The Picard code for the numerical solution of the Galactic cosmic ray propagation problem allows for high-resolution models that acknowledge the 3D structure of our Galaxy. Picard was used to determine diffuse gamma-ray emission of the Galaxy over the energy range from 100 MeV to 100 TeV. We discuss the impact of a cosmic-ray source distribution aligned with the Galactic spiral arms for a range of such spiral-arm models. As expected, the impact on the gamma-ray emission is most distinct in the inverse-Compton channel, where imprints of the spiral arms are visible and yield predictions that are no longer symmetric to the rotational axis of the Milkyway. We will illustrate these differences by a direct comparison to results from previous axially symmetric Galactic propagation models: we find differences in the gamma-ray flux both on global scales and on local scales related to the spiral arm tangents. We compare gamma-ray flux and spectra at on-arm vs. off-arm projections and characterize the differences to axially symmetric models.
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4 January 2017
HIGH ENERGY GAMMA-RAY ASTRONOMY: 6th International Meeting on High Energy Gamma-Ray Astronomy
11–15 July 2016
Heidelberg, Germany
Research Article|
January 04 2017
Diffuse gamma rays in 3D galactic cosmic-ray propagation models
R. Kissmann;
R. Kissmann
a)
1Institut für Astro-und Teilchenphysik,
Leopold Franzens Universität Innsbruck Technikerstraße
25/8, 6020 Innsbruck, Austria
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F. Niederwanger;
F. Niederwanger
1Institut für Astro-und Teilchenphysik,
Leopold Franzens Universität Innsbruck Technikerstraße
25/8, 6020 Innsbruck, Austria
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O. Reimer;
O. Reimer
1Institut für Astro-und Teilchenphysik,
Leopold Franzens Universität Innsbruck Technikerstraße
25/8, 6020 Innsbruck, Austria
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A. W. Strong
A. W. Strong
2
Max-Planck-Institut für extraterrestrische Physik
, Garching, Germany
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a)
Corresponding author: Ralf.Kissmann@uibk.ac.at
AIP Conf. Proc. 1792, 070011 (2017)
Citation
R. Kissmann, F. Niederwanger, O. Reimer, A. W. Strong; Diffuse gamma rays in 3D galactic cosmic-ray propagation models. AIP Conf. Proc. 4 January 2017; 1792 (1): 070011. https://doi.org/10.1063/1.4969008
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