Robust cosmic shear with small-scale nulling

(2025)

Authors:

Giulia Piccirilli, Matteo Zennaro, Carlos García-García, David Alonso

On unveiling Buried Nuclei with JWST: a technique for hunting the most obscured galaxy nuclei from local to high redshift

(2025)

Authors:

I García-Bernete, FR Donnan, D Rigopoulou, M Pereira-Santaella, E González-Alfonso, N Thatte, S Aalto, S König, M Maksymowicz-Maciata, MWR Smith, J-S Huang, GE Magdis, PF Roche, J Devriendt, A Slyz

Cosmological constraints using Minkowski functionals from the first year data of the Hyper Suprime-Cam

Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 537:4 (2025) 3553-3560

Authors:

Joaquin Armijo, Gabriela A Marques, Camila P Novaes, Leander Thiele, Jessica A Cowell, Daniela Grandón, Masato Shirasaki, Jia Liu

Validating a main beam treatment of parametric, pixel-based component separation in the context of CMB observations

Physical Review D 111:4 (2025)

Authors:

A Rizzieri, J Errard, R Stompor

Abstract:

We implement a simple, main beam correction in the maximum-likelihood, parametric component separation approach, which allows on accounting for different beam widths of input maps at different frequencies without any preprocessing. We validate the approach on full-sky and cut-sky simulations and discuss the importance and impact of the assumptions and simplifications. We find that, in the cases when the underlying sky model is indeed parametric, the method successfully recovers component spectral parameters and component maps at the predefined resolution. The improvement on the precision of the estimated spectral parameters is found to be minor due to the redness of the foreground angular spectra, however the method is potentially more accurate, in particular if the foreground properties display strong, spatial variability, as it does not assume commutation of the beam smoothing and mixing matrix operators. The method permits a reconstruction of the cosmic microwave background map with a resolution significantly superior to that of the lowest resolution map used in the analysis and with the nearly optimal noise level, facilitating exploitation of the cosmological information contained on angular scales, which would be otherwise inaccessible. The method preserves all the advantages of a pixel-domain implementation of the parametric approach, and, as it deals with the beams in the harmonic domain, it can also straightforwardly account for spatially stationary map-domain noise correlations.

Euclid preparation

Astronomy & Astrophysics EDP Sciences 694 (2025) ARTN A141

Authors:

N Tessore, B Joachimi, A Loureiro, A Hall, G Cañas-Herrera, I Tutusaus, N Jeffrey, K Naidoo, Jd McEwen, A Amara, S Andreon, N Auricchio, C Baccigalupi, M Baldi, S Bardelli, F Bernardeau, D Bonino, E Branchini, M Brescia, J Brinchmann, A Caillat, S Camera, V Capobianco, C Carbone, Vf Cardone, J Carretero, S Casas, M Castellano, G Castignani, S Cavuoti, A Cimatti, C Colodro-Conde, G Congedo, Cj Conselice, L Conversi, Y Copin, F Courbin, Hm Courtois, M Cropper, A Da Silva, H Degaudenzi, G De Lucia, J Dinis, F Dubath, Caj Duncan, X Dupac, S Dusini, M Farina, S Farrens, F Faustini

Abstract:

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.