메뉴 건너뛰기




Volumn 2017, Issue 1, 2017, Pages

Deep learning in color: towards automated quark/gluon jet discrimination

Author keywords

Jets

Indexed keywords


EID: 85011307893     PISSN: 11266708     EISSN: 10298479     Source Type: Journal    
DOI: 10.1007/JHEP01(2017)110     Document Type: Article
Times cited : (394)

References (56)
  • 1
    • 85011270961 scopus 로고    scopus 로고
    • ATLAS collaboration, A neural network clustering algorithm for the ATLAS silicon pixel detector, 2014 JINST 9 P09009 [] []
    • ATLAS collaboration, A neural network clustering algorithm for the ATLAS silicon pixel detector, 2014 JINST 9 P09009 [arXiv:1406.7690] [INSPIRE].
  • 2
    • 85011285836 scopus 로고    scopus 로고
    • ATLAS collaboration, Performance of b-jet identification in the ATLAS experiment, 2016 JINST 11 P04008 [] []
    • ATLAS collaboration, Performance of b-jet identification in the ATLAS experiment, 2016 JINST 11 P04008 [arXiv:1512.01094] [INSPIRE].
  • 3
    • 84961918561 scopus 로고    scopus 로고
    • Performance of tracking, b-tagging and jet/MET reconstruction at the CMS high level trigger
    • M. Tosi, Performance of tracking, b-tagging and jet/MET reconstruction at the CMS high level trigger, J. Phys. Conf. Ser. 664 (2015) 082055.
    • (2015) J. Phys. Conf. Ser. , vol.664 , pp. 082055
    • Tosi, M.1
  • 4
    • 85011269011 scopus 로고    scopus 로고
    • CMS collaboration, Performance of tau-lepton reconstruction and identification in CMS, 2012 JINST 7 P01001 [] []
    • CMS collaboration, Performance of tau-lepton reconstruction and identification in CMS, 2012 JINST 7 P01001 [arXiv:1109.6034] [INSPIRE].
  • 5
    • 84928688667 scopus 로고    scopus 로고
    • NNPDF collaboration, R.D. Ball et al., Parton distributions for the LHC Run II, JHEP 04 (2015) 040 [] []
    • NNPDF collaboration, R.D. Ball et al., Parton distributions for the LHC Run II, JHEP 04 (2015) 040 [arXiv:1410.8849] [INSPIRE].
  • 6
    • 80053239671 scopus 로고    scopus 로고
    • Multivariate discrimination and the Higgs + W/Z search
    • [arXiv:1010.3698] [INSPIRE]
    • J. Gallicchio, J. Huth, M. Kagan, M.D. Schwartz, K. Black and B. Tweedie, Multivariate discrimination and the Higgs + W/Z search, JHEP 04 (2011) 069 [arXiv:1010.3698] [INSPIRE].
    • (2011) JHEP , vol.4 , pp. 069
    • Gallicchio, J.1    Huth, J.2    Kagan, M.3    Schwartz, M.D.4    Black, K.5    Tweedie, B.6
  • 7
    • 0004642580 scopus 로고    scopus 로고
    • T. Maggipinto et al., Role of neural networks in the search of the Higgs boson at LHC, Phys. Lett. B 409 (1997) 517 [] []
    • T. Maggipinto et al., Role of neural networks in the search of the Higgs boson at LHC, Phys. Lett. B 409 (1997) 517 [hep-ex/9705020] [INSPIRE].
  • 8
    • 85161728384 scopus 로고    scopus 로고
    • CMS collaboration, Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network, Phys. Rev. D 87 (2013) 072001 [] []
    • CMS collaboration, Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network, Phys. Rev. D 87 (2013) 072001 [arXiv:1301.0916] [INSPIRE].
  • 9
  • 10
    • 84923197285 scopus 로고    scopus 로고
    • Jet-images: computer vision inspired techniques for jet tagging
    • [arXiv:1407.5675] [INSPIRE]
    • J. Cogan, M. Kagan, E. Strauss and A. Schwarztman, Jet-images: computer vision inspired techniques for jet tagging, JHEP 02 (2015) 118 [arXiv:1407.5675] [INSPIRE].
    • (2015) JHEP , vol.2 , pp. 118
    • Cogan, J.1    Kagan, M.2    Strauss, E.3    Schwarztman, A.4
  • 11
    • 84938262433 scopus 로고    scopus 로고
    • Playing tag with ANN: boosted top identification with pattern recognition
    • [arXiv:1501.05968] [INSPIRE]
    • L.G. Almeida, M. Backović, M. Cliche, S.J. Lee and M. Perelstein, Playing tag with ANN: boosted top identification with pattern recognition, JHEP 07 (2015) 086 [arXiv:1501.05968] [INSPIRE].
    • (2015) JHEP , vol.7 , pp. 086
    • Almeida, L.G.1    Backović, M.2    Cliche, M.3    Lee, S.J.4    Perelstein, M.5
  • 12
    • 84978898035 scopus 로고    scopus 로고
    • Jet-images — Deep learning edition
    • [arXiv:1511.05190] [INSPIRE]
    • L. de Oliveira, M. Kagan, L. Mackey, B. Nachman and A. Schwartzman, Jet-images — Deep learning edition, JHEP 07 (2016) 069 [arXiv:1511.05190] [INSPIRE].
    • (2016) JHEP , vol.7 , pp. 069
    • de Oliveira, L.1    Kagan, M.2    Mackey, L.3    Nachman, B.4    Schwartzman, A.5
  • 13
    • 84971602519 scopus 로고    scopus 로고
    • Jet substructure classification in high-energy physics with deep neural networks
    • [arXiv:1603.09349] [INSPIRE]
    • P. Baldi, K. Bauer, C. Eng, P. Sadowski and D. Whiteson, Jet substructure classification in high-energy physics with deep neural networks, Phys. Rev. D 93 (2016) 094034 [arXiv:1603.09349] [INSPIRE].
    • (2016) Phys. Rev. , vol.500 , pp. 094034
    • Baldi, P.1    Bauer, K.2    Eng, C.3    Sadowski, P.4    Whiteson, D.5
  • 14
    • 85002406555 scopus 로고    scopus 로고
    • Jet flavor classification in high-energy physics with deep neural networks
    • [arXiv:1607.08633] [INSPIRE]
    • D. Guest, J. Collado, P. Baldi, S.-C. Hsu, G. Urban and D. Whiteson, Jet flavor classification in high-energy physics with deep neural networks, Phys. Rev. D 94 (2016) 112002 [arXiv:1607.08633] [INSPIRE].
    • (2016) Phys. Rev. , vol.500 , pp. 112002
    • Guest, D.1    Collado, J.2    Baldi, P.3    Hsu, S.-C.4    Urban, G.5    Whiteson, D.6
  • 15
    • 85011316042 scopus 로고    scopus 로고
    • J. Barnard, E.N. Dawe, M.J. Dolan and N. Rajcic, Parton shower uncertainties in jet substructure analyses with deep neural networks, []
    • J. Barnard, E.N. Dawe, M.J. Dolan and N. Rajcic, Parton shower uncertainties in jet substructure analyses with deep neural networks, arXiv:1609.00607 [INSPIRE].
  • 16
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks, in the proceedings of Neural Information Processing Systems (NIPS 2012)
    • Lake Tahoe: U.S.A
    • A. Krizhevsky, I. Sutskever and G.E. Hinton, Imagenet classification with deep convolutional neural networks, in the proceedings of Neural Information Processing Systems (NIPS 2012), December 3-8, Lake Tahoe, U.S.A. (2012).
    • (2012) December , vol.3-8
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 17
    • 23544442655 scopus 로고
    • How to tell quark jets from gluon jets
    • [INSPIRE]
    • J. Pumplin, How to tell quark jets from gluon jets, Phys. Rev. D 44 (1991) 2025 [INSPIRE].
    • (1991) Phys. Rev. , vol.500 , pp. 2025
    • Pumplin, J.1
  • 19
    • 85148311856 scopus 로고    scopus 로고
    • OPAL collaboration, A Study of differences between quark and gluon jets using vertex tagging of quark jets, Z. Phys. C 58 (1993) 387
    • OPAL collaboration, A Study of differences between quark and gluon jets using vertex tagging of quark jets, Z. Phys. C 58 (1993) 387.
  • 20
    • 0000252637 scopus 로고    scopus 로고
    • OPAL collaboration, A direct observation of quark-gluon jet differences at LEP, Phys. Lett. B 265 (1991) 462
    • OPAL collaboration, A direct observation of quark-gluon jet differences at LEP, Phys. Lett. B 265 (1991) 462.
  • 21
    • 85011269030 scopus 로고    scopus 로고
    • D. Ferreira de Lima, P. Petrov, D. Soper and M. Spannowsky, Quark-gluon tagging with shower deconstruction: unearthing dark matter and Higgs couplings, []
    • D. Ferreira de Lima, P. Petrov, D. Soper and M. Spannowsky, Quark-gluon tagging with shower deconstruction: unearthing dark matter and Higgs couplings, arXiv:1607.06031 [INSPIRE].
  • 22
    • 84920145134 scopus 로고    scopus 로고
    • Gaining (mutual) information about quark/gluon discrimination
    • [arXiv:1408.3122] [INSPIRE]
    • A.J. Larkoski, J. Thaler and W.J. Waalewijn, Gaining (mutual) information about quark/gluon discrimination, JHEP 11 (2014) 129 [arXiv:1408.3122] [INSPIRE].
    • (2014) JHEP , vol.11 , pp. 129
    • Larkoski, A.J.1    Thaler, J.2    Waalewijn, W.J.3
  • 23
    • 84928667310 scopus 로고    scopus 로고
    • Associated jet and subjet rates in light-quark and gluon jet discrimination
    • [arXiv:1501.04794] [INSPIRE]
    • B. Bhattacherjee, S. Mukhopadhyay, M.M. Nojiri, Y. Sakaki and B.R. Webber, Associated jet and subjet rates in light-quark and gluon jet discrimination, JHEP 04 (2015) 131 [arXiv:1501.04794] [INSPIRE].
    • (2015) JHEP , vol.4 , pp. 131
    • Bhattacherjee, B.1    Mukhopadhyay, S.2    Nojiri, M.M.3    Sakaki, Y.4    Webber, B.R.5
  • 24
    • 84928250592 scopus 로고    scopus 로고
    • Quark and gluon jet substructure
    • [arXiv:1211.7038] [INSPIRE]
    • J. Gallicchio and M.D. Schwartz, Quark and gluon jet substructure, JHEP 04 (2013) 090 [arXiv:1211.7038] [INSPIRE].
    • (2013) JHEP , vol.4 , pp. 090
    • Gallicchio, J.1    Schwartz, M.D.2
  • 25
    • 80054766696 scopus 로고    scopus 로고
    • Quark and gluon tagging at the LHC
    • [arXiv:1106.3076] [INSPIRE]
    • J. Gallicchio and M.D. Schwartz, Quark and gluon tagging at the LHC, Phys. Rev. Lett. 107 (2011) 172001 [arXiv:1106.3076] [INSPIRE].
    • (2011) Phys. Rev. Lett. , vol.107 , pp. 172001
    • Gallicchio, J.1    Schwartz, M.D.2
  • 26
    • 85011273190 scopus 로고    scopus 로고
    • J.R. Andersen et al., Les Houches 2015: physics at TeV colliders standard model working group report, []
    • J.R. Andersen et al., Les Houches 2015: physics at TeV colliders standard model working group report, arXiv:1605.04692 [INSPIRE].
  • 27
    • 85029801742 scopus 로고    scopus 로고
    • ATLAS collaboration, Light-quark and gluon jet discrimination in pp collisions at221AsTeV with the ATLAS detector, Eur. Phys. J. C 74 (2014) 3023 [] []
    • ATLAS collaboration, Light-quark and gluon jet discrimination in pp collisions at s=7 TeV with the ATLAS detector, Eur. Phys. J. C 74 (2014) 3023 [arXiv:1405.6583] [INSPIRE].
  • 28
    • 84978818158 scopus 로고    scopus 로고
    • Factorization for groomed jet substructure beyond the next-to-leading logarithm
    • [arXiv:1603.09338] [INSPIRE]
    • C. Frye, A.J. Larkoski, M.D. Schwartz and K. Yan, Factorization for groomed jet substructure beyond the next-to-leading logarithm, JHEP 07 (2016) 064 [arXiv:1603.09338] [INSPIRE].
    • (2016) JHEP , vol.7 , pp. 064
    • Frye, C.1    Larkoski, A.J.2    Schwartz, M.D.3    Yan, K.4
  • 29
    • 56449095373 scopus 로고    scopus 로고
    • th International Conference on Machine Learning, July 5-9, Helsinki, Finland (2008)
    • th International Conference on Machine Learning, July 5-9, Helsinki, Finland (2008).
  • 30
    • 84903779279 scopus 로고    scopus 로고
    • Searching for exotic particles in high-energy physics with deep learning
    • [arXiv:1402.4735] [INSPIRE]
    • P. Baldi, P. Sadowski and D. Whiteson, Searching for exotic particles in high-energy physics with deep learning, Nature Commun. 5 (2014) 4308 [arXiv:1402.4735] [INSPIRE].
    • (2014) Nature Commun. , vol.5 , pp. 4308
    • Baldi, P.1    Sadowski, P.2    Whiteson, D.3
  • 31
    • 84936124348 scopus 로고    scopus 로고
    • Rotation-invariant convolutional neural networks for galaxy morphology prediction
    • [arXiv:1503.07077]
    • S. Dieleman, K.W. Willet and J. Dambre, Rotation-invariant convolutional neural networks for galaxy morphology prediction, Mon. Roy. Astron. Soc. 450 (2015) 1441 [arXiv:1503.07077].
    • (2015) Mon. Roy. Astron. Soc. , vol.450 , pp. 1441
    • Dieleman, S.1    Willet, K.W.2    Dambre, J.3
  • 34
    • 85011262525 scopus 로고    scopus 로고
    • th International Conference on Artificial Intelligence and Statistics, April 11-13, Ft. Lauderdale, U.S.A. (2011)
    • th International Conference on Artificial Intelligence and Statistics, April 11-13, Ft. Lauderdale, U.S.A. (2011).
  • 35
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • K. Hornik, M. Stinchcombe and H. White, Multilayer feedforward networks are universal approximators, Neural Netw. 2 (1989) 359.
    • (1989) Neural Netw. , vol.2 , pp. 359
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 36
    • 84910651844 scopus 로고    scopus 로고
    • Deep learning in neural networks: an overview
    • [arXiv:1404.7828]
    • J. Schmidhuber, Deep learning in neural networks: an overview, Neural Netw. 61 (2015) 85 [arXiv:1404.7828].
    • (2015) Neural Netw. , vol.61 , pp. 85
    • Schmidhuber, J.1
  • 38
    • 84904163933 scopus 로고    scopus 로고
    • Dropout: a simple way to prevent neural networks from overfitting
    • N. Srivastava et al., Dropout: a simple way to prevent neural networks from overfitting, JMLR 15 (2014) 1929.
    • (2014) JMLR , vol.15 , pp. 1929
    • Srivastava, N.1
  • 39
    • 84928671738 scopus 로고    scopus 로고
    • T. Sjöstrand, et al., An Introduction to PYTHIA 8.2, Comput. Phys. Commun. 191 (2015) 159 [] []
    • T. Sjöstrand, et al., An Introduction to PYTHIA 8.2, Comput. Phys. Commun. 191 (2015) 159 [arXiv:1410.3012] [INSPIRE].
  • 40
    • 57049125048 scopus 로고    scopus 로고
    • HERWIG++ physics and manual
    • [arXiv:0803.0883] [INSPIRE]
    • M. Bahr et al., HERWIG++ physics and manual, Eur. Phys. J. C 58 (2008) 639 [arXiv:0803.0883] [INSPIRE].
    • (2008) Eur. Phys. J. , vol.100 , pp. 639
    • Bahr, M.1
  • 41
    • 84963876705 scopus 로고    scopus 로고
    • J. Bellm et al., HERWIG 7.0/HERWIG++ 3.0 release note, Eur. Phys. J. C 76 (2016) 196 [] []
    • J. Bellm et al., HERWIG 7.0/HERWIG++ 3.0 release note, Eur. Phys. J. C 76 (2016) 196 [arXiv:1512.01178] [INSPIRE].
  • 42
    • 84858019473 scopus 로고    scopus 로고
    • FastJet user manual
    • [arXiv:1111.6097] [INSPIRE]
    • M. Cacciari, G.P. Salam and G. Soyez, FastJet user manual, Eur. Phys. J. C 72 (2012) 1896 [arXiv:1111.6097] [INSPIRE].
    • (2012) Eur. Phys. J. , vol.100 , pp. 1896
    • Cacciari, M.1    Salam, G.P.2    Soyez, G.3
  • 43
    • 84856393274 scopus 로고    scopus 로고
    • t jet clustering algorithm
    • [arXiv:0802.1189] [INSPIRE]
    • t jet clustering algorithm, JHEP 04 (2008) 063 [arXiv:0802.1189] [INSPIRE].
    • (2008) JHEP , vol.4 , pp. 063
    • Cacciari, M.1    Salam, G.P.2    Soyez, G.3
  • 44
    • 53549092486 scopus 로고    scopus 로고
    • Top tagging: a method for identifying boosted hadronically decaying top quarks
    • [arXiv:0806.0848] [INSPIRE]
    • D.E. Kaplan, K. Rehermann, M.D. Schwartz and B. Tweedie, Top tagging: a method for identifying boosted hadronically decaying top quarks, Phys. Rev. Lett. 101 (2008) 142001 [arXiv:0806.0848] [INSPIRE].
    • (2008) Phys. Rev. Lett. , vol.101 , pp. 142001
    • Kaplan, D.E.1    Rehermann, K.2    Schwartz, M.D.3    Tweedie, B.4
  • 45
    • 56749163377 scopus 로고    scopus 로고
    • A determination of parton distributions with faithful uncertainty estimation
    • NNPDF collaboration, R.D. Ball et al., A determination of parton distributions with faithful uncertainty estimation, Nucl. Phys. B 809 (2009) 1
    • (2009) Nucl. Phys. , vol.809 , pp. 1
    • Ball, R.D.1
  • 46
    • 64649106278 scopus 로고    scopus 로고
    • A determination of parton distributions with faithful uncertainty estimation
    • [arXiv:0808.1231] [INSPIRE]
    • [Erratum ibid. B 816 (2009) 293] [arXiv:0808.1231] [INSPIRE]
    • (2009) Nucl. Phys. , vol.816 , pp. 293
    • Ball, R.D.1
  • 47
    • 84945900998 scopus 로고    scopus 로고
    • P.Y. Simard, D. Steinkraus and J.C. Platt, Best practices for convolutional neural networks applied to visual document analysis, ICDAR 3 (2003)
    • P.Y. Simard, D. Steinkraus and J.C. Platt, Best practices for convolutional neural networks applied to visual document analysis, ICDAR 3 (2003).
  • 49
    • 85011262535 scopus 로고    scopus 로고
    • th Python in science conference, June 28-July 3, Austin, U.S.A. (2010)
    • th Python in science conference, June 28-July 3, Austin, U.S.A. (2010).
  • 50
    • 84973911419 scopus 로고    scopus 로고
    • Delving deep into rectifiers: surpassing human-level performance on imagenet classification, in the proceedings of the IEEE International Conference on Computer Vision
    • Santiago, Chile
    • K. He, X. Zhang, S. Ren and J. Sun, Delving deep into rectifiers: surpassing human-level performance on imagenet classification, in the proceedings of the IEEE International Conference on Computer Vision, December 11-18, Santiago, Chile (2015).
    • (2015) December , vol.11-18
    • He, K.1    Zhang, X.2    Ren, S.3    Sun, J.4
  • 51
    • 85011316278 scopus 로고    scopus 로고
    • D. Kingma and J. Ba, Adam: a method for stochastic optimization
    • D. Kingma and J. Ba, Adam: a method for stochastic optimization, arXiv:1412.6980.
  • 52
    • 84869201485 scopus 로고    scopus 로고
    • Practical bayesian optimization of machine learning algorithms, in the proceedings of Neural Information Processing Systems (NIPS
    • J. Snoek, H. Larochelle and R.P. Adams, Practical bayesian optimization of machine learning algorithms, in the proceedings of Neural Information Processing Systems (NIPS 2012), December 3-8, Lake Tahoe, U.S.A. (2012), arXiv:1206.2944.
    • (2012) December 3-8, Lake Tahoe, U.S.A. (2012), arXiv , vol.1206 , pp. 2944
    • Snoek, J.1    Larochelle, H.2    Adams, R.P.3
  • 53
    • 85034428200 scopus 로고    scopus 로고
    • Taus and MET
    • CMS Collaboration, Particle-flow event reconstruction in CMS and Performance for Jets, Taus and MET, CMS-PAS-PFT-09-001 (2009).
    • (2009) CMS-PAS-PFT-09-001
  • 54
    • 80555140075 scopus 로고    scopus 로고
    • Scikit-learn: machine learning in Python
    • F. Pedregosa et al., Scikit-learn: machine learning in Python, JMLR 12 (2012) 2825.
    • (2012) JMLR , vol.12 , pp. 2825
    • Pedregosa, F.1
  • 55
    • 84880382537 scopus 로고    scopus 로고
    • Energy correlation functions for jet substructure
    • [arXiv:1305.0007] [INSPIRE]
    • A.J. Larkoski, G.P. Salam and J. Thaler, Energy correlation functions for jet substructure, JHEP 06 (2013) 108 [arXiv:1305.0007] [INSPIRE].
    • (2013) JHEP , vol.6 , pp. 108
    • Larkoski, A.J.1    Salam, G.P.2    Thaler, J.3
  • 56
    • 85011286472 scopus 로고    scopus 로고
    • London
    • H. Küçük, Measurement of the inclusive-jet cross-section in proton-proton collisions and study of quark-gluon jet discrimination with the ATLAS experiment at the LHC, Dissertation, University College London, London. U.K. (2016).
    • (2016) U.K


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.