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: Tessore, Nicolas (VerfasserIn) , Jahnke, Knud (VerfasserIn) , Sakr, Ziad (VerfasserIn) , Seidel, Gregor (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: February 2025
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
Volltext
Verfasserangaben:N. Tessore, K. Jahnke, Z. Sakr, G. Seidel [und 264 weitere Personen]
Beschreibung
Zusammenfassung: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.
Beschreibung:Online veröffentlicht: 10. Februar 2025
Gesehen am 15.10.2025
Beschreibung:Online Resource
ISSN:1432-0746
DOI:10.1051/0004-6361/202452018