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Author Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V. url  doi
openurl 
  Title (up) SMEFT goes dark: Dark Matter models for four-fermion operators Type Journal Article
  Year 2023 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 09 Issue 9 Pages 081 - 47pp  
  Keywords SMEFT; Dark Matter at Colliders; Specific BSM Phenomenology  
  Abstract We study ultra-violet completions for d = 6 four-fermion operators in the standard model effective field theory (SMEFT), focusing on models that contain cold dark matter candidates. Via a diagrammatic method, we generate systematically lists of possible UV completions, with the aim of providing sets of models, which are complete under certain, well specified assumptions. Within these lists of models we rediscover many known DM models, as diverse as R-parity conserving supersymmetry or the scotogenic neutrino mass model. Our lists, however, also contain many new constructions, which have not been studied in the literature so far. We also briefly discuss how our DM models could be constrained by reinterpretations of LHC searches and the prospects for HL-LHC and future lepton colliders.  
  Address [Cepedello, Ricardo] Univ Wurzburg, Inst Theoret Phys & Astrophys, D-97074 Wurzburg, Germany, Email: ricardo.cepedello@physik.uni-wuerzburg.de;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1029-8479 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001067194100002 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5688  
Permanent link to this record
 

 
Author Escudero, M.; Rius, N.; Sanz, V. url  doi
openurl 
  Title (up) Sterile neutrino portal to Dark Matter I: the U(1)(B-L) case Type Journal Article
  Year 2017 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 02 Issue 2 Pages 045 - 27pp  
  Keywords Beyond Standard Model; Neutrino Physics  
  Abstract In this paper we explore the possibility that the sterile neutrino and Dark Matter sectors in the Universe have a common origin. We study the consequences of this assumption in the simple case of coupling the dark sector to the Standard Model via a global U(1)(B-L), broken down spontaneously by a dark scalar. This dark scalar provides masses to the dark fermions and communicates with the Higgs via a Higgs portal coupling. We find an interesting interplay between Dark Matter annihilation to dark scalars – the CP-even that mixes with the Higgs and the CP-odd which becomes a Goldstone boson, the Majoron and heavy neutrinos, as well as collider probes via the coupling to the Higgs. Moreover, Dark Matter annihilation into sterile neutrinos and its subsequent decay to gauge bosons and quarks, charged leptons or neutrinos lead to indirect detection signatures which are close to current bounds on the gamma ray flux from the galactic center and dwarf galaxies.  
  Address [Escudero, Miguel; Rius, Nuria] Univ Valencia, Dept Fis Teor, CSIC, C Catedrat Jose Beltran 2, E-46980 Paterna, Spain, Email: miguel.escudero@ific.uv.es;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1029-8479 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000394747600008 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 3018  
Permanent link to this record
 

 
Author Escudero, M.; Rius, N.; Sanz, V. url  doi
openurl 
  Title (up) Sterile neutrino portal to Dark Matter II: exact dark symmetry Type Journal Article
  Year 2017 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C  
  Volume 77 Issue 6 Pages 397 - 11pp  
  Keywords  
  Abstract We analyze a simple extension of the standard model (SM) with a dark sector composed of a scalar and a fermion, both singlets under the SM gauge group but charged under a dark sector symmetry group. Sterile neutrinos, which are singlets under both groups, mediate the interactions between the dark sector and the SM particles, and generate masses for the active neutrinos via the seesaw mechanism. We explore the parameter space region where the observed Dark Matter relic abundance is determined by the annihilation into sterile neutrinos, both for fermion and scalar Dark Matter particles. The scalar Dark Matter case provides an interesting alternative to the usual Higgs portal scenario. We also study the constraints from direct Dark Matter searches and the prospects for indirect detection via sterile neutrino decays to leptons, which may be able to rule out Dark Matter masses below and around 100 GeV.  
  Address [Escudero, Miguel; Rius, Nuria] Univ Valencia, CSIC, Dept Fis Teor, C Catedrat Jose Beltran 2, Paterna 46980, Spain, Email: miguel.escudero@ific.uv.es;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1434-6044 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000403504200002 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 3171  
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Author Barenboim, G.; Hirn, J.; Sanz, V. url  doi
openurl 
  Title (up) Symmetry meets AI Type Journal Article
  Year 2021 Publication Scipost Physics Abbreviated Journal SciPost Phys.  
  Volume 11 Issue 1 Pages 014 - 11pp  
  Keywords  
  Abstract We explore whether Neural Networks (NNs) can discover the presence of symmetries as they learn to perform a task. For this, we train hundreds of NNs on a decoy task based on well-controlled Physics templates, where no information on symmetry is provided. We use the output from the last hidden layer of all these NNs, projected to fewer dimensions, as the input for a symmetry classification task, and show that information on symmetry had indeed been identified by the original NN without guidance. As an interdisciplinary application of this procedure, we identify the presence and level of symmetry in artistic paintings from different styles such as those of Picasso, Pollock and Van Gogh.  
  Address [Barenboim, Gabriela; Hirn, Johannes; Sanz, Veronica] Univ Valencia, CSIC, Dept Fis Teor, E-46100 Burjassot, Spain  
  Corporate Author Thesis  
  Publisher Scipost Foundation Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2542-4653 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000680039500002 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4920  
Permanent link to this record
 

 
Author Kasieczka, G. et al; Sanz, V. url  doi
openurl 
  Title (up) The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics Type Journal Article
  Year 2021 Publication Reports on Progress in Physics Abbreviated Journal Rep. Prog. Phys.  
  Volume 84 Issue 12 Pages 124201 - 64pp  
  Keywords anomaly detection; machine learning; unsupervised learning; weakly supervised learning; semisupervised learning; beyond the standard model; model-agnostic methods  
  Abstract A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.  
  Address [Kasieczka, Gregor] Univ Hamburg, Inst Expt Phys, Hamburg, Germany, Email: gregor.kasieczka@uni-hamburg.de;  
  Corporate Author Thesis  
  Publisher IOP Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0034-4885 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000727698500001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5039  
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