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Navarro, P.; Gimeno, B.; Alvarez Melcon, A.; Arguedas Cuendis, S.; Cogollos, C.; Diaz-Morcillo, A.; Gallego, J.D.; Garcia Barcelo, J.M.; Golm, J.; Irastorza, I.G.; Lozano Guerrero, A.J.; Garay, C.P. |
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Title |
Wide-band full-wave electromagnetic modal analysis of the coupling between dark-matter axions and photons in microwave resonators |
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Journal Article |
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Year |
2022 |
Publication |
Physics of the Dark Universe |
Abbreviated Journal |
Phys. Dark Universe |
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Volume |
36 |
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Pages |
101001 - 14pp |
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Keywords  |
Axion detection; Axion field; Axion-photon interaction; BI-RME 3D; Broad-band analysis; Dark matter; Full wave analysis; Haloscope; Microwave resonator; Modal technique |
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Abstract |
The electromagnetic coupling axion-photon in a microwave cavity is revisited with the Boundary Integral-Resonant Mode Expansion (BI-RME) 3D technique. Such full-wave modal technique has been applied for the rigorous analysis of the excitation of a microwave cavity with an axion field. In this scenario, the electromagnetic field generated by the axion-photon coupling can be assumed to be driven by equivalent electrical charge and current densities. These densities have been inserted in the general BI-RME 3D equations, which express the RF electromagnetic field existing within a cavity as an integral involving the Dyadic Green's functions of the cavity (under Coulomb gauge) as well as such densities. This method is able to take into account any arbitrary spatial and temporal variation of both magnitude and phase of the axion field. Next, we have obtained a simple network driven by the axion current source, which represents the coupling between the axion field and the resonant modes of the cavity. With this approach, it is possible to calculate the extracted and dissipated RF power as a function of frequency along a broad band and without Cauchy-Lorentz approximations, obtaining the spectrum of the electromagnetic field generated in the cavity, and dealing with modes relatively close to the axion resonant mode. Moreover, with this technique we have a complete knowledge of the signal extracted from the cavity, not only in magnitude but also in phase. This can be an interesting issue for future analysis where the axion phase is an important parameter. |
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Address |
[Navarro, P.; Melcon, A. alvarez; Diaz-Morcillo, A.; Barcelo, J. M. Garcia; Guerrero, A. J. Lozano] Tech Univ Cartagena, Dept Informat & Commun Technol, Cartagena 30203, Spain, Email: pablonm.ct.94@gmail.com; |
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Elsevier |
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English |
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WOS:000791333100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5218 |
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Author |
Gammaldi, V.; Zaldivar, B.; Sanchez-Conde, M.A.; Coronado-Blazquez, J. |
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Title |
A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning |
Type |
Journal Article |
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Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
520 |
Issue |
1 |
Pages |
1348-1361 |
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Keywords |
astroparticle physics – methods; data analysis – methods; observational – methods; statistical – dark matter – gamma-rays; general |
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Abstract |
Around one-third of the point-like sources in the Fermi-LAT catalogues remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma-rays from WIMPs annihilation. We propose a new approach to solve the standard, machine learning (ML) binary classification problem of disentangling prospective DM sources (simulated data) from astrophysical sources (observed data) among the unIDs of the 4FGL Fermi-LAT catalogue. We artificially build two systematic features for the DM data which are originally inherent to observed data: the detection significance and the uncertainty on the spectral curvature. We do it by sampling from the observed population of unIDs, assuming that the DM distributions would, if any, follow the latter. We consider different ML models: Logistic Regression, Neural Network (NN), Naive Bayes, and Gaussian Process, out of which the best, in terms of classification accuracy, is the NN, achieving around 93 . 3 per cent +/- 0 . 7 per cent performance. Other ML evaluation parameters, such as the True Ne gativ e and True Positive rates, are discussed in our work. Applying the NN to the unIDs sample, we find that the de generac y between some astrophysical and DM sources can be partially solved within this methodology. None the less, we conclude that there are no DM source candidates among the pool of 4FGL Fermi-LAT unIDs. |
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Address |
[Gammaldi, V; Sanchez-Conde, M. A.; Coronado-Blazquez, J.] Univ Autonoma Madrid, Departamentode Fis Teor, E-28049 Madrid, Spain, Email: viviana.gammaldi@uam.es; |
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Oxford Univ Press |
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English |
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0035-8711 |
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Notes |
WOS:000937053400014 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5489 |
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