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  • 1
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 671 ( 2023-3), p. A101-
    Abstract: The European Space Agency's Euclid mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in real time is being developed by the Science Ground Segment of the Euclid Consortium; this pipeline will include a model-fitting algorithm, which will provide photometric and morphological estimates of paramount importance for the core science goals of the mission and for legacy science. The Euclid Morphology Challenge is a comparative investigation of the performance of five model-fitting software packages on simulated Euclid data, aimed at providing the baseline to identify the best-suited algorithm to be implemented in the pipeline. In this paper we describe the simulated dataset, and we discuss the photometry results. A companion paper is focussed on the structural and morphological estimates. We created mock Euclid images simulating five fields of view of 0.48 deg 2 each in the I E band of the VIS instrument, containing a total of about one and a half million galaxies (of which 350 000 have a nominal signal-to-noise ratio above 5), each with three realisations of galaxy profiles (single and double Sérsic, and 'realistic' profiles obtained with a neural network); for one of the fields in the double Sérsic realisation, we also simulated images for the three near-infrared Y E , J E , and H E bands of the NISP-P instrument, and five Rubin/LSST optical complementary bands ( u , g, r, i, and z ), which together form a typical dataset for an Euclid observation. The images were simulated at the expected Euclid Wide Survey depths. To analyse the results, we created diagnostic plots and defined metrics to take into account the completeness of the provided catalogues, as well as the median biases, dispersions, and outlier fractions of their measured flux distributions. Five model-fitting software packages ( DeepLeGATo , Galapagos-2 , Morfometryka , ProFit , and SourceXtractor++ ) were compared, all typically providing good results. Of the differences among them, some were at least partly due to the distinct strategies adopted to perform the measurements. In the best-case scenario, the median bias of the measured fluxes in the analytical profile realisations is below 1% at a signal-to-noise ratio above 5 in I E , and above 10 in all the other bands; the dispersion of the distribution is typically comparable to the theoretically expected one, with a small fraction of catastrophic outliers. However, we can expect that real observations will prove to be more demanding, since the results were found to be less accurate for the most realistic realisation. We conclude that existing model-fitting software can provide accurate photometric measurements on Euclid datasets. The results of the challenge are fully available and reproducible through an online plotting tool.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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  • 2
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 658 ( 2022-02), p. A126-
    Abstract: We present a new infrared survey covering the three Euclid deep fields and four other Euclid calibration fields using Spitzer Space Telescope’s Infrared Array Camera (IRAC). We combined these new observations with all relevant IRAC archival data of these fields in order to produce the deepest possible mosaics of these regions. In total, these observations represent nearly 11 % of the total Spitzer Space Telescope mission time. The resulting mosaics cover a total of approximately 71.5 deg 2 in the 3.6 and 4.5 μm bands, and approximately 21.8 deg 2 in the 5.8 and 8 μm bands. They reach at least 24 AB magnitude (measured to 5 σ , in a 2″​​.5 aperture) in the 3.6 μm band and up to ∼5 mag deeper in the deepest regions. The astrometry is tied to the Gaia astrometric reference system, and the typical astrometric uncertainty for sources with 16  〈  [3.6] 〈 19 is ≲0″​​.15. The photometric calibration is in excellent agreement with previous WISE measurements. We extracted source number counts from the 3.6 μm band mosaics, and they are in excellent agreement with previous measurements. Given that the Spitzer Space Telescope has now been decommissioned, these mosaics are likely to be the definitive reduction of these IRAC data. This survey therefore represents an essential first step in assembling multi-wavelength data on the Euclid deep fields, which are set to become some of the premier fields for extragalactic astronomy in the 2020s.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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  • 3
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 671 ( 2023-03), p. A102-
    Abstract: The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15 000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morphologies from Euclid -detected galaxies and to help implement measurements in the pipeline of the Organisational Unit MER of the Euclid Science Ground Segment, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper focusses on the analysis of photometry, this paper assesses the accuracy of the parametric galaxy morphology measurements in imaging predicted from within the Euclid Wide Survey. We evaluate the performance of five state-of-the-art surface-brightness-fitting codes, DeepLeGATo , Galapagos-2 , Morfometryka , ProFit and SourceXtractor++ , on a sample of about 1.5 million simulated galaxies (350 000 above 5 σ ) resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic Sérsic profiles with one and two components, as well as more realistic galaxies generated with neural networks. We find that, despite some code-specific differences, all methods tend to achieve reliable structural measurements ( 〈 10% scatter on ideal Sérsic simulations) down to an apparent magnitude of about I E  = 23 in one component and I E  = 21 in two components, which correspond to a signal-to-noise ratio of approximately 1 and 5, respectively. We also show that when tested on non-analytic profiles, the results are typically degraded by a factor of 3, driven by systematics. We conclude that the official Euclid Data Releases will deliver robust structural parameters for at least 400 million galaxies in the Euclid Wide Survey by the end of the mission. We find that a key factor for explaining the different behaviour of the codes at the faint end is the set of adopted priors for the various structural parameters.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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  • 4
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 657 ( 2022-01), p. A90-
    Abstract: We present a machine learning framework to simulate realistic galaxies for the Euclid Survey, producing more complex and realistic galaxies than the analytical simulations currently used in Euclid . The proposed method combines a control on galaxy shape parameters offered by analytic models with realistic surface brightness distributions learned from real Hubble Space Telescope observations by deep generative models. We simulate a galaxy field of 0.4 deg 2 as it will be seen by the Euclid visible imager VIS, and we show that galaxy structural parameters are recovered to an accuracy similar to that for pure analytic Sérsic profiles. Based on these simulations, we estimate that the Euclid Wide Survey (EWS) will be able to resolve the internal morphological structure of galaxies down to a surface brightness of 22.5 mag arcsec −2 , and the Euclid Deep Survey (EDS) down to 24.9 mag arcsec −2 . This corresponds to approximately 250 million galaxies at the end of the mission and a 50% complete sample for stellar masses above 10 10.6   M ⊙ (resp. 10 9.6   M ⊙ ) at a redshift z  ∼ 0.5 for the EWS (resp. EDS). The approach presented in this work can contribute to improving the preparation of future high-precision cosmological imaging surveys by allowing simulations to incorporate more realistic galaxies.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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  • 5
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 665 ( 2022-09), p. A56-
    Abstract: We present a tomographic weak lensing analysis of the Kilo Degree Survey Data Release 4 (KiDS-1000), using a new pseudo angular power spectrum estimator (pseudo- C ℓ ) under development for the ESA Euclid mission. Over 21 million galaxies with shape information are divided into five tomographic redshift bins, ranging from 0.1 to 1.2 in photometric redshift. We measured pseudo- C ℓ using eight bands in the multipole range 76  〈   ℓ   〈  1500 for auto- and cross-power spectra between the tomographic bins. A series of tests were carried out to check for systematic contamination from a variety of observational sources including stellar number density, variations in survey depth, and point spread function properties. While some marginal correlations with these systematic tracers were observed, there is no evidence of bias in the cosmological inference. B -mode power spectra are consistent with zero signal, with no significant residual contamination from E / B -mode leakage. We performed a Bayesian analysis of the pseudo- C ℓ estimates by forward modelling the effects of the mask. Assuming a spatially flat ΛCDM cosmology, we constrained the structure growth parameter S 8  =  σ 8 (Ω m /0.3) 1/2  = 0.754 −0.029 +0.027 . When combining cosmic shear from KiDS-1000 with baryon acoustic oscillation and redshift space distortion data from recent Sloan Digital Sky Survey (SDSS) measurements of luminous red galaxies, as well as the Lyman- α forest and its cross-correlation with quasars, we tightened these constraints to S 8  = 0.771 −0.032 +0.006 . These results are in very good agreement with previous KiDS-1000 and SDSS analyses and confirm a ∼3 σ tension with early-Universe constraints from cosmic microwave background experiments.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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  • 6
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 670 ( 2023-02), p. A149-
    Abstract: Cosmological constraints from key probes of the Euclid imaging survey rely critically on the accurate determination of the true redshift distributions, n ( z ), of tomographic redshift bins. We determine whether the mean redshift, ⟨ z ⟩, of ten Euclid tomographic redshift bins can be calibrated to the Euclid target uncertainties of σ (⟨ z ⟩)  〈  0.002 (1 +  z ) via cross-correlation, with spectroscopic samples akin to those from the Baryon Oscillation Spectroscopic Survey (BOSS), Dark Energy Spectroscopic Instrument (DESI), and Euclid ’s NISP spectroscopic survey. We construct mock Euclid and spectroscopic galaxy samples from the Flagship simulation and measure small-scale clustering redshifts up to redshift z   〈  1.8 with an algorithm that performs well on current galaxy survey data. The clustering measurements are then fitted to two n ( z ) models: one is the true n ( z ) with a free mean; the other a Gaussian process modified to be restricted to non-negative values. We show that ⟨ z ⟩ is measured in each tomographic redshift bin to an accuracy of order 0.01 or better. By measuring the clustering redshifts on subsets of the full Flagship area, we construct scaling relations that allow us to extrapolate the method performance to larger sky areas than are currently available in the mock. For the full expected Euclid , BOSS, and DESI overlap region of approximately 6000 deg 2 , the uncertainties attainable by clustering redshifts exceeds the Euclid requirement by at least a factor of three for both n ( z ) models considered, although systematic biases limit the accuracy. Clustering redshifts are an extremely effective method for redshift calibration for Euclid if the sources of systematic biases can be determined and removed, or calibrated out with sufficiently realistic simulations. We outline possible future work, in particular an extension to higher redshifts with quasar reference samples.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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  • 7
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 671 ( 2023-3), p. A99-
    Abstract: The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across ~15 000deg 2 of the sky. Euclid is expected to detect ~12 billion astronomical sources, facilitating new insights into cosmology, galaxy evolution, and various other topics. In order to optimally exploit the expected very large dataset, appropriate methods and software tools need to be developed. Here we present a novel machine-learning-based methodology for the selection of quiescent galaxies using broadband Euclid I E , Y E , J E , and H E photometry, in combination with multi-wavelength photometry from other large surveys (e.g. the Rubin LSST). The ARIADNE pipeline uses meta-learning to fuse decision-tree ensembles, nearest-neighbours, and deep-learning methods into a single classifier that yields significantly higher accuracy than any of the individual learning methods separately. The pipeline has been designed to have 'sparsity awareness', such that missing photometry values are informative for the classification. In addition, our pipeline is able to derive photometric redshifts for galaxies selected as quiescent, aided by the 'pseudo-labelling' semi-supervised method, and using an outlier detection algorithm to identify and reject likely catastrophic outliers. After the application of the outlier filter, our pipeline achieves a normalised mean absolute deviation of ≲0.03 and a fraction of catastrophic outliers of ≲0.02 when measured against the COSMOS2015 photometric redshifts. We apply our classification pipeline to mock galaxy photometry catalogues corresponding to three main scenarios: (i) Euclid Deep Survey photometry with ancillary ugriz, WISE, and radio data; (ii) Euclid Wide Survey photometry with ancillary ugriz, WISE, and radio data; and (iii) Euclid Wide Survey photometry only, with no foreknowledge of galaxy redshifts. In a like-for-like comparison, our classification pipeline outperforms UVJ selection, in addition to the Euclid I E – Y E , J E – H E and u – I E , I E – J E colour-colour methods, with improvements in completeness and the F 1-score (the harmonic mean of precision and recall) of up to a factor of 2.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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  • 8
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2017
    In:  Monthly Notices of the Royal Astronomical Society Vol. 466, No. 2 ( 2017-04-11), p. 1444-1461
    In: Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP), Vol. 466, No. 2 ( 2017-04-11), p. 1444-1461
    Type of Medium: Online Resource
    ISSN: 0035-8711 , 1365-2966
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2017
    detail.hit.zdb_id: 2016084-7
    SSG: 16,12
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  • 9
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 671 ( 2023-3), p. A153-
    Abstract: Current and future imaging surveys require photometric redshifts (photo- z s) to be estimated for millions of galaxies. Improving the photo- z quality is a major challenge but is needed to advance our understanding of cosmology. In this paper we explore how the synergies between narrow-band photometric data and large imaging surveys can be exploited to improve broadband photometric redshifts. We used a multi-task learning (MTL) network to improve broadband photo- z estimates by simultaneously predicting the broadband photo- z and the narrow-band photometry from the broadband photometry. The narrow-band photometry is only required in the training field, which also enables better photo- z predictions for the galaxies without narrow-band photometry in the wide field. This technique was tested with data from the Physics of the Accelerating Universe Survey (PAUS) in the COSMOS field. We find that the method predicts photo- z s that are 13% more precise down to magnitude i AB 〈 23; the outlier rate is also 40% lower when compared to the baseline network. Furthermore, MTL reduces the photo- z bias for high-redshift galaxies, improving the redshift distributions for tomographic bins with z 〉 1. Applying this technique to deeper samples is crucial for future surveys such as Euclid or LSST. For simulated data, training on a sample with i AB 〈 23, the method reduces the photo- z scatter by 16% for all galaxies with i AB 〈 25. We also studied the effects of extending the training sample with photometric galaxies using PAUS high-precision photo- z s, which reduces the photo- z scatter by 20% in the COSMOS field.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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  • 10
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 675 ( 2023-07), p. A120-
    Abstract: Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of Euclid -like mocks, derived from N -body simulations. In this first paper of the HOWLS series, we computed the nontomographic (Ω m , σ 8 ) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a 4.5 times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with Euclid . The data used in this analysis are publicly released with the paper.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
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