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Author |
Folgado, M.G.; Sanz, V. |
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Title |
On the Interpretation of Nonresonant Phenomena at Colliders |
Type |
Journal Article |
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Year |
2021 |
Publication |
Advances in High Energy Physics |
Abbreviated Journal |
Adv. High. Energy Phys. |
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Volume |
2021 |
Issue |
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Pages |
2573471 - 12pp |
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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. |
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Address |
[Folgado, Miguel G.; Sanz, Veronica] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, E-46980 Valencia, Spain, Email: migarfol@ific.uv.es |
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Publisher |
Hindawi Ltd |
Place of Publication |
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Language |
English |
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Edition |
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ISSN |
1687-7357 |
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Notes |
WOS:000636258800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4775 |
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Author |
Bernal, N.; Donini, A.; Folgado, M.G.; Rius, N. |
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Title |
FIMP Dark Matter in Clockwork/Linear Dilaton extra-dimensions |
Type |
Journal Article |
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Year |
2021 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
04 |
Issue |
4 |
Pages |
061 - 29pp |
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Keywords |
Beyond Standard Model; Cosmology of Theories beyond the SM; Large Extra Dimensions |
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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. |
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Address |
[Bernal, Nicolas] Univ Antonio Narino, Ctr Invest, Carrera 3 Este 47A-15, Bogota, Colombia, Email: nicolas.bernal@uan.edu.co; |
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Publisher |
Springer |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Volume |
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Edition |
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ISSN |
1029-8479 |
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Notes |
WOS:000639271100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4792 |
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Author |
Folgado, M.G.; Sanz, V. |
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Title |
Exploring the political pulse of a country using data science tools |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Computational Social Science |
Abbreviated Journal |
J. Comput. Soc. Sci. |
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Volume |
5 |
Issue |
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Pages |
987-1000 |
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Keywords |
Politics; Spain; Sentiment analysis; Artificial Intelligence; Machine learning; Neural networks; Natural Language Processing (NLP) |
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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. |
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Address |
[Folgado, Miguel G.; Sanz, Veronica] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, Valencia 46980, Spain, Email: migarfol@upvnet.upv.es; |
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Springernature |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2432-2717 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000742263500002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5077 |
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