Lance Miller

Abstract:

This paper describes the VIS processing function (VIS PF) of the Euclid ground segment pipeline, which processes and calibrates raw data from the VIS camera. We present the algorithms used in each processing element along with a description of the on-orbit performance of VIS PF based on performance verification and Q1 datasets. We demonstrate that the principal performance metrics (image quality, astrometric accuracy, photometric calibration) are within pre-launch specifications. The image-to-image photometric scatter is less than 0.8% and absolute astrometric accuracy compared to Gaia is 5 mas. Image quality is stable over all Q1 images, with a full width at half maximum (FWHM) of 0 . ″ 16. The stacked images (combining four nominal and two short exposures) reach I E = 25.6 (10 σ , measured as the variance of 1 . ″ 3 diameter apertures). We also describe quality control metrics provided with each image, and an appendix provides a detailed description of the provided data products. The excellent quality of these images demonstrates the immense potential of Euclid VIS data for weak lensing. VIS data covering most of the extragalactic sky will provide a lasting high-resolution atlas of the Universe.

Abstract:

We present a quadratic estimator that detects and reconstructs spatially varying multiplicative (m-) bias in weak lensing shear measurements, by exploiting the mode coupling that it generates. The method combines E and B modes with inverse-variance weights, to yield an unbiased reconstruction of to first order. We study the ability of future Stage IV surveys to obtain an unbiased reconstruction of the m-bias in differing scenarios, considering differing bias morphologies, and characteristic scales, as well as differing metrics to quantify the signal-to-noise ratio of the reconstructed map. We consider an m pattern repeating on sky patches, as might be the case for an m field caused by focal-plane systematics. With a Euclid-like redshift distribution, we find that root mean square (rms) variations in m-bias may be detected at the 20 level, after stacking between and patches (rising to between and for 1 per cent rms variations, data volumes that are becoming available with upcoming surveys), depending on the morphology of the m pattern. We show that these results are robust against the cosmological model assumed in the reconstruction, as well as the presence of intrinsic alignments or baryonic effects, and that the method shows no spurious response to additive (c-) bias. These results demonstrate that percent-level, spatially varying m-bias can be detected at high significance, enabling diagnosis and mitigation in the Stage IV weak lensing era.

Abstract:

We present cosmic shear constraints from the completed Kilo-Degree Survey (KiDS), where the cosmological parameter S 8 ≡ σ 8 √Ω m /0.3 = 0.81 +0.016 −0.021 is found to be in agreement (0.73 σ ) with results from the Planck Legacy cosmic microwave background experiment. The final KiDS footprint spans 1347 square degrees of deep nine-band imaging across the optical and near-infrared (NIR), along with an extra 23-square degrees of KiDS-like calibration observations of deep spectroscopic surveys. Improvements in our redshift distribution estimation methodology, combined with our enhanced calibration data and multi-band image simulations, allowed us to extend our lensed sample out to a photometric redshift of z B ≤ 2.0. Compared to previous KiDS analyses, the increased survey area and redshift depth results in a ∼32% improvement in constraining power in terms of Σ 8 ≡ σ 8 (Ω m /0.3) α = 0.821 +0.014 −0.016 , where α = 0.58 has been optimised to match the revised degeneracy direction of σ 8 and Ω m for our current survey at higher redshift. We adopted a new physically motivated intrinsic alignment (IA) model that jointly depends on the galaxy sample’s halo mass and spectral type distributions, and which is informed by previous direct alignment measurements. We also marginalised over our uncertainty on the impact of baryon feedback on the non-linear matter power spectrum. Compared to previous KiDS analyses, we conclude that the increase seen in S 8 primarily results from our improved redshift distribution estimation and calibration, as well as a new survey area and improved image reduction. Our companion paper presents a full suite of internal and external consistency tests (including joint constraints with other datasets), finding the KiDS-Legacy dataset to be the most internally robust sample produced by KiDS to date.