Characterizing γ-ray sources with HAL (HAWC Accelerated Likelihood) and 3ML

Abeysekara AU, Albert A, Alfaro R, Alvarez C, Álvarez JD, Angeles Camacho JR, Arteaga-Velázquez JC, Arunbabu KP, Avila Rojas D, Ayala Solares HA, Babu R, Baghmanyan V, Barber AS, Becerra Gonzalez J, Belmont-Moreno E, BenZvi SY, Berley D, Brisbois C, Caballero-Mora KS, Capistrán T, Carramiñana A, Casanova S, Chaparro-Amaro O, Cotti U, Cotzomi J, Coutiño de León S, De la Fuente E, de León C, Diaz-Cruz L, Diaz Hernandez R, Díaz-Vélez JC, Dingus BL, Durocher M, DuVernois MA, Ellsworth RW, Engel K, Espinoza C, Fan KL, Fang K, Fernández Alonso M, Fick B, Fleischhack H, Flores JL, Fraija NI, Garcia D, García-González JA, García-Luna JL, García-Torales G, Garfias F, Giacinti G, Goksu H, González MM, Goodman JA, Harding JP, Hernandez S, Herzog I, Hinton J, Hona B, Huang D, Hueyotl-Zahuantitla F, Hui CM, Humensky B, Hüntemeyer P, Iriarte A, Jardin-Blicq A, Jhee H, Joshi V, Kieda D, Kunde GJ, Kunwar S, Lara A, Lee J, Lee WH, Lennarz D, León Vargas H, Linnemann J, Longinotti AL, López-Coto R, Luis-Raya G, Lundeen J, Malone K, Marandon V, Martinez O, Martinez-Castellanos I, Martínez-Huerta H, Martínez-Castro J, Matthews JA, McEnery J, Miranda-Romagnoli P, Morales-Soto JA, Moreno E, Mostafá M, Nayerhoda A, Nellen L, Newbold M, Nisa MU, Noriega-Papaqui R, Olivera-Nieto L, Omodei N, Peisker A, Pérez Araujo Y, Pérez-Pérez EG, Rho CD, Rivière C, Rosa-Gonzalez D, Ruiz-Velasco E, Ryan J, Salazar H, Salesa Greus F, Sandoval A, Schneider M, Schoorlemmer H, Serna-Franco J, Sinnis G, Smith AJ, Springer RW, Surajbali P, Taboada I, Tanner M, Tollefson K, Torres I, Torres-Escobedo R, Turner R, Ureña-Mena F, Villaseñor L, Wang X, Watson IJ, Weisgarber T, Werner F, Willox E, Wood J, Yodh GB, Zepeda A, Zhou H (2022)

Publication Type: Conference contribution

Publication year: 2022

Journal

Publisher: Sissa Medialab Srl

Book Volume: 395

Conference Proceedings Title: Proceedings of Science

Event location: Virtual, Berlin, DEU

Abstract

The open-source Multi-Mission Maximum likelihood (3ML) Framework allows for the common analysis of diverse datasets. The ability to consistently fit and characterize astronomical data across many decades in energy is key to understanding the origin of the emission we measure with many different instruments. 3ML uses plugins to encapsulate the interfaces to data and instrument response functions. The user can then define a model with one or multiple sources to describe a given region of interest. The model is fit to the data to determine the locations, spatial shapes, and energy spectra of the sources in the model. The High Altitude Water Cherenkov (HAWC) Observatory, a wide FoV instrument sensitive to energies from 300 GeV to above 100 TeV, has used 3ML for data analysis for several years using a plugin optimized for single source analysis. As multisource fitting became more common, a faster plugin was required. Spectral fits to the Crab Nebula and the nearby source HAWC J0543+233 obtained using HAL, the HAWC plugin for 3ML, will be presented.

Authors with CRIS profile

Involved external institutions

Michigan State University United States (USA) (US) University of Utah United States (USA) (US) Benemérita Universidad Autónoma de Puebla (BUAP) / Meritorious Autonomous University of Puebla Mexico (MX) National Autonomous University of Mexico / Universidad Nacional Autónoma de México (UNAM) Mexico (MX) Pennsylvania State University (Penn State) United States (USA) (US) Michigan Technological University United States (USA) (US) Institute of Nuclear Physics Polish Academy of Sciences / Instytut Fizyki Jądrowej im. Henryka Niewodniczańskiego Polskiej Akademii Nauk Poland (PL) Los Alamos National Laboratory United States (USA) (US) Universidad Autónoma de Chiapas (UNACH) Mexico (MX) Universidad Michoacana de San Nicolás de Hidalgo (UMSNH) Mexico (MX) National Institute of Astrophysics, Optics and Electronics / Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE) Mexico (MX) National Polytechnic Institute of Mexico / Instituto Politécnico Nacional de México Mexico (MX) National Aeronautics and Space Administration (NASA) United States (USA) (US) Universidad de Guadalajara (UDEG) Mexico (MX) University of Rochester (UR) United States (USA) (US) University of Maryland United States (USA) (US) National Institute for Nuclear Physics / Istituto Nazionale di Fisica Nucleare (INFN) Italy (IT) Max-Planck-Institut für Kernphysik (MPIK) / Max Planck Institute for Nuclear Physics Germany (DE) University of New Hampshire United States (USA) (US) University of Seoul (UOS) / 서울시립대학교 Korea, Republic of (KR) Georgia Institute of Technology United States (USA) (US) Shanghai Jiao Tong University / 上海交通大学 China (CN) University of Wisconsin - Madison United States (USA) (US) Universidad de Monterrey (UDEM) Mexico (MX) University of New Mexico (UNM) / Universidad de Nuevo México United States (USA) (US) Autonomous University of the State of Hidalgo / Universidad Autónoma del Estado de Hidalgo Mexico (MX) Stanford University United States (USA) (US) University of California Irvine United States (USA) (US) Tecnológico de Monterrey (ITESM) Mexico (MX) Universidad Politécnica de Pachuca (UPP) Mexico (MX)

How to cite

APA:

Abeysekara, A.U., Albert, A., Alfaro, R., Alvarez, C., Álvarez, J.D., Angeles Camacho, J.R.,... Zhou, H. (2022). Characterizing γ-ray sources with HAL (HAWC Accelerated Likelihood) and 3ML. In Proceedings of Science. Virtual, Berlin, DEU: Sissa Medialab Srl.

MLA:

Abeysekara, A. U., et al. "Characterizing γ-ray sources with HAL (HAWC Accelerated Likelihood) and 3ML." Proceedings of the 37th International Cosmic Ray Conference, ICRC 2021, Virtual, Berlin, DEU Sissa Medialab Srl, 2022.

BibTeX: Download