Euclid preparation - LIX. Angular power spectra from discrete observations
In this paper we present the framework for measuring angular power spectra in the Euclid mission. The observables in galaxy surveys, such as galaxy clustering and cosmic shear, are not continuous fields, but discrete sets of data, obtained only at the positions of galaxies. We show how to compute th...
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| Hauptverfasser: | , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
February 2025
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| In: |
Astronomy and astrophysics
Year: 2025, Jahrgang: 694, Pages: 1-27 |
| ISSN: | 1432-0746 |
| DOI: | 10.1051/0004-6361/202452018 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1051/0004-6361/202452018 Verlag, kostenfrei, Volltext: https://www.aanda.org/articles/aa/abs/2025/02/aa52018-24/aa52018-24.html 
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| Verfasserangaben: | N. Tessore, K. Jahnke, Z. Sakr, G. Seidel [und 264 weitere Personen] |
MARC
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| 520 | |a In this paper we present the framework for measuring angular power spectra in the Euclid mission. The observables in galaxy surveys, such as galaxy clustering and cosmic shear, are not continuous fields, but discrete sets of data, obtained only at the positions of galaxies. We show how to compute the angular power spectra of such discrete data sets, without treating observations as maps of an underlying continuous field that is overlaid with a noise component. This formalism allows us to compute the exact theoretical expectations for our measured spectra, under a number of assumptions that we track explicitly. In particular, we obtain exact expressions for the additive biases (‘shot noise’) in angular galaxy clustering and cosmic shear. For efficient practical computations, we introduce a spin-weighted spherical convolution with a well-defined convolution theorem, which allows us to apply exact theoretical predictions to finite-resolution maps, including HEALPix. When validating our methodology, we find that our measurements are biased by less than 1% of their statistical uncertainty in simulations of Euclid’s first data release. | ||
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