Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques

Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques

A. M. Sirunyan, A. Tumasyan, W. Adam, F. Ambrogi, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Ero, A. E. Del Valle, M. Flechl, R. Fruhwirth, M. Jeitler, N. Krammer, I. Kratschmer, D. Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck, R. Schofbeck, M. Spanring, D. Spitzbart, W. Waltenberger, C....

ARTIGO

Inglês

Agradecimentos: We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully...

Abstract: Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The identification performances of a variety of algorithms are...

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ

COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES

FUNDAÇÃO CARLOS CHAGAS FILHO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIRO - FAPERJ

FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DO RIO GRANDE DO SUL - FAPERGS

FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP

Aberto

Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques

A. M. Sirunyan, A. Tumasyan, W. Adam, F. Ambrogi, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Ero, A. E. Del Valle, M. Flechl, R. Fruhwirth, M. Jeitler, N. Krammer, I. Kratschmer, D. Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck, R. Schofbeck, M. Spanring, D. Spitzbart, W. Waltenberger, C....

										

Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques

A. M. Sirunyan, A. Tumasyan, W. Adam, F. Ambrogi, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Ero, A. E. Del Valle, M. Flechl, R. Fruhwirth, M. Jeitler, N. Krammer, I. Kratschmer, D. Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck, R. Schofbeck, M. Spanring, D. Spitzbart, W. Waltenberger, C....

    Fontes

    Journal of instrumentation

    Vol. 15, n. 6 (June, 2020), n. art. P06005, p. 1-87