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

ATLAS Collaboration

doi:10.1140/epjc/s10052-019-6847-8

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

ATLAS Collaboration

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Abstract

The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb^-1 for the tt¯ and γ + jet and 36.7 fb^-1 for the dijet event topologies.

Original language	English
Article number	375
Pages (from-to)	1-54
Number of pages	54
Journal	European Physical Journal C
Volume	79
Issue number	5
DOIs	https://doi.org/10.1140/epjc/s10052-019-6847-8
Publication status	Published - May 2019
Externally published	Yes

Bibliographical note

Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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10.1140/epjc/s10052-019-6847-8Licence: CC BY

Publisher version (open access)Final published version, 3.32 MBLicence: CC BY

Cite this

@article{8a54d4236b1243699323963b1a49ce71,

title = "Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC",

abstract = "The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb-1 for the tt¯ and γ + jet and 36.7 fb-1 for the dijet event topologies.",

author = "\{ATLAS Collaboration\} and M. Aaboud and G. Aad and B. Abbott and O. Abdinov and B. Abeloos and Abhayasinghe, \{D. K.\} and Abidi, \{S. H.\} and AbouZeid, \{O. S.\} and Abraham, \{N. L.\} and H. Abramowicz and H. Abreu and Y. Abulaiti and Acharya, \{B. S.\} and S. Adachi and L. Adam and L. Adamczyk and J. Adelman and M. Adersberger and A. Adiguzel and T. Adye and Affolder, \{A. A.\} and Y. Afik and C. Agheorghiesei and Aguilar-Saavedra, \{J. A.\} and F. Ahmadov and G. Aielli and S. Akatsuka and {\AA}kesson, \{T. P.A.\} and E. Akilli and Akimov, \{A. V.\} and Alberghi, \{G. L.\} and J. Albert and P. Albicocco and Alconada Verzini, \{M. J.\} and S. Alderweireldt and M. Aleksa and Aleksandrov, \{I. N.\} and C. Alexa and T. Alexopoulos and M. Alhroob and B. Ali and G. Alimonti and J. Alison and Alkire, \{S. P.\} and C. Allaire and Allbrooke, \{B. M.M.\} and Allen, \{B. W.\} and Allport, \{P. P.\} and A. Aloisio and A. Alonso and F. Alonso and C. Alpigiani and Alshehri, \{A. A.\} and Alstaty, \{M. I.\} and B. Alvarez Gonzalez and D. {\'A}lvarez Piqueras and Alviggi, \{M. G.\} and Amadio, \{B. T.\} and Y. Amaral Coutinho and A. Ambler and L. Ambroz and C. Amelung and D. Amidei and Amor Dos Santos, \{S. P.\} and S. Amoroso and Amrouche, \{C. S.\} and C. Anastopoulos and Ancu, \{L. S.\} and N. Andari and T. Andeen and Anders, \{C. F.\} and Anders, \{J. K.\} and Anderson, \{K. J.\} and A. Andreazza and V. Andrei and Anelli, \{C. R.\} and S. Angelidakis and I. Angelozzi and A. Angerami and Anisenkov, \{A. V.\} and A. Annovi and C. Antel and Anthony, \{M. T.\} and M. Antonelli and Antrim, \{D. J.A.\} and F. Anulli and M. Aoki and Pozo, \{J. A.Aparisi\} and L. Aperio Bella and G. Arabidze and Araque, \{J. P.\} and V. Araujo Ferraz and R. Araujo Pereira and Arce, \{A. T.H.\} and Ardell, \{R. E.\} and Arduh, \{F. A.\} and Arguin, \{J. F.\} and S. Argyropoulos and Armbruster, \{A. J.\} and Armitage, \{L. J.\} and A. Armstrong and O. Arnaez and H. Arnold and M. Arratia and O. Arslan and A. Artamonov and G. Artoni and S. Artz and S. Asai and N. Asbah and Asimakopoulou, \{E. M.\} and L. Asquith and K. Assamagan and R. Astalos and Atkin, \{R. J.\} and M. Atkinson and Atlay, \{N. B.\} and K. Augsten and G. Avolio and R. Avramidou and Ayoub, \{M. K.\} and Azoulay, \{A. M.\} and G. Azuelos and Baas, \{A. E.\} and Baca, \{M. J.\} and H. Bachacou and K. Bachas and M. Backes and P. Bagnaia and M. Bahmani and H. Bahrasemani and Bailey, \{A. J.\} and Baines, \{J. T.\} and M. Bajic and C. Bakalis and Baker, \{O. K.\} and Bakker, \{P. J.\} and D. Bakshi Gupta and S. Balaji and Baldin, \{E. M.\} and P. Balek and F. Balli and Balunas, \{W. K.\} and J. Balz and E. Banas and A. Bandyopadhyay and S. Banerjee and Bannoura, \{A. A.E.\} and L. Barak and Barbe, \{W. M.\} and Barberio, \{E. L.\} and D. Barberis and M. Barbero and T. Barillari and Barisits, \{M. S.\} and J. Barkeloo and T. Barklow and R. Barnea and Barnes, \{S. L.\} and Barnett, \{B. M.\} and Barnett, \{R. M.\} and Z. Barnovska-Blenessy and A. Baroncelli and G. Barone and Barr, \{A. J.\} and L. Barranco Navarro and F. Barreiro and J. Barreiro Guimar{\~a}es da Costa and R. Bartoldus and Barton, \{A. E.\} and P. Bartos and A. Basalaev and A. Bassalat and Bates, \{R. L.\} and Batista, \{S. J.\} and S. Batlamous and Batley, \{J. R.\} and M. Battaglia and M. Bauce and F. Bauer and Bauer, \{K. T.\} and Bawa, \{H. S.\} and Beacham, \{J. B.\} and T. Beau and Beauchemin, \{P. H.\} and P. Bechtle and Beck, \{H. C.\} and Beck, \{H. P.\} and K. Becker and M. Becker and C. Becot and Beddall, \{A. J.\} and Beddall, \{A. J.\} and Bednyakov, \{V. A.\} and M. Bedognetti and Bee, \{C. P.\} and Beermann, \{T. A.\} and M. Begalli and M. Begel and A. Behera and Behr, \{J. K.\} and Bell, \{A. S.\} and G. Bella and L. Bellagamba and A. Bellerive and M. Bellomo and P. Bellos and K. Belotskiy and Belyaev, \{N. L.\} and O. Benary and D. Benchekroun and M. Bender and N. Benekos and Y. Benhammou and E. Benhar Noccioli and J. Benitez and Benjamin, \{D. P.\} and M. Benoit and Bensinger, \{J. R.\} and S. Bentvelsen and L. Beresford and M. Beretta and D. Berge and E. Bergeaas Kuutmann and N. Berger and Bergsten, \{L. J.\} and J. Beringer and S. Berlendis and Bernard, \{N. R.\} and G. Bernardi and C. Bernius and Bernlochner, \{F. U.\} and T. Berry and P. Berta and C. Bertella and G. Bertoli and Bertram, \{I. A.\} and Besjes, \{G. J.\} and O. Bessidskaia Bylund and M. Bessner and N. Besson and A. Bethani and S. Bethke and A. Betti and Bevan, \{A. J.\} and J. Beyer and R. Bi and Bianchi, \{R. M.\} and O. Biebel and S. Shojaii",

note = "Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",

year = "2019",

month = may,

doi = "10.1140/epjc/s10052-019-6847-8",

language = "English",

volume = "79",

pages = "1--54",

journal = "European Physical Journal C",

issn = "1434-6052",

publisher = "Springer, Springer Nature",

number = "5",

}

TY - JOUR

T1 - Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC

AU - ATLAS Collaboration

AU - Aaboud, M.

AU - Aad, G.

AU - Abbott, B.

AU - Abdinov, O.

AU - Abeloos, B.

AU - Abhayasinghe, D. K.

AU - Abidi, S. H.

AU - AbouZeid, O. S.

AU - Abraham, N. L.

AU - Abramowicz, H.

AU - Abreu, H.

AU - Abulaiti, Y.

AU - Acharya, B. S.

AU - Adachi, S.

AU - Adam, L.

AU - Adamczyk, L.

AU - Adelman, J.

AU - Adersberger, M.

AU - Adiguzel, A.

AU - Adye, T.

AU - Affolder, A. A.

AU - Afik, Y.

AU - Agheorghiesei, C.

AU - Aguilar-Saavedra, J. A.

AU - Ahmadov, F.

AU - Aielli, G.

AU - Akatsuka, S.

AU - Åkesson, T. P.A.

AU - Akilli, E.

AU - Akimov, A. V.

AU - Alberghi, G. L.

AU - Albert, J.

AU - Albicocco, P.

AU - Alconada Verzini, M. J.

AU - Alderweireldt, S.

AU - Aleksa, M.

AU - Aleksandrov, I. N.

AU - Alexa, C.

AU - Alexopoulos, T.

AU - Alhroob, M.

AU - Ali, B.

AU - Alimonti, G.

AU - Alison, J.

AU - Alkire, S. P.

AU - Allaire, C.

AU - Allbrooke, B. M.M.

AU - Allen, B. W.

AU - Allport, P. P.

AU - Aloisio, A.

AU - Alonso, A.

AU - Alonso, F.

AU - Alpigiani, C.

AU - Alshehri, A. A.

AU - Alstaty, M. I.

AU - Alvarez Gonzalez, B.

AU - Álvarez Piqueras, D.

AU - Alviggi, M. G.

AU - Amadio, B. T.

AU - Amaral Coutinho, Y.

AU - Ambler, A.

AU - Ambroz, L.

AU - Amelung, C.

AU - Amidei, D.

AU - Amor Dos Santos, S. P.

AU - Amoroso, S.

AU - Amrouche, C. S.

AU - Anastopoulos, C.

AU - Ancu, L. S.

AU - Andari, N.

AU - Andeen, T.

AU - Anders, C. F.

AU - Anders, J. K.

AU - Anderson, K. J.

AU - Andreazza, A.

AU - Andrei, V.

AU - Anelli, C. R.

AU - Angelidakis, S.

AU - Angelozzi, I.

AU - Angerami, A.

AU - Anisenkov, A. V.

AU - Annovi, A.

AU - Antel, C.

AU - Anthony, M. T.

AU - Antonelli, M.

AU - Antrim, D. J.A.

AU - Anulli, F.

AU - Aoki, M.

AU - Pozo, J. A.Aparisi

AU - Aperio Bella, L.

AU - Arabidze, G.

AU - Araque, J. P.

AU - Araujo Ferraz, V.

AU - Araujo Pereira, R.

AU - Arce, A. T.H.

AU - Ardell, R. E.

AU - Arduh, F. A.

AU - Arguin, J. F.

AU - Argyropoulos, S.

AU - Armbruster, A. J.

AU - Armitage, L. J.

AU - Armstrong, A.

AU - Arnaez, O.

AU - Arnold, H.

AU - Arratia, M.

AU - Arslan, O.

AU - Artamonov, A.

AU - Artoni, G.

AU - Artz, S.

AU - Asai, S.

AU - Asbah, N.

AU - Asimakopoulou, E. M.

AU - Asquith, L.

AU - Assamagan, K.

AU - Astalos, R.

AU - Atkin, R. J.

AU - Atkinson, M.

AU - Atlay, N. B.

AU - Augsten, K.

AU - Avolio, G.

AU - Avramidou, R.

AU - Ayoub, M. K.

AU - Azoulay, A. M.

AU - Azuelos, G.

AU - Baas, A. E.

AU - Baca, M. J.

AU - Bachacou, H.

AU - Bachas, K.

AU - Backes, M.

AU - Bagnaia, P.

AU - Bahmani, M.

AU - Bahrasemani, H.

AU - Bailey, A. J.

AU - Baines, J. T.

AU - Bajic, M.

AU - Bakalis, C.

AU - Baker, O. K.

AU - Bakker, P. J.

AU - Bakshi Gupta, D.

AU - Balaji, S.

AU - Baldin, E. M.

AU - Balek, P.

AU - Balli, F.

AU - Balunas, W. K.

AU - Balz, J.

AU - Banas, E.

AU - Bandyopadhyay, A.

AU - Banerjee, S.

AU - Bannoura, A. A.E.

AU - Barak, L.

AU - Barbe, W. M.

AU - Barberio, E. L.

AU - Barberis, D.

AU - Barbero, M.

AU - Barillari, T.

AU - Barisits, M. S.

AU - Barkeloo, J.

AU - Barklow, T.

AU - Barnea, R.

AU - Barnes, S. L.

AU - Barnett, B. M.

AU - Barnett, R. M.

AU - Barnovska-Blenessy, Z.

AU - Baroncelli, A.

AU - Barone, G.

AU - Barr, A. J.

AU - Barranco Navarro, L.

AU - Barreiro, F.

AU - Barreiro Guimarães da Costa, J.

AU - Bartoldus, R.

AU - Barton, A. E.

AU - Bartos, P.

AU - Basalaev, A.

AU - Bassalat, A.

AU - Bates, R. L.

AU - Batista, S. J.

AU - Batlamous, S.

AU - Batley, J. R.

AU - Battaglia, M.

AU - Bauce, M.

AU - Bauer, F.

AU - Bauer, K. T.

AU - Bawa, H. S.

AU - Beacham, J. B.

AU - Beau, T.

AU - Beauchemin, P. H.

AU - Bechtle, P.

AU - Beck, H. C.

AU - Beck, H. P.

AU - Becker, K.

AU - Becker, M.

AU - Becot, C.

AU - Beddall, A. J.

AU - Bednyakov, V. A.

AU - Bedognetti, M.

AU - Bee, C. P.

AU - Beermann, T. A.

AU - Begalli, M.

AU - Begel, M.

AU - Behera, A.

AU - Behr, J. K.

AU - Bell, A. S.

AU - Bella, G.

AU - Bellagamba, L.

AU - Bellerive, A.

AU - Bellomo, M.

AU - Bellos, P.

AU - Belotskiy, K.

AU - Belyaev, N. L.

AU - Benary, O.

AU - Benchekroun, D.

AU - Bender, M.

AU - Benekos, N.

AU - Benhammou, Y.

AU - Benhar Noccioli, E.

AU - Benitez, J.

AU - Benjamin, D. P.

AU - Benoit, M.

AU - Bensinger, J. R.

AU - Bentvelsen, S.

AU - Beresford, L.

AU - Beretta, M.

AU - Berge, D.

AU - Bergeaas Kuutmann, E.

AU - Berger, N.

AU - Bergsten, L. J.

AU - Beringer, J.

AU - Berlendis, S.

AU - Bernard, N. R.

AU - Bernardi, G.

AU - Bernius, C.

AU - Bernlochner, F. U.

AU - Berry, T.

AU - Berta, P.

AU - Bertella, C.

AU - Bertoli, G.

AU - Bertram, I. A.

AU - Besjes, G. J.

AU - Bessidskaia Bylund, O.

AU - Bessner, M.

AU - Besson, N.

AU - Bethani, A.

AU - Bethke, S.

AU - Betti, A.

AU - Bevan, A. J.

AU - Beyer, J.

AU - Bi, R.

AU - Bianchi, R. M.

AU - Biebel, O.

AU - Shojaii, S.

N1 - Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2019/5

Y1 - 2019/5

N2 - The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb-1 for the tt¯ and γ + jet and 36.7 fb-1 for the dijet event topologies.

AB - The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb-1 for the tt¯ and γ + jet and 36.7 fb-1 for the dijet event topologies.

UR - https://www.scopus.com/pages/publications/85065123030

U2 - 10.1140/epjc/s10052-019-6847-8

DO - 10.1140/epjc/s10052-019-6847-8

M3 - Article

AN - SCOPUS:85065123030

SN - 1434-6052

VL - 79

SP - 1

EP - 54

JO - European Physical Journal C

JF - European Physical Journal C

IS - 5

M1 - 375

ER -

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

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