Issue |
A&A
Volume 666, October 2022
|
|
---|---|---|
Article Number | A107 | |
Number of page(s) | 10 | |
Section | Interstellar and circumstellar matter | |
DOI | https://doi.org/10.1051/0004-6361/202244133 | |
Published online | 14 October 2022 |
COSMOGLOBE: Simulating zodiacal emission with ZodiPy★
Institute of Theoretical Astrophysics, University of Oslo,
Blindern, Oslo, Norway
e-mail: metin.san@astro.uio.no
Received:
27
May
2022
Accepted:
22
June
2022
We present ZodiPy, a modern and easy-to-use Python package for modeling the zodiacal emission seen by an arbitrary Solar System observer, which can be used for the removal of both thermal emission and scattered sunlight from interplanetary dust in astrophysical data. The code implements the COBE Diffuse Infrared Background Experiment (DIRBE) interplanetary dust model and the Planck extension, which allows for zodiacal emission predictions at infrared wavelengths in the 1.25–240 µm range and at microwave frequencies in the 30–857 GHz range. The predicted zodiacal emission may be extrapolated to frequencies and wavelengths not covered by the built-in models to produce forecasts for future experiments. ZodiPy attempts to enable the development of new interplanetary dust models by providing the community with an easy-to-use interface for testing both current and future models. We demonstrate how the software can be used by creating simulated zodiacal emission timestreams for the DIRBE experiment and show that these agree with corresponding timestreams produced with the DIRBE Zodiacal Light Prediction Software. We also make binned maps of the zodiacal emission as predicted to be observed by DIRBE and compare them with the DIRBE calibrated individual observations (CIO).
Key words: interplanetary medium / cosmic background radiation / zodiacal dust
This work is part of the Cosmoglobe effort, and the code is published under an open-source license at https://github.com/Cosmoglobe/zodipy
© M. San et al. 2022
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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