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Author Folgado, M.G.; Sanz, V.
Title On the Interpretation of Nonresonant Phenomena at Colliders Type Journal Article
Year 2021 Publication Advances in High Energy Physics Abbreviated Journal Adv. High. Energy Phys.
Volume 2021 Issue Pages 2573471 - 12pp
Keywords
Abstract With null results in resonance searches at the LHC, the physics potential focus is now shifting towards the interpretation of nonresonant phenomena. An example of such shift is the increased popularity of the EFT programme. We can embark on such programme owing to the good integrated luminosity and an excellent understanding of the detectors, which will allow these searches to become more intense as the LHC continues. In this paper, we provide a framework to perform this interpretation in terms of a diverse set of scenarios, including (1) generic heavy new physics described at low energies in terms of a derivative expansion, such as in the EFT approach; (2) very light particles with derivative couplings, such as axions or other light pseudo-Goldstone bosons; and (3) the effect of a quasicontinuum of resonances, which can come from a number of strongly coupled theories, extradimensional models, clockwork set-ups, and their deconstructed cousins. These scenarios are not equivalent despite all nonresonance, although the matching among some of them is possible, and we provide it in this paper.
Address [Folgado, Miguel G.; Sanz, Veronica] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, E-46980 Valencia, Spain, Email: migarfol@ific.uv.es
Corporate Author (up) Thesis
Publisher Hindawi Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1687-7357 ISBN Medium
Area Expedition Conference
Notes WOS:000636258800001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4775
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Author Bernal, N.; Donini, A.; Folgado, M.G.; Rius, N.
Title FIMP Dark Matter in Clockwork/Linear Dilaton extra-dimensions Type Journal Article
Year 2021 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 04 Issue 4 Pages 061 - 29pp
Keywords Beyond Standard Model; Cosmology of Theories beyond the SM; Large Extra Dimensions
Abstract We study the possibility that Dark Matter (DM) is made of Feebly Interacting Massive Particles (FIMP) interacting just gravitationally with the Standard Model particles in the framework of a Clockwork/Linear Dilaton (CW/LD) model. We restrict here to the case in which the DM particles are scalar fields. This paper extends our previous study of FIMP's in Randall-Sundrum (RS) warped extra-dimensions. As it was the case in the RS scenario, also in the CW/LD model we find a significant region of the parameter space in which the observed DM relic abundance can be reproduced with scalar DM mass in the MeV range, with a reheating temperature varying from 10 GeV to 10(9) GeV. We comment on the similarities of the results in both extra-dimensional models.
Address [Bernal, Nicolas] Univ Antonio Narino, Ctr Invest, Carrera 3 Este 47A-15, Bogota, Colombia, Email: nicolas.bernal@uan.edu.co;
Corporate Author (up) 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:000639271100001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4792
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Author Folgado, M.G.; Sanz, V.
Title Exploring the political pulse of a country using data science tools Type Journal Article
Year 2022 Publication Journal of Computational Social Science Abbreviated Journal J. Comput. Soc. Sci.
Volume 5 Issue Pages 987-1000
Keywords Politics; Spain; Sentiment analysis; Artificial Intelligence; Machine learning; Neural networks; Natural Language Processing (NLP)
Abstract In this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train a Fully-Connected Neural Network (FCNN) to recognise the political affiliation of a tweet. The FCNN is able to predict the origin of the tweet with a precision in the range of 71-75%, and the political leaning (left or right) with a precision of around 90%. This study is meant to be viewed as an example of how to use Twitter data and different types of Data Science tools for a political analysis.
Address [Folgado, Miguel G.; Sanz, Veronica] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, Valencia 46980, Spain, Email: migarfol@upvnet.upv.es;
Corporate Author (up) Thesis
Publisher Springernature Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2432-2717 ISBN Medium
Area Expedition Conference
Notes WOS:000742263500002 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5077
Permanent link to this record