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Author |
NEXT Collaboration (Monrabal, F. et al); Laing, A.; Alvarez, V.; Benlloch-Rodriguez, J.M.; Carcel, S.; Carrion, J.V.; Felkai, R.; Martinez, A.; Musti, M.; Querol, M.; Rodriguez, J.; Simon, A.; Torrent, J.; Botas, A.; Diaz, J.; Kekic, M.; Lopez-March, N.; Martinez-Lema, G.; Muñoz Vidal, J.; Nebot-Guinot, M.; Novella, P.; Palmeiro, B.; Perez, J.; Renner, J.; Romo-Luque, C.; Sorel, M.; Yahlali, N. |
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Title |
The NEXT White (NEW) detector |
Type |
Journal Article |
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Year |
2018 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume  |
13 |
Issue |
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Pages |
P12010 - 38pp |
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Keywords |
Double-beta decay detectors; Particle tracking detectors; Scintillators; scintillation and light emission processes (solid gas and liquid scintillators); Time projection chambers |
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Abstract |
Conceived to host 5 kg of xenon at a pressure of 15 bar in the fiducial volume, the NEXT-White apparatus is currently the largest high pressure xenon gas TPC using electroluminescent amplification in the world. It is also a 1:2 scale model of the NEXT-100 detector for Xe-136 beta beta 0 nu decay searches, scheduled to start operations in 2019. Both detectors measure the energy of the event using a plane of photomultipliers located behind a transparent cathode. They can also reconstruct the trajectories of charged tracks in the dense gas of the TPC with the help of a plane of silicon photomultipliers located behind the anode. A sophisticated gas system, common to both detectors, allows the high gas purity needed to guarantee a long electron lifetime. NEXT-White has been operating since October 2016 at the Laboratorio Subterraneo de Canfranc (LSC), in Spain. This paper describes the detector and associated infrastructures, as well as the main aspects of its initial operation. |
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Address |
[Ouero, M.; Hauptman, J.] Iowa State Univ, Dept Phys & Astron, 12 Phys Hall, Ames, IA 50011 USA, Email: monrabal18@gmail.com |
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Publisher |
Iop Publishing Ltd |
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English |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
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Conference |
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Notes |
WOS:000452463500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3833 |
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Author |
Yamamoto, H. |
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Title |
The International Linear Collider Project-Its Physics and Status |
Type |
Journal Article |
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Year |
2021 |
Publication |
Symmetry-Basel |
Abbreviated Journal |
Symmetry-Basel |
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Volume |
13 |
Issue |
4 |
Pages |
674 - 15pp |
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Keywords |
Higgs particle; elementary particles; standard theory; linear collider; dark matter; top quark |
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Abstract |
The discovery of Higgs particle has ushered in a new era of particle physics. Even though the list of members of the standard theory of particle physics is now complete, the shortcomings of the theory became ever more acute. It is generally considered that the best solution to the problems is an electron-positron collider that can study Higgs particle with high precision and high sensitivity; namely, a Higgs factory. Among a few candidates for Higgs factory, the International Linear Collider (ILC) is currently the most advanced in its program. In this article, we review the physics and the project status of the ILC including its energy expandability. |
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Address |
[Yamamoto, Hitoshi] Tohoku Univ, Grad Sch Sci, Sendai, Miyagi 9800812, Japan, Email: yhitoshi@epx.phys.tohoku.ac.jp |
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Publisher |
Mdpi |
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Language |
English |
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Conference |
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Notes |
WOS:000643622400001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4797 |
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Author |
Hirn, J.; Garcia, J.E.; Montesinos-Navarro, A.; Sanchez-Martin, R.; Sanz, V.; Verdu, M. |
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Title |
A deep Generative Artificial Intelligence system to predict species coexistence patterns |
Type |
Journal Article |
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Year |
2022 |
Publication |
Methods in Ecology and Evolution |
Abbreviated Journal |
Methods Ecol. Evol. |
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Volume |
13 |
Issue |
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Pages |
1052-1061 |
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Keywords |
artificial intelligence; direct interactions; generative adversarial networks; indirect interactions; species coexistence; variational AutoEncoders |
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Abstract |
Predicting coexistence patterns is a current challenge to understand diversity maintenance, especially in rich communities where these patterns' complexity is magnified through indirect interactions that prevent their approximation with classical experimental approaches. We explore cutting-edge Machine Learning techniques called Generative Artificial Intelligence (GenAI) to predict species coexistence patterns in vegetation patches, training generative adversarial networks (GAN) and variational AutoEncoders (VAE) that are then used to unravel some of the mechanisms behind community assemblage. The GAN accurately reproduces real patches' species composition and plant species' affinity to different soil types, and the VAE also reaches a high level of accuracy, above 99%. Using the artificially generated patches, we found that high-order interactions tend to suppress the positive effects of low-order interactions. Finally, by reconstructing successional trajectories, we could identify the pioneer species with larger potential to generate a high diversity of distinct patches in terms of species composition. Understanding the complexity of species coexistence patterns in diverse ecological communities requires new approaches beyond heuristic rules. Generative Artificial Intelligence can be a powerful tool to this end as it allows to overcome the inherent dimensionality of this challenge. |
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Address |
[Hirn, Johannes; Enrique Garcia, Jose; Sanz, Veronica] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: miguel.verdu@ext.uv.es |
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Publisher |
Wiley |
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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Series Issue |
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Edition |
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ISSN |
2041-210x |
ISBN |
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Area |
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Conference |
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Notes |
WOS:000765239700001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5155 |
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Author |
Rinaldi, M.; Scopetta, S.; Traini, M.; Vento, V. |
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Title |
Double parton correlations and constituent quark models: a light front approach to the valence sector |
Type |
Journal Article |
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Year |
2014 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
12 |
Issue |
12 |
Pages |
028 - 23pp |
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Keywords |
Phenomenological Models; Parton Model |
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Abstract |
An explicit evaluation of the double parton distribution functions (dPDFs), within a relativistic Light-Front approach to constituent quark models, is presented. dPDFs encode information on the correlations between two partons inside a target and represent the non-perturbative QCD ingredient for the description of double parton scattering in proton-proton collisions, a crucial issue in the search of new Physics at the LHC. Valence dPDFs are evaluated at the low scale of the model and the perturbative scale of the experiments is reached by means of QCD evolution. The present results show that the strong correlation effects present at the scale of the model are still sizable, in the valence region, at the experimental scale. At the low values of x presently studied at the LHC the correlations become less relevant, although they are still important for the spin-dependent contributions to unpolarized proton scattering. |
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Address |
[Rinaldi, M.; Scopetta, S.] Univ Perugia, Dipartimento Fis & Geol, I-06100 Perugia, Italy, Email: matteo.rinaldi@pg.infn.it; |
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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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Series Issue |
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Edition |
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ISSN |
1029-8479 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000346002800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2028 |
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Author |
ATLAS Collaboration (Aaboud, M. et al); Alvarez Piqueras, D.; Barranco Navarro, L.; Cabrera Urban, S.; Castillo Gimenez, V.; Cerda Alberich, L.; Costa, M.J.; Fernandez Martinez, P.; Ferrer, A.; Fiorini, L.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gonzalez de la Hoz, S.; Higon-Rodriguez, E.; Jimenez Pena, J.; Lacasta, C.; Mamuzic, J.; Marti-Garcia, S.; Melini, D.; Mitsou, V.A.; Pedraza Lopez, S.; Rodriguez Rodriguez, D.; Romero Adam, E.; Salt, J.; Sanchez Martinez, V.; Soldevila, U.; Sanchez, J.; Valero, A.; Valls Ferrer, J.A.; Vos, M. |
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Title |
Performance of the ATLAS Transition Radiation Tracker in Run 1 of the LHC: tracker properties |
Type |
Journal Article |
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Year |
2017 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
12 |
Issue |
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Pages |
P05002 - 42pp |
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Keywords |
Particle tracking detectors (Gaseous detectors); Transition radiation detectors |
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Abstract |
The tracking performance parameters of the ATLAS Transition Radiation Tracker (TRT) as part of the ATLAS inner detector are described in this paper for different data-taking conditions in proton-proton, proton-lead and lead-lead collisions at the Large Hadron Collider (LHC). The performance is studied using data collected during the first period of LHC operation (Run 1) and is compared with Monte Carlo simulations. The performance of the TRT, operating with two different gas mixtures (xenon-based and argon-based) and its dependence on the TRT occupancy is presented. These studies show that the tracking performance of the TRT is similar for the two gas mixtures and that a significant contribution to the particle momentum resolution is made by the TRT up to high particle densities. |
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Address |
[Jackson, P.; Lee, L.; Petridis, A.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia, Email: atlas.publications@cern.ch |
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Corporate Author |
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Thesis |
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Publisher |
Iop Publishing Ltd |
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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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000405076000002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3220 |
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