Gamma/hadron separation with the HAWC observatory

R. Alfaro; C. Alvarez; J. D. Álvarez; J. R. Angeles Camacho; J. C. Arteaga-Velázquez; D. Avila Rojas; H. A. Ayala Solares; R. Babu; E. Belmont-Moreno; C. Brisbois; K. S. Caballero-Mora; T. Capistrán; A. Carramiñana; S. Casanova; O. Chaparro-Amaro; U. Cotti; J. Cotzomi; S. Coutiño de León; E. De la Fuente; C. de León; R. Diaz Hernandez; B. L. Dingus; M. A. DuVernois; M. Durocher; J. C. Díaz-Vélez; R. W. Ellsworth; K. Engel; C. Espinoza; K. L. Fan; M. Fernández Alonso; N. Fraija; D. Garcia; J. A. García-González; F. Garfias; M. M. González; J. A. Goodman; J. P. Harding; S. Hernandez; B. Hona; D. Huang; F. Hueyotl-Zahuantitla; P. Hüntemeyer; A. Iriarte; A. Jardin-Blicq; V. Joshi; S. Kaufmann; G. J. Kunde; A. Lara; W. H. Lee; J. Lee; H. León Vargas; J. T. Linnemann; G. Luis-Raya; J. Lundeen; K. Malone; V. Marandon; O. Martinez; J. Martínez-Castro; J. A. Matthews; P. Miranda-Romagnoli; J. A. Morales-Soto; A. Nayerhoda; L. Nellen; M. U. Nisa; R. Noriega-Papaqui; L. Olivera-Nieto; N. Omodei; A. Peisker; Y. Pérez Araujo; E. G. Pérez-Pérez; C. D. Rho; D. Rosa-González; E. Ruiz-Velasco; H. Salazar; F. Salesa Greus; A. Sandoval; P. M. Saz Parkinson; J. Serna-Franco; A. J. Smith; R. W. Springer; O. Tibolla; K. Tollefson; I. Torres; R. Torres-Escobedo; R. Turner; F. Ureña-Mena; L. Villaseñor; X. Wang; I. J. Watson; F. Werner; E. Willox; J. Wood; A. Zepeda; H. Zhou

doi:10.1016/j.nima.2022.166984

Gamma/hadron separation with the HAWC observatory

R. Alfaro, C. Alvarez, J. D. Álvarez, J. R. Angeles Camacho, J. C. Arteaga-Velázquez, D. Avila Rojas, H. A. Ayala Solares, R. Babu, E. Belmont-Moreno, C. Brisbois, K. S. Caballero-Mora, T. Capistrán, A. Carramiñana, S. Casanova, O. Chaparro-Amaro, U. Cotti, J. Cotzomi, S. Coutiño de León, E. De la Fuente, C. de LeónR. Diaz Hernandez, B. L. Dingus, M. A. DuVernois, M. Durocher, J. C. Díaz-Vélez, R. W. Ellsworth, K. Engel, C. Espinoza, K. L. Fan, M. Fernández Alonso, N. Fraija, D. Garcia, J. A. García-González, F. Garfias, M. M. González, J. A. Goodman, J. P. Harding, S. Hernandez, B. Hona, D. Huang, F. Hueyotl-Zahuantitla, P. Hüntemeyer, A. Iriarte, A. Jardin-Blicq, V. Joshi, S. Kaufmann, G. J. Kunde, A. Lara, W. H. Lee, J. Lee, H. León Vargas, J. T. Linnemann, G. Luis-Raya, J. Lundeen, K. Malone, V. Marandon, O. Martinez, J. Martínez-Castro, J. A. Matthews, P. Miranda-Romagnoli, J. A. Morales-Soto, A. Nayerhoda, L. Nellen, M. U. Nisa, R. Noriega-Papaqui, L. Olivera-Nieto, N. Omodei, A. Peisker, Y. Pérez Araujo, E. G. Pérez-Pérez, C. D. Rho, D. Rosa-González, E. Ruiz-Velasco, H. Salazar, F. Salesa Greus, A. Sandoval, P. M. Saz Parkinson, J. Serna-Franco, A. J. Smith, R. W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Ureña-Mena, L. Villaseñor, X. Wang, I. J. Watson, F. Werner, E. Willox, J. Wood, A. Zepeda, H. Zhou

Department of Physics

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11 Scopus citations

Abstract

The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes atmospheric showers produced by incident gamma rays and cosmic rays with energy from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray sources using ground-based gamma-ray detectors like HAWC is to identify the showers produced by gamma rays or hadrons. The HAWC observatory records roughly 25,000 events per second, with hadrons representing the vast majority (>99.9%) of these events. The standard gamma/hadron separation technique in HAWC uses a simple rectangular cut involving only two parameters. This work describes the implementation of more sophisticated gamma/hadron separation techniques, via machine learning methods (boosted decision trees and neural networks), and summarizes the resulting improvements in gamma/hadron separation obtained in HAWC.

Original language	English
Article number	166984
Journal	Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Volume	1039
DOIs	https://doi.org/10.1016/j.nima.2022.166984
State	Published - 11 Sep 2022

Keywords

Crab Nebula
G/H separation
High energy
Machine Learning

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10.1016/j.nima.2022.166984

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Alfaro, R., Alvarez, C., Álvarez, J. D., Angeles Camacho, J. R., Arteaga-Velázquez, J. C., Avila Rojas, D., Ayala Solares, H. A., Babu, R., Belmont-Moreno, E., Brisbois, C., Caballero-Mora, K. S., Capistrán, T., Carramiñana, A., Casanova, S., Chaparro-Amaro, O., Cotti, U., Cotzomi, J., de León, S. C., De la Fuente, E., ... Zhou, H. (2022). Gamma/hadron separation with the HAWC observatory. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1039, Article 166984. https://doi.org/10.1016/j.nima.2022.166984

@article{ddad2188a3ed4f2bbc6695f0b12f1f35,

title = "Gamma/hadron separation with the HAWC observatory",

abstract = "The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes atmospheric showers produced by incident gamma rays and cosmic rays with energy from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray sources using ground-based gamma-ray detectors like HAWC is to identify the showers produced by gamma rays or hadrons. The HAWC observatory records roughly 25,000 events per second, with hadrons representing the vast majority (>99.9\%) of these events. The standard gamma/hadron separation technique in HAWC uses a simple rectangular cut involving only two parameters. This work describes the implementation of more sophisticated gamma/hadron separation techniques, via machine learning methods (boosted decision trees and neural networks), and summarizes the resulting improvements in gamma/hadron separation obtained in HAWC.",

keywords = "Crab Nebula, G/H separation, High energy, Machine Learning",

author = "R. Alfaro and C. Alvarez and {\'A}lvarez, \{J. D.\} and \{Angeles Camacho\}, \{J. R.\} and Arteaga-Vel{\'a}zquez, \{J. C.\} and \{Avila Rojas\}, D. and \{Ayala Solares\}, \{H. A.\} and R. Babu and E. Belmont-Moreno and C. Brisbois and Caballero-Mora, \{K. S.\} and T. Capistr{\'a}n and A. Carrami{\~n}ana and S. Casanova and O. Chaparro-Amaro and U. Cotti and J. Cotzomi and \{de Le{\'o}n\}, \{S. Couti{\~n}o\} and \{De la Fuente\}, E. and \{de Le{\'o}n\}, C. and \{Diaz Hernandez\}, R. and Dingus, \{B. L.\} and DuVernois, \{M. A.\} and M. Durocher and D{\'i}az-V{\'e}lez, \{J. C.\} and Ellsworth, \{R. W.\} and K. Engel and C. Espinoza and Fan, \{K. L.\} and \{Fern{\'a}ndez Alonso\}, M. and N. Fraija and D. Garcia and Garc{\'i}a-Gonz{\'a}lez, \{J. A.\} and F. Garfias and Gonz{\'a}lez, \{M. M.\} and Goodman, \{J. A.\} and Harding, \{J. P.\} and S. Hernandez and B. Hona and D. Huang and F. Hueyotl-Zahuantitla and P. H{\"u}ntemeyer and A. Iriarte and A. Jardin-Blicq and V. Joshi and S. Kaufmann and Kunde, \{G. J.\} and A. Lara and Lee, \{W. H.\} and J. Lee and \{Le{\'o}n Vargas\}, H. and Linnemann, \{J. T.\} and G. Luis-Raya and J. Lundeen and K. Malone and V. Marandon and O. Martinez and J. Mart{\'i}nez-Castro and Matthews, \{J. A.\} and P. Miranda-Romagnoli and Morales-Soto, \{J. A.\} and A. Nayerhoda and L. Nellen and Nisa, \{M. U.\} and R. Noriega-Papaqui and L. Olivera-Nieto and N. Omodei and A. Peisker and \{P{\'e}rez Araujo\}, Y. and P{\'e}rez-P{\'e}rez, \{E. G.\} and Rho, \{C. D.\} and D. Rosa-Gonz{\'a}lez and E. Ruiz-Velasco and H. Salazar and \{Salesa Greus\}, F. and A. Sandoval and \{Saz Parkinson\}, \{P. M.\} and J. Serna-Franco and Smith, \{A. J.\} and Springer, \{R. W.\} and O. Tibolla and K. Tollefson and I. Torres and R. Torres-Escobedo and R. Turner and F. Ure{\~n}a-Mena and L. Villase{\~n}or and X. Wang and Watson, \{I. J.\} and F. Werner and E. Willox and J. Wood and A. Zepeda and H. Zhou",

note = "Publisher Copyright: {\textcopyright} 2022",

year = "2022",

month = sep,

day = "11",

doi = "10.1016/j.nima.2022.166984",

language = "English",

volume = "1039",

journal = "Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment",

issn = "0168-9002",

publisher = "Elsevier B.V.",

}

Alfaro, R, Alvarez, C, Álvarez, JD, Angeles Camacho, JR, Arteaga-Velázquez, JC, Avila Rojas, D, Ayala Solares, HA, Babu, R, Belmont-Moreno, E, Brisbois, C, Caballero-Mora, KS, Capistrán, T, Carramiñana, A, Casanova, S, Chaparro-Amaro, O, Cotti, U, Cotzomi, J, de León, SC, De la Fuente, E, de León, C, Diaz Hernandez, R, Dingus, BL, DuVernois, MA, Durocher, M, Díaz-Vélez, JC, Ellsworth, RW, Engel, K, Espinoza, C, Fan, KL, Fernández Alonso, M, Fraija, N, Garcia, D, García-González, JA, Garfias, F, González, MM, Goodman, JA, Harding, JP, Hernandez, S, Hona, B, Huang, D, Hueyotl-Zahuantitla, F, Hüntemeyer, P, Iriarte, A, Jardin-Blicq, A, Joshi, V, Kaufmann, S, Kunde, GJ, Lara, A, Lee, WH, Lee, J, León Vargas, H, Linnemann, JT, Luis-Raya, G, Lundeen, J, Malone, K, Marandon, V, Martinez, O, Martínez-Castro, J, Matthews, JA, Miranda-Romagnoli, P, Morales-Soto, JA, Nayerhoda, A, Nellen, L, Nisa, MU, Noriega-Papaqui, R, Olivera-Nieto, L, Omodei, N, Peisker, A, Pérez Araujo, Y, Pérez-Pérez, EG, Rho, CD, Rosa-González, D, Ruiz-Velasco, E, Salazar, H, Salesa Greus, F, Sandoval, A, Saz Parkinson, PM, Serna-Franco, J, Smith, AJ, Springer, RW, Tibolla, O, Tollefson, K, Torres, I, Torres-Escobedo, R, Turner, R, Ureña-Mena, F, Villaseñor, L, Wang, X, Watson, IJ, Werner, F, Willox, E, Wood, J, Zepeda, A & Zhou, H 2022, 'Gamma/hadron separation with the HAWC observatory', Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 1039, 166984. https://doi.org/10.1016/j.nima.2022.166984

TY - JOUR

T1 - Gamma/hadron separation with the HAWC observatory

AU - Alfaro, R.

AU - Alvarez, C.

AU - Álvarez, J. D.

AU - Angeles Camacho, J. R.

AU - Arteaga-Velázquez, J. C.

AU - Avila Rojas, D.

AU - Ayala Solares, H. A.

AU - Babu, R.

AU - Belmont-Moreno, E.

AU - Brisbois, C.

AU - Caballero-Mora, K. S.

AU - Capistrán, T.

AU - Carramiñana, A.

AU - Casanova, S.

AU - Chaparro-Amaro, O.

AU - Cotti, U.

AU - Cotzomi, J.

AU - de León, S. Coutiño

AU - De la Fuente, E.

AU - de León, C.

AU - Diaz Hernandez, R.

AU - Dingus, B. L.

AU - DuVernois, M. A.

AU - Durocher, M.

AU - Díaz-Vélez, J. C.

AU - Ellsworth, R. W.

AU - Engel, K.

AU - Espinoza, C.

AU - Fan, K. L.

AU - Fernández Alonso, M.

AU - Fraija, N.

AU - Garcia, D.

AU - García-González, J. A.

AU - Garfias, F.

AU - González, M. M.

AU - Goodman, J. A.

AU - Harding, J. P.

AU - Hernandez, S.

AU - Hona, B.

AU - Huang, D.

AU - Hueyotl-Zahuantitla, F.

AU - Hüntemeyer, P.

AU - Iriarte, A.

AU - Jardin-Blicq, A.

AU - Joshi, V.

AU - Kaufmann, S.

AU - Kunde, G. J.

AU - Lara, A.

AU - Lee, W. H.

AU - Lee, J.

AU - León Vargas, H.

AU - Linnemann, J. T.

AU - Luis-Raya, G.

AU - Lundeen, J.

AU - Malone, K.

AU - Marandon, V.

AU - Martinez, O.

AU - Martínez-Castro, J.

AU - Matthews, J. A.

AU - Miranda-Romagnoli, P.

AU - Morales-Soto, J. A.

AU - Nayerhoda, A.

AU - Nellen, L.

AU - Nisa, M. U.

AU - Noriega-Papaqui, R.

AU - Olivera-Nieto, L.

AU - Omodei, N.

AU - Peisker, A.

AU - Pérez Araujo, Y.

AU - Pérez-Pérez, E. G.

AU - Rho, C. D.

AU - Rosa-González, D.

AU - Ruiz-Velasco, E.

AU - Salazar, H.

AU - Salesa Greus, F.

AU - Sandoval, A.

AU - Saz Parkinson, P. M.

AU - Serna-Franco, J.

AU - Smith, A. J.

AU - Springer, R. W.

AU - Tibolla, O.

AU - Tollefson, K.

AU - Torres, I.

AU - Torres-Escobedo, R.

AU - Turner, R.

AU - Ureña-Mena, F.

AU - Villaseñor, L.

AU - Wang, X.

AU - Watson, I. J.

AU - Werner, F.

AU - Willox, E.

AU - Wood, J.

AU - Zepeda, A.

AU - Zhou, H.

PY - 2022/9/11

Y1 - 2022/9/11

N2 - The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes atmospheric showers produced by incident gamma rays and cosmic rays with energy from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray sources using ground-based gamma-ray detectors like HAWC is to identify the showers produced by gamma rays or hadrons. The HAWC observatory records roughly 25,000 events per second, with hadrons representing the vast majority (>99.9%) of these events. The standard gamma/hadron separation technique in HAWC uses a simple rectangular cut involving only two parameters. This work describes the implementation of more sophisticated gamma/hadron separation techniques, via machine learning methods (boosted decision trees and neural networks), and summarizes the resulting improvements in gamma/hadron separation obtained in HAWC.

AB - The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes atmospheric showers produced by incident gamma rays and cosmic rays with energy from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray sources using ground-based gamma-ray detectors like HAWC is to identify the showers produced by gamma rays or hadrons. The HAWC observatory records roughly 25,000 events per second, with hadrons representing the vast majority (>99.9%) of these events. The standard gamma/hadron separation technique in HAWC uses a simple rectangular cut involving only two parameters. This work describes the implementation of more sophisticated gamma/hadron separation techniques, via machine learning methods (boosted decision trees and neural networks), and summarizes the resulting improvements in gamma/hadron separation obtained in HAWC.

KW - Crab Nebula

KW - G/H separation

KW - High energy

KW - Machine Learning

UR - https://www.scopus.com/pages/publications/85133305339

U2 - 10.1016/j.nima.2022.166984

DO - 10.1016/j.nima.2022.166984

M3 - Article

AN - SCOPUS:85133305339

SN - 0168-9002

VL - 1039

JO - Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

JF - Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

M1 - 166984

ER -

Gamma/hadron separation with the HAWC observatory

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Keywords

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