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Author |
Folgado, M.G.; Donini, A.; Rius, N. |
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Title |
Gravity-mediated scalar Dark Matter in warped extra-dimensions |
Type |
Journal Article |
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Year |
2020 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
01 |
Issue |
1 |
Pages |
161 - 39pp |
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Keywords  |
Phenomenology of Field Theories in Higher Dimensions |
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Abstract |
We revisit the case of scalar Dark Matter interacting just gravitationally with the Standard Model (SM) particles in an extra-dimensional Randall-Sundrum scenario. We assume that both, the Dark Matter and the Standard Model, are localized in the TeV brane and only interact via gravitational mediators, namely the graviton Kaluza-Klein modes and the radion. We analyze in detail the dark matter annihilation channel into two on-shell KK-gravitons, and contrary to previous studies which overlooked this process, we find that it is possible to obtain the correct relic abundance for dark matter masses in the range [1, 10] TeV even after taking into account the strong bounds from LHC Run II. We also consider the impact of the radion contribution (virtual exchange leading to SM final states as well as on-shell production), which does not significantly change our results. Quite interestingly, a sizeable part of the currently allowed parameter space could be tested by LHC Run III and by the High-Luminosity LHC. |
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Address |
[Folgado, Miguel G.] Univ Valencia, CSIC, Dept Fis Teor, C Catedrat Jose Beltran 2, E-46980 Paterna, Spain, Email: migarfol@ific.uv.es; |
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Springer |
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Language |
English |
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ISSN |
1029-8479 |
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Notes |
WOS:000513955300002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4292 |
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Author |
Folgado, M.G.; Donini, A.; Rius, N. |
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Title |
Gravity-mediated dark matter in clockwork/linear dilaton extra-dimensions |
Type |
Journal Article |
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Year |
2020 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
04 |
Issue |
4 |
Pages |
036 - 46pp |
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Keywords |
Phenomenology of Field Theories in Higher Dimensions; Strings and branes phenomenology |
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Abstract |
We study for the first time the possibility that Dark Matter (represented by particles with spin 0, 1/2 or 1) interacts gravitationally with Standard Model particles in an extra-dimensional Clockwork/Linear Dilaton model. We assume that both, the Dark Matter and the Standard Model, are localized in the IR-brane and only interact via gravitational mediators, namely the Kaluza-Klein (KK) graviton and the radion/KK-dilaton modes. We analyse in detail the Dark Matter annihilation channel into Standard Model particles and into two on-shell Kaluza-Klein towers (either two KK-gravitons, or two radion/KK- dilatons, or one of each), finding that it is possible to obtain the observed relic abundance via thermal freeze-out for Dark Matter masses in the range m(DM) is an element of [1, 15] TeV for a 5- dimensional gravitational scale M-5 ranging from 5 to a few hundreds of TeV, even after taking into account the bounds from LHC Run II and irrespectively of the DM particle spin. |
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Address |
[Folgado, Miguel G.] Univ Valencia, Dept Fis Teor, CSIC, C Catedrat Jose Beltran 2, E-46980 Paterna, Spain, Email: migarfol@ific.uv.es; |
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Corporate Author |
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Thesis |
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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 Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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ISSN |
1029-8479 |
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Area |
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Conference |
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Notes |
WOS:000526531300002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4375 |
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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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English |
Summary Language |
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Series Editor |
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Series Title |
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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 |
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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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