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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

On the Physical Association of Fermi-LAT Blazars with Their Low-energy Counterparts

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Autor(es):
de Menezes, Raniere [1, 2] ; D'Abrusco, Raffaele [3] ; Massaro, Francesco [4, 5, 1, 6] ; Gasparrini, Dario [7, 8] ; Nemmen, Rodrigo [2]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Univ Torino, Dipartimento Fis, Via Pietro Giuria 1, I-10125 Turin - Italy
[2] Univ Sao Paulo, Dept Astron, Rua Matao 1226, BR-05508090 Sao Paulo, SP - Brazil
[3] Ctr Astrophys Harvard & Smithsonian, 60 Garden St, Cambridge, MA 20138 - USA
[4] Ist Nazl Fis Nucl, Sez Torino, I-10125 Turin - Italy
[5] INAF Osservatorio Astrofis Torino, Via Osservatorio 20, I-10025 Pino Torinese - Italy
[6] CIFS, Via Pietro Giuria 1, I-10125 Turin - Italy
[7] Ist Nazl Fis Nucl, Sez Roma Tor Vergata, I-00133 Rome - Italy
[8] Space Sci Data Ctr Agenzia Spaziale Italiana, Via Politecn Snc, I-00133 Rome - Italy
Número total de Afiliações: 8
Tipo de documento: Artigo Científico
Fonte: ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES; v. 248, n. 2 JUN 2020.
Citações Web of Science: 0
Resumo

Associating gamma-ray sources to their low-energy counterparts is one of the major challenges of modern gamma-ray astronomy. In the context of the Fourth Fermi Large Area Telescope Source Catalog (4FGL), the associations rely mainly on parameters such as apparent magnitude, integrated flux, and angular separation between the gamma-ray source and its low-energy candidate counterpart. In this work, we propose a new use of the likelihood ratio (LR) and a complementary supervised learning technique to associate gamma-ray blazars in 4FGL, based only on spectral parameters such as the gamma-ray photon index, mid-infrared colors, and radio-loudness. In the LR approach, we crossmatch the Wide-field Infrared Survey Explorer Blazar-Like Radio-Loud Sources catalog with 4FGL and compare the resulting candidate counterparts with the sources listed in the gamma-ray blazar locus to compute an association probability (AP) for 1138 counterparts. In the supervised learning approach, we train a random forest algorithm with 869 high-confidence blazar associations and 711 fake associations and then compute an AP for 1311 candidate counterparts. A list with all 4FGL blazar candidates of uncertain type associated by our method is provided to guide future optical spectroscopic follow-up observations. (AU)

Processo FAPESP: 16/25484-9 - Observações no óptico de candidatos a blazares e fontes de raios gama desconhecidas
Beneficiário:Raniere Maciel de Menezes
Linha de fomento: Bolsas no Brasil - Doutorado
Processo FAPESP: 18/24801-6 - Espectroscopia de fendas multiplas de fontes de raios gama não-identificadas
Beneficiário:Raniere Maciel de Menezes
Linha de fomento: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
Processo FAPESP: 17/01461-2 - O universo extremo: buracos negros e o telescópio Fermi
Beneficiário:Rodrigo Nemmen da Silva
Linha de fomento: Auxílio à Pesquisa - Apoio a Jovens Pesquisadores