Euclid: Testing the Copernican principle with next-generation surveys⋆
Astronomy & Astrophysics EDP Sciences 671 (2023) a68
Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 520:3 (2023) 3529-3548
Euclid: Forecasts from the void-lensing cross-correlation⋆
Astronomy & Astrophysics EDP Sciences 670 (2023) a47
Propagating spatially varying multiplicative shear bias to cosmological parameter estimation for stage-IV weak-lensing surveys
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 518:4 (2022) 4909-4920
Abstract:
<jats:title>ABSTRACT</jats:title> <jats:p>We consider the bias introduced by a spatially varying multiplicative shear bias (m-bias) on tomographic cosmic shear angular power spectra. To compute the bias in the power spectra, we estimate the mode-coupling matrix associated with an m-bias map using a computationally efficient pseudo-Cℓ method. This allows us to consider the effect of the m-bias to high ℓ. We then conduct a Fisher matrix analysis to forecast resulting biases in cosmological parameters. For a Euclid-like survey with a spatially varying m-bias, with zero mean and rms of 0.01, we find that parameter biases reach a maximum of $\sim 10 {{\ \rm per\ cent}}$ of the expected statistical error, if multipoles up to ℓmax = 5000 are included. We conclude that the effect of the spatially varying m-bias may be a subdominant but potentially non-negligible contribution to the error budget in forthcoming weak lensing surveys. We also investigate the dependence of parameter biases on the amplitude and angular scale of spatial variations of the m-bias field, and conclude that requirements should be placed on the rms of spatial variations of the m-bias, in addition to any requirement on the mean value. We find that, for a Euclid-like survey, biases generally exceed $\sim 30 {{\ \rm per\ cent}}$ of the statistical error for m-bias rms ∼0.02–0.03 and can exceed the statistical error for rms ∼0.04–0.05. This allows requirements to be set on the permissible amplitude of spatial variations of the m-bias that will arise due to systematics in forthcoming weak lensing measurements.</jats:p>Euclid: Fast two-point correlation function covariance through linear construction
ASTRONOMY & ASTROPHYSICS 666 (2022) ARTN A129