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In the top quark pair production in association with the Higgs boson decaying to a b quark pair t-tbar H (b-bbar), the final state has an irreducible nonresonant background from the production of a top quark pair in association with a b…

High Energy Physics - Experiment · Physics 2020-12-30 Jieun Choi , Tae Jeong Kim , Jongwon Lim , Jiwon Park , Yeonsu Ryou , Juhee Song , Soohyun Yun

Heavy flavor hadrons, i.e. those containing charm and bottom quarks, will be abundantly produced at the LHC and are important probes of the Quark-Gluon Plasma (QGP). Of particular interest is the investigation of parton energy loss in the…

Nuclear Experiment · Physics 2016-11-25 Mark Heinz

Run-2 of the Large Hadron Collider (LHC) will provide new challenges to track and vertex reconstruction with higher energies, denser jets and higher rates. Therefore the ATLAS experiment has constructed the first 4-layer Pixel Detector in…

Instrumentation and Detectors · Physics 2016-08-30 Karolos Potamianos

An algorithm is described for tagging the flavour content at production of neutral $B$ mesons in the LHCb experiment. The algorithm exploits the correlation of the flavour of a $B$ meson with the charge of a reconstructed secondary charm…

High Energy Physics - Experiment · Physics 2016-08-10 LHCb collaboration , R. Aaij , B. Adeva , M. Adinolfi , A. Affolder , Z. Ajaltouni , S. Akar , J. Albrecht , F. Alessio , M. Alexander , S. Ali , G. Alkhazov , P. Alvarez Cartelle , A. A. Alves , S. Amato , S. Amerio , Y. Amhis , L. An , L. Anderlini , J. Anderson , G. Andreassi , M. Andreotti , J. E. Andrews , R. B. Appleby , O. Aquines Gutierrez , F. Archilli , P. d'Argent , A. Artamonov , M. Artuso , E. Aslanides , G. Auriemma , M. Baalouch , S. Bachmann , J. J. Back , A. Badalov , C. Baesso , W. Baldini , R. J. Barlow , C. Barschel , S. Barsuk , W. Barter , V. Batozskaya , V. Battista , A. Bay , L. Beaucourt , J. Beddow , F. Bedeschi , I. Bediaga , L. J. Bel , V. Bellee , N. Belloli , I. Belyaev , E. Ben-Haim , G. Bencivenni , S. Benson , J. Benton , A. Berezhnoy , R. Bernet , A. Bertolin , M. -O. Bettler , M. van Beuzekom , A. Bien , S. Bifani , P. Billoir , T. Bird , A. Birnkraut , A. Bizzeti , T. Blake , F. Blanc , J. Blouw , S. Blusk , V. Bocci , A. Bondar , N. Bondar , W. Bonivento , S. Borghi , M. Borsato , T. J. V. Bowcock , E. Bowen , C. Bozzi , S. Braun , M. Britsch , T. Britton , J. Brodzicka , N. H. Brook , E. Buchanan , A. Bursche , J. Buytaert , S. Cadeddu , R. Calabrese , M. Calvi , M. Calvo Gomez , P. Campana , D. Campora Perez , L. Capriotti , A. Carbone , G. Carboni , R. Cardinale , A. Cardini , P. Carniti , L. Carson , K. Carvalho Akiba , G. Casse , L. Cassina , L. Castillo Garcia , M. Cattaneo , Ch. Cauet , G. Cavallero , R. Cenci , M. Charles , Ph. Charpentier , M. Chefdeville , S. Chen , S. -F. Cheung , N. Chiapolini , M. Chrzaszcz , X. Cid Vidal , G. Ciezarek , P. E. L. Clarke , M. Clemencic , H. V. Cliff , J. Closier , V. Coco , J. Cogan , E. Cogneras , V. Cogoni , L. Cojocariu , G. Collazuol , P. Collins , A. Comerma-Montells , A. Contu , A. Cook , M. Coombes , S. Coquereau , G. Corti , M. Corvo , B. Couturier , G. A. Cowan , D. C. Craik , A. Crocombe , M. Cruz Torres , S. Cunliffe , R. Currie , C. D'Ambrosio , E. Dall'Occo , J. Dalseno , P. N. Y. David , A. Davis , K. De Bruyn , S. De Capua , M. De Cian , J. M. De Miranda , L. De Paula , P. De Simone , C. -T. Dean , D. Decamp , M. Deckenhoff , L. Del Buono , N. Déléage , M. Demmer , D. Derkach , O. Deschamps , F. Dettori , B. Dey , A. Di Canto , F. Di Ruscio , H. Dijkstra , S. Donleavy , F. Dordei , M. Dorigo , A. Dosil Suárez , D. Dossett , A. Dovbnya , K. Dreimanis , L. Dufour , G. Dujany , F. Dupertuis , P. Durante , R. Dzhelyadin , A. Dziurda , A. Dzyuba , S. Easo , U. Egede , V. Egorychev , S. Eidelman , S. Eisenhardt , U. Eitschberger , R. Ekelhof , L. Eklund , I. El Rifai , Ch. Elsasser , S. Ely , S. Esen , H. M. Evans , T. Evans , A. Falabella , C. Färber , C. Farinelli , N. Farley , S. Farry , R. Fay , D. Ferguson , V. Fernandez Albor , F. Ferrari , F. Ferreira Rodrigues , M. Ferro-Luzzi , S. Filippov , M. Fiore , M. Fiorini , M. Firlej , C. Fitzpatrick , T. Fiutowski , K. Fohl , P. Fol , M. Fontana , F. Fontanelli , R. Forty , O. Francisco , M. Frank , C. Frei , M. Frosini , J. Fu , E. Furfaro , A. Gallas Torreira , D. Galli , S. Gallorini , S. Gambetta , M. Gandelman , P. Gandini , Y. Gao , J. García Pardiñas , J. Garra Tico , L. Garrido , D. Gascon , C. Gaspar , R. Gauld , L. Gavardi , G. Gazzoni , D. Gerick , E. Gersabeck , M. Gersabeck , T. Gershon , Ph. Ghez , A. Gianelle , S. Gianì , V. Gibson , O. G. Girard , L. Giubega , V. V. Gligorov , C. Göbel , D. Golubkov , A. Golutvin , A. Gomes , C. Gotti , M. Grabalosa Gándara , R. Graciani Diaz , L. A. Granado Cardoso , E. Graugés , E. Graverini , G. Graziani , A. Grecu , E. Greening , S. Gregson , P. Griffith , L. Grillo , O. Grünberg , B. Gui , E. Gushchin , Yu. Guz , T. Gys , T. Hadavizadeh , C. Hadjivasiliou , G. Haefeli , C. Haen , S. C. Haines , S. Hall , B. Hamilton , X. Han , S. Hansmann-Menzemer , N. Harnew , S. T. Harnew , J. Harrison , J. He , T. Head , V. Heijne , K. Hennessy , P. Henrard , L. Henry , J. A. Hernando Morata , E. van Herwijnen , M. Heß , A. Hicheur , D. Hill , M. Hoballah , C. Hombach , W. Hulsbergen , T. Humair , N. Hussain , D. Hutchcroft , D. Hynds , M. Idzik , P. Ilten , R. Jacobsson , A. Jaeger , J. Jalocha , E. Jans , A. Jawahery , F. Jing , M. John , D. Johnson , C. R. Jones , C. Joram , B. Jost , N. Jurik , S. Kandybei , W. Kanso , M. Karacson , T. M. Karbach , S. Karodia , M. Kecke , M. Kelsey , I. R. Kenyon , M. Kenzie , T. Ketel , B. Khanji , C. Khurewathanakul , S. Klaver , K. Klimaszewski , O. Kochebina , M. Kolpin , I. Komarov , R. F. Koopman , P. Koppenburg , M. Kozeiha , L. Kravchuk , K. Kreplin , M. Kreps , G. Krocker , P. Krokovny , F. Kruse , W. Krzemien , W. Kucewicz , M. Kucharczyk , V. Kudryavtsev , A. K. Kuonen , K. Kurek , T. Kvaratskheliya , D. Lacarrere , G. Lafferty , A. Lai , D. Lambert , G. Lanfranchi , C. Langenbruch , B. Langhans , T. Latham , C. Lazzeroni , R. Le Gac , J. van Leerdam , J. -P. Lees , R. Lefèvre , A. Leflat , J. 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Morris , R. Mountain , F. Muheim , D. Muller , J. Müller , K. Müller , V. Müller , M. Mussini , B. Muster , P. Naik , T. Nakada , R. Nandakumar , A. Nandi , I. Nasteva , M. Needham , N. Neri , S. Neubert , N. Neufeld , M. Neuner , A. D. Nguyen , T. D. Nguyen , C. Nguyen-Mau , V. Niess , R. Niet , N. Nikitin , T. Nikodem , D. Ninci , A. Novoselov , D. P. O'Hanlon , A. Oblakowska-Mucha , V. Obraztsov , S. Ogilvy , O. Okhrimenko , R. Oldeman , C. J. G. Onderwater , B. Osorio Rodrigues , J. M. Otalora Goicochea , A. Otto , P. Owen , A. Oyanguren , A. Palano , F. Palombo , M. Palutan , J. Panman , A. Papanestis , M. Pappagallo , L. L. Pappalardo , C. Pappenheimer , C. Parkes , G. Passaleva , G. D. Patel , M. Patel , C. Patrignani , A. Pearce , A. Pellegrino , G. Penso , M. Pepe Altarelli , S. Perazzini , P. Perret , L. Pescatore , K. Petridis , A. Petrolini , M. Petruzzo , E. Picatoste Olloqui , B. Pietrzyk , T. Pilař , D. Pinci , A. Pistone , A. Piucci , S. Playfer , M. Plo Casasus , T. 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Wyllie , Y. Xie , Z. Xu , Z. Yang , J. Yu , X. Yuan , O. Yushchenko , M. Zangoli , M. Zavertyaev , L. Zhang , Y. Zhang , A. Zhelezov , A. Zhokhov , L. Zhong , S. Zucchelli

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to…

I present a new scheme for tagging boosted heavy flavor jets called "$\mu_x$ tagging" and its application to TeV-scale physics beyond the Standard Model. Using muons from B hadron decay to define a particular combination "x" of angular…

High Energy Physics - Phenomenology · Physics 2016-05-16 Zack Sullivan

The ATLAS inner detector comprises three different sub-detectors: the pixel detector, the silicon strip tracker, and the transition-radiation drift-tube tracker. The Insertable $B$-Layer, a new innermost pixel layer, was installed during…

High Energy Physics - Experiment · Physics 2017-12-08 ATLAS Collaboration

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

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

Jet flavour tagging enables the identification of jets originating from heavy-flavour quarks in proton-proton collisions at the Large Hadron Collider, playing a critical role in its physics programmes. This paper presents GN2, a…

High Energy Physics - Experiment · Physics 2026-01-27 ATLAS Collaboration

This article describes a new experimental method for accelerator based neutrino experiments called neutrino tagging. The method consists in exploiting the neutrino production mechanism, the $\pi^{\pm}\to\mu^{\pm}\nu_\mu$ decay, to…

High Energy Physics - Experiment · Physics 2022-06-02 Mathieu Perrin-Terrin

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of $\sqrt{s} =$ 13 TeV at the CERN LHC. The algorithm is trained on a large…

Data Analysis, Statistics and Probability · Physics 2020-11-09 CMS Collaboration

Measurements and searches performed with the ATLAS detector at the CERN Large Hadron Collider often involve signatures with one or more prompt leptons. Such analyses are subject to `fake/non-prompt' lepton backgrounds, where either a hadron…

High Energy Physics - Experiment · Physics 2024-11-11 ATLAS Collaboration

In high energy physics, graph-based implementations have the advantage of treating the input data sets in a similar way as they are collected by collider experiments. To expand on this concept, we propose a graph neural network enhanced by…

Data Analysis, Statistics and Probability · Physics 2020-09-29 Vinicius Mikuni , Florencia Canelli

The Large Hadron Collider (LHC) experiments ATLAS and CMS have established hybrid pixel detectors as the instrument of choice for particle tracking and vertexing in high rate and radiation environments, as they operate close to the LHC…

Instrumentation and Detectors · Physics 2018-06-27 Maurice Garcia-Sciveres , Norbert Wermes

Real-time jet tagging is critical for identifying short-lived particle decays in the high-throughput detectors of the Large Hadron Collider, where real-time trigger systems responsible for deciding which collision events to store impose…

High Energy Physics - Experiment · Physics 2026-05-22 Aaron Wang , Zihan Zhao , Alan Xia , Chang Sun , Abhijith Gandrakota , Jennifer Ngadiuba , Richard Cavanaugh , Javier Duarte

Neural network-based algorithms provide a promising approach to jet classification problems, such as boosted top jet tagging. To date, NN-based top taggers demonstrated excellent performance in Monte Carlo studies. In this paper, we…

High Energy Physics - Phenomenology · Physics 2019-03-27 Suyong Choi , Seung J. Lee , Maxim Perelstein

Many theoretical models, like the Standard Model or SUSY at large tan(beta), predict Higgs bosons or new particles which decay more abundantly to final states including tau leptons than to other leptons. At the energy scale of the LHC, the…

Jet flavor tagging plays an important role in precise Standard Model measurement enabling the extraction of mass dependence in jet-quark interaction and quark-gluon plasma (QGP) interactions. They also enable inferring the nature of…

High Energy Physics - Phenomenology · Physics 2026-03-24 Diego F. Vasquez Plaza , Vidya Manian

We introduce a new and highly efficient tagger for hadronically decaying top quarks, based on a deep neural network working with Lorentz vectors and the Minkowski metric. With its novel machine learning setup and architecture it allows us…

High Energy Physics - Phenomenology · Physics 2018-09-26 Anja Butter , Gregor Kasieczka , Tilman Plehn , Michael Russell
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