PoS - Proceedings of Science
Volume 301 - 35th International Cosmic Ray Conference (ICRC2017) - Session Gamma-Ray Astronomy. GA-galactic
Study of the Interstellar Medium and Cosmic Rays in the MBM 53-55 Clouds and the Pegasus Loop
T. Mizuno* on behalf of the Fermi-LAT Collaboration
*corresponding author
Full text: pdf
Pre-published on: August 16, 2017
Published on: August 03, 2018
High-energy cosmic-ray (CR) protons interact with the interstellar gas
and produce intense diffuse $\gamma$ rays.
Since the interstellar medium (ISM) is transparent to these high-energy photons,
GeV $\gamma$ rays are a powerful probe to study the ISM and Galactic CRs.
In order to study the spatial and spectral distributions of CRs through $\gamma$ rays,
either in the CR accelerators or in the interstellar space,
the interstellar gas column densities need to be estimated with good accuracy using observations in other wavebands such as radio, infrared, and optical.
Radio line observations at 21 cm and 2.6 mm have been used to trace the atomic and molecular gas distributions, respectively.
Yet, a significant amount of gas not traced properly by these surveys was revealed by EGRET and has been confirmed by
using \textit{Fermi} Large Area Telescope (LAT) data.
Although dust distribution has been used to trace these ``dark gas'',
the procedure to convert dust observations into the total gas column density ($N({\rm H_{tot}})$) has not been established yet.
In this contribution, we report the study of ISM and CRs in the nearby molecular clouds MBM 53, 54, and 55 and a far-infrared loop-like structure in Pegasus.
By combining the dust thermal emission model based on Planck data with \textit{Fermi}-LAT $\gamma$-ray data,
it was found that neither the dust radiance ($R$) nor the dust opacity at 353~GHz ($\tau_{353}$) was proportional to $N({\rm H_{tot}})$,
but instead, their ratios ($N({\rm H_{tot}})/R$ or $N({\rm H_{tot}})/\tau_{353}$)
depend on the dust temperature $T_{\rm d}$.
Using the $\gamma$-ray data as a robust gas tracer to compensate for the temperature dependence,
we evaluated $N({\rm H_{tot}})$ distributions
by employing an empirical linear relation
between $N({\rm H_{tot}})/R$ and $T_{\rm d}$.
We present the data analysis, results, and implications for the ISM and CRs.
DOI: https://doi.org/10.22323/1.301.0688
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