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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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Publisher |
Oxford Univ Press |
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English |
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ISSN |
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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Author |
KM3NeT Collaboration (Aiello, S. et al); Alves Garre, S.; Calvo, D.; Carretero, V.; Colomer, M.; Garcia Soto, A.; Gozzini, S.R.; Hernandez-Rey, J.J.; Khan Chowdhury, N.R.; Lazo, A.; Manczak, J.; Palacios Gonzalez, J.; Pieterse, C.; Real, D.; Salesa Greus, F.; Sanchez Losa, A.; Zornoza, J.D.; Zuñiga, J. |
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Title |
The KM3NeT multi-PMT optical module |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
17 |
Issue |
7 |
Pages |
P07038 - 28pp |
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Keywords |
Cherenkov detectors; Large detector systems for particle and astroparticle physics; Neutrino detectors |
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Abstract |
The optical module of the KM3NeT neutrino telescope is an innovative multi-faceted large area photodetection module. It contains 31 three-inch photomultiplier tubes in a single 0.44 m diameter pressure-resistant glass sphere. The module is a sensory device also comprising calibration instruments and electronics for power, readout and data acquisition. It is capped with a breakout-box with electronics for connection to an electro-optical cable for power and long-distance communication to the onshore control station. The design of the module was qualified for the first time in the deep sea in 2013. Since then, the technology has been further improved to meet requirements of scalability, cost-effectiveness and high reliability. The module features a sub-nanosecond timing accuracy and a dynamic range allowing the measurement of a single photon up to a cascade of thousands of photons, suited for the measurement of the Cherenkov radiation induced in water by secondary particles from interactions of neutrinos with energies in the range of GeV to PeV. A distributed production model has been implemented for the delivery of more than 6000 modules in the coming few years with an average production rate of more than 100 modules per month. In this paper a review is presented of the design of the multi-PMT KM3NeT optical module with a proven effective background suppression and signal recognition and sensitivity to the incoming direction of photons. |
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Address |
[Aiello, S.; Bruno, R.; Leonora, E.; Longhitano, F.; Randazzo, N.] Ist Nazl Fis Nucl, Sez Catania, Via Santa Sofia 64, I-95123 Italy, Italy, Email: km3net-pc@km3net.de |
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IOP Publishing Ltd |
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English |
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Edition |
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ISSN |
1748-0221 |
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Conference |
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Notes |
WOS:000898568200003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5449 |
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Author |
Feng, J.L. et al; Garcia Soto, A.; Hirsch, M. |
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Title |
The Forward Physics Facility at the High-Luminosity LHC |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of Physics G |
Abbreviated Journal |
J. Phys. G |
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Volume |
50 |
Issue |
3 |
Pages |
030501 - 410pp |
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Keywords |
Forward Physics Facility; Large Hadron Collider; new particle searches; neutrinos; QCD; astroparticle physics; dark matter |
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Abstract |
High energy collisions at the High-Luminosity Large Hadron Collider (LHC) produce a large number of particles along the beam collision axis, outside of the acceptance of existing LHC experiments. The proposed Forward Physics Facility (FPF), to be located several hundred meters from the ATLAS interaction point and shielded by concrete and rock, will host a suite of experiments to probe standard model (SM) processes and search for physics beyond the standard model (BSM). In this report, we review the status of the civil engineering plans and the experiments to explore the diverse physics signals that can be uniquely probed in the forward region. FPF experiments will be sensitive to a broad range of BSM physics through searches for new particle scattering or decay signatures and deviations from SM expectations in high statistics analyses with TeV neutrinos in this low-background environment. High statistics neutrino detection will also provide valuable data for fundamental topics in perturbative and non-perturbative QCD and in weak interactions. Experiments at the FPF will enable synergies between forward particle production at the LHC and astroparticle physics to be exploited. We report here on these physics topics, on infrastructure, detector, and simulation studies, and on future directions to realize the FPF's physics potential. |
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Address |
[Feng, Jonathan L.; Tsai, Yu-Dai; Bian, Jianming; Casper, David W.; Fieg, Max; Huang, Fei; Kuo, Jui-Lin; Wu, Wenjie] Univ Calif Irvine, Dept Phys & Astron, Irvine, CA 92697 USA, Email: jlf@uci.edu |
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Publisher |
IOP Publishing Ltd |
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English |
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ISSN |
0954-3899 |
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Notes |
WOS:000934195400001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5491 |
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Author |
Salesa Greus, F.; Sanchez Losa, A. |
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Title |
Multimessenger Astronomy with Neutrinos |
Type |
Journal Article |
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Year |
2021 |
Publication |
Universe |
Abbreviated Journal |
Universe |
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Volume |
7 |
Issue |
11 |
Pages |
397 - 11pp |
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Keywords |
multimessenger astronomy; astroparticle physics; neutrinos |
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Abstract |
Multimessenger astronomy is arguably the branch of the astroparticle physics field that has seen the most significant developments in recent years. In this manuscript, we will review the state-of-the-art, the recent observations, and the prospects and challenges for the near future. We will give special emphasis to the observation carried out with neutrino telescopes. |
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Address |
[Salesa Greus, Francisco; Sanchez Losa, Agustin] Univ Valencia, CSIC, IFIC Inst Fis Corpuscular, C Catedratico Jose Beltran 2, E-46980 Paterna, Spain, Email: sagreus@ific.uv.es; |
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Publisher |
Mdpi |
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English |
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Notes |
WOS:000724957500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5036 |
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Author |
Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. |
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Title |
Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge |
Type |
Journal Article |
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Year |
2021 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
656 |
Issue |
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Pages |
A62 - 18pp |
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Keywords |
catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing |
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Abstract |
Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources. |
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Address |
[Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com |
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Publisher |
Edp Sciences S A |
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Language |
English |
Summary Language |
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ISSN |
0004-6361 |
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Notes |
WOS:000725877600001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5053 |
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