Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/87721
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Campo DC | Valor | Idioma |
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dc.contributor.author | Morais, Antonio P. | por |
dc.contributor.author | Onofre, A. | por |
dc.contributor.author | Freitas, Felipe F. | por |
dc.contributor.author | Goncalves, João | por |
dc.contributor.author | Pasechnik, Roman | por |
dc.contributor.author | Santos, Rui | por |
dc.date.accessioned | 2024-01-02T21:38:00Z | - |
dc.date.available | 2024-01-02T21:38:00Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Morais, A.P., Onofre, A., Freitas, F.F. et al. Deep learning searches for vector-like leptons at the LHC and electron/muon colliders. Eur. Phys. J. C 83, 232 (2023). https://doi.org/10.1140/epjc/s10052-023-11314-3 | por |
dc.identifier.issn | 1434-6044 | - |
dc.identifier.uri | https://hdl.handle.net/1822/87721 | - |
dc.description | This manuscript has no associated data or the data will not be deposited. [Authors’ comment: Due to the big memory size of the root files, they are not provided. Instead, csv data files used in the numerics are provided and can be found in one of the author’s GitHub page https://github.com/Mrazi09/VLL_collider.] | por |
dc.description.abstract | The discovery potential of both singlet and doublet vector-like leptons (VLLs) at the Large Hadron Collider (LHC) as well as at the not-so-far future muon and electron machines is explored. The focus is on a single production channel for LHC direct searches while double production signatures are proposed for the leptonic colliders. A Deep Learning algorithm to determine the discovery (or exclusion) statistical significance at the LHC is employed. While doublet VLLs can be probed up to masses of 1 TeV, their singlet counterparts have very low cross sections and can hardly be tested beyond a few hundreds of GeV at the LHC. This motivates a physics-case analysis in the context of leptonic colliders where one obtains larger cross sections in VLL double production channels, allowing to probe higher mass regimes otherwise inaccessible even to the LHC high-luminosity upgrade. | por |
dc.description.sponsorship | The authors would like to thank Celso Nishi for valuable comments made to the initial version of this manuscript. J.G., F.F.F., and A.P.M. are supported by the Center for Research and Development in Mathematics and Applications (CIDMA) through the Portuguese Foundation for Science and Technology (FCT - FundacOpara a Ciencia e a Tecnologia), references UIDB/04106/2020 and UIDP/04106/2020. A.P.M., F.F.F., J.G. and R.S. are supported by the project PTDC/FIS-PAR/31000/2017. A.P.M., F.F.F., J.G. are also supported by the projects CERN/FIS-PAR/0021/2021. Additionally, A.P.M. and J.G. are supported by CERN/FIS-PAR/0019/2021. J.G. is also directly funded by FCT through the doctoral program grant with the reference 2021.04527.BD. A.P.M. is also supported by national funds (OE), through FCT, I.P., in the scope of the framework contract foreseen in the numbers 4, 5 and 6 of the article 23, of the Decree-Law 57/2016, of August 29, changed by Law 57/2017, of July 19. R.P. is supported in part by the Swedish Research Council grant, contract number 2016-05996, as well as by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 668679). R.S. is supported by CFTC-UL under FCT contracts UIDB/00618/2020, UIDP/00618/2020, and by the projects CERN/FISPAR/0002/2017, CERN/FIS-PAR/0014/2019 and by the HARMONIA project of the National Science Centre, Poland, under contract UMO-2015/18/M/ST2/00518. A.O. is supported by the FCT project CERN/FIS-PAR/0029/2019. | por |
dc.language.iso | eng | por |
dc.publisher | Springer | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04106%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04106%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FFIS-PAR%2F31000%2F2017/PT | por |
dc.relation | CERN/FIS-PAR/0021/2021 | por |
dc.relation | CERN/FIS-PAR0019/2021 | por |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/668679/EU | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00618%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00618%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/3599-PPCDT/CERN%2FFIS-PAR%2F0002%2F2017/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/3599-PPCDT/CERN%2FFIS-PAR%2F0014%2F2019/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/3599-PPCDT/CERN%2FFIS-PAR%2F0029%2F2019/PT | por |
dc.rights | openAccess | por |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | por |
dc.title | Deep learning searches for vector-like leptons at the LHC and electron/muon colliders | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://link.springer.com/article/10.1140/epjc/s10052-023-11314-3 | por |
oaire.citationIssue | 3 | por |
oaire.citationVolume | 83 | por |
dc.identifier.eissn | 1434-6052 | - |
dc.identifier.doi | 10.1140/epjc/s10052-023-11314-3 | por |
dc.subject.fos | Ciências Naturais::Ciências Físicas | por |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | - |
dc.subject.wos | Science & Technology | por |
sdum.journal | European Physical Journal C | por |
oaire.version | VoR | por |
Aparece nas coleções: | LIP - Artigos/papers |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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s10052-023-11314-3.pdf | 2,06 MB | Adobe PDF | Ver/Abrir |
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