons, in a final state consisting of two b quark-antiquark pairs, is performed. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV…

High Energy Physics - Experiment · Physics 2018-04-13 CMS Collaboration

Deep Learning approaches are becoming the go-to methods for data analysis in High Energy Physics (HEP). Nonetheless, most physics-inspired modern architectures are computationally inefficient and lack interpretability. This is especially…

Computational Physics · Physics 2023-01-31 Jose M Munoz , Ilyes Batatia , Christoph Ortner

We develop an algorithm based on an interaction network to identify high-transverse-momentum Higgs bosons decaying to bottom quark-antiquark pairs and distinguish them from ordinary jets that reflect the configurations of quarks and gluons…

A search is performed for a heavy scalar resonance X decaying to a Higgs boson (H) and a Higgs-like scalar boson (Y) in the two bottom quark (H $\to$ $\mathrm{b\bar{b}}$) and four quark (Y $\to$ VV $\to$ 4q) final state, where V denotes a W…

High Energy Physics - Experiment · Physics 2026-02-03 CMS Collaboration

A search is performed for narrow resonances decaying to final states of two jets, with at least one jet originating from a b quark, in proton-proton collisions at $\sqrt{s}$ = 13 TeV. The data set corresponds to an integrated luminosity of…

High Energy Physics - Experiment · Physics 2023-07-17 CMS Collaboration

We apply gradient boosting machine learning techniques to the problem of hadronic jet substructure recognition using classical subjettiness variables available within a common parameterized detector simulation package DELPHES. Per-jet…

High Energy Physics - Experiment · Physics 2024-01-25 Petr Baroň , Jiří Kvita , Radek Přívara , Jan Tomeček , Rostislav Vodák

A deep-learning approach based on the transformer architecture is developed to distinguish between jets originating from quarks and gluons. The algorithm operates on jets with transverse momentum $p_{\text{T}} > 20$ and pseudorapidity…

High Energy Physics - Experiment · Physics 2025-12-04 ATLAS Collaboration

Future electron-positron colliders will play a leading role in the precision measurement of Higgs boson couplings which is one of the central interests in particle physics. Aiming at maximizing the performance to measure the Higgs couplings…

High Energy Physics - Phenomenology · Physics 2022-07-20 So Chigusa , Shu Li , Yuichiro Nakai , Wenxing Zhang , Yufei Zhang , Jiaming Zheng

We apply both cut-based and machine learning techniques using the same inputs to the challenge of hadronic jet substructure recognition, utilizing classical subjettiness variables within the Delphes parameterized detector simulation…

High Energy Physics - Phenomenology · Physics 2024-10-21 Jiří Kvita , Petr Baroň , Monika Machalová , Radek Přívara , Rostislav Vodák , Jan Tomeček