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  • 1
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 676 ( 2023-8), p. A34-
    Abstract: This work focusses on the pilot run of a simulation campaign aimed at investigating the spectroscopic capabilities of the Euclid Near-Infrared Spectrometer and Photometer (NISP), in terms of continuum and emission line detection in the context of galaxy evolutionary studies. To this purpose, we constructed, emulated, and analysed the spectra of 4992 star-forming galaxies at 0.3 ≤ z ≤ 2.5 using the NISP pixel-level simulator. We built the spectral library starting from public multi-wavelength galaxy catalogues, with value-added information on spectral energy distribution (SED) fitting results, and stellar population templates from Bruzual & Charlot (2003, MNRAS, 344, 1000). Rest-frame optical and near-IR nebular emission lines were included using empirical and theoretical relations. Dust attenuation was treated using the Calzetti extinction law accounting for the differential attenuation in line-emitting regions with respect to the stellar continuum. The NISP simulator was configured including instrumental and astrophysical sources of noise such as the dark current, read-out noise, zodiacal background, and out-of-field stray light. In this preliminary study, we avoided contamination due to the overlap of the slitless spectra. For this purpose, we located the galaxies on a grid and simulated only the first order spectra. We inferred the 3.5 σ NISP red grism spectroscopic detection limit of the continuum measured in the H band for star-forming galaxies with a median disk half-light radius of 0.″4 at magnitude H = 19.5 ± 0.2 AB mag for the Euclid Wide Survey and at H = 20.8 ± 0.6 AB mag for the Euclid Deep Survey. We found a very good agreement with the red grism emission line detection limit requirement for the Wide and Deep surveys. We characterised the effect of the galaxy shape on the detection capability of the red grism and highlighted the degradation of the quality of the extracted spectra as the disk size increased. In particular, we found that the extracted emission line signal-to-noise ratio (S/N) drops by ~45% when the disk size ranges from 0.″25 to 1″. These trends lead to a correlation between the emission line S/N and the stellar mass of the galaxy and we demonstrate the effect in a stacking analysis unveiling emission lines otherwise too faint to detect.
    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. 662 ( 2022-06), p. A93-
    Abstract: Aims. We investigate the importance of lensing magnification for estimates of galaxy clustering and its cross-correlation with shear for the photometric sample of Euclid . Using updated specifications, we study the impact of lensing magnification on the constraints and the shift in the estimation of the best fitting cosmological parameters that we expect if this effect is neglected. Methods. We follow the prescriptions of the official Euclid Fisher matrix forecast for the photometric galaxy clustering analysis and the combination of photometric clustering and cosmic shear. The slope of the luminosity function (local count slope), which regulates the amplitude of the lensing magnification, and the galaxy bias have been estimated from the Euclid Flagship simulation. Results. We find that magnification significantly affects both the best-fit estimation of cosmological parameters and the constraints in the galaxy clustering analysis of the photometric sample. In particular, including magnification in the analysis reduces the 1 σ errors on Ω m, 0 ,  w 0 ,  w a at the level of 20–35%, depending on how well we will be able to independently measure the local count slope. In addition, we find that neglecting magnification in the clustering analysis leads to shifts of up to 1.6 σ in the best-fit parameters. In the joint analysis of galaxy clustering, cosmic shear, and galaxy–galaxy lensing, magnification does not improve precision, but it leads to an up to 6 σ bias if neglected. Therefore, for all models considered in this work, magnification has to be included in the analysis of galaxy clustering and its cross-correlation with the shear signal (3 × 2pt analysis) for an accurate parameter estimation.
    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. 662 ( 2022-06), p. A112-
    Abstract: Euclid is a mission of the European Space Agency that is designed to constrain the properties of dark energy and gravity via weak gravitational lensing and galaxy clustering. It will carry out a wide area imaging and spectroscopy survey (the Euclid Wide Survey: EWS) in visible and near-infrared bands, covering approximately 15 000 deg 2 of extragalactic sky in six years. The wide-field telescope and instruments are optimised for pristine point spread function and reduced stray light, producing very crisp images. This paper presents the building of the Euclid reference survey: the sequence of pointings of EWS, deep fields, and calibration fields, as well as spacecraft movements followed by Euclid as it operates in a step-and-stare mode from its orbit around the Lagrange point L2. Each EWS pointing has four dithered frames; we simulated the dither pattern at the pixel level to analyse the effective coverage. We used up-to-date models for the sky background to define the Euclid region-of-interest (RoI). The building of the reference survey is highly constrained from calibration cadences, spacecraft constraints, and background levels; synergies with ground-based coverage were also considered. Via purposely built software, we first generated a schedule for the calibrations and deep fields observations. On a second stage, the RoI was tiled and scheduled with EWS observations, using an algorithm optimised to prioritise the best sky areas, produce a compact coverage, and ensure thermal stability. The result is the optimised reference survey RSD_2021A, which fulfils all constraints and is a good proxy for the final solution. The current EWS covers ≈14 500 deg 2 . The limiting AB magnitudes (5 σ point-like source) achieved in its footprint are estimated to be 26.2 (visible band I E ) and 24.5 (for near infrared bands Y E , J E , H E ); for spectroscopy, the H α line flux limit is 2 × 10 −16 erg −1 cm −2 s −1 at 1600 nm; and for diffuse emission, the surface brightness limits are 29.8 (visible band) and 28.4 (near infrared bands) mag arcsec −2 .
    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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  • 4
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 662 ( 2022-6), p. A92-
    Abstract: Euclid will be the first space mission to survey most of the extragalactic sky in the 0.95–2.02 µm range, to a 5 σ point-source median depth of 24.4 AB mag. This unique photometric dataset will find wide use beyond Euclid’s core science. In this paper, we present accurate computations of the Euclid Y E , J E , and H E passbands used by the Near-Infrared Spectrometer and Photometer (NISP), and the associated photometric system. We pay particular attention to passband variations in the field of view, accounting for, among other factors, spatially variable filter transmission and variations in the angle of incidence on the filter substrate using optical ray tracing. The response curves’ cut-on and cut-off wavelengths – and their variation in the field of view – are determined with ~0.8 nm accuracy, essential for the photometric redshift accuracy required by Euclid. After computing the photometric zero points in the AB mag system, we present linear transformations from and to common ground-based near-infrared photometric systems, for normal stars, red and brown dwarfs, and galaxies separately. A Python tool to compute accurate magnitudes for arbitrary passbands and spectral energy distributions is provided. We discuss various factors, from space weathering to material outgassing, that may slowly alter Euclid ’s spectral response. At the absolute flux scale, the Euclid in-flight calibration program connects the NISP photometric system to Hubble Space Telescope spectrophotometric white dwarf standards; at the relative flux scale, the chromatic evolution of the response is tracked at the milli-mag level. In this way, we establish an accurate photometric system that is fully controlled throughout Euclid’s lifetime.
    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. 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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  • 6
    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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  • 7
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 668 ( 2022-12), p. C3-
    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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  • 8
    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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  • 9
    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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  • 10
    In: Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP), Vol. 520, No. 3 ( 2023-02-15), p. 3529-3548
    Abstract: Next-generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine-learning methods are increasingly becoming the most efficient tools to handle this enormous amount of data, because they are often faster and more accurate than traditional methods. We investigate how well redshifts, stellar masses, and star-formation rates (SFRs) can be measured with deep-learning algorithms for observed galaxies within data mimicking the Euclid and Rubin/LSST surveys. We find that deep-learning neural networks and convolutional neural networks (CNNs), which are dependent on the parameter space of the training sample, perform well in measuring the properties of these galaxies and have a better accuracy than methods based on spectral energy distribution fitting. CNNs allow the processing of multiband magnitudes together with $H_{\scriptscriptstyle \rm E}$-band images. We find that the estimates of stellar masses improve with the use of an image, but those of redshift and SFR do not. Our best results are deriving (i) the redshift within a normalized error of & lt;0.15 for 99.9 ${{\ \rm per\ cent}}$ of the galaxies with signal-to-noise ratio & gt;3 in the $H_{\scriptscriptstyle \rm E}$ band; (ii) the stellar mass within a factor of two ($\sim\!0.3 \rm \ dex$) for 99.5 ${{\ \rm per\ cent}}$ of the considered galaxies; and (iii) the SFR within a factor of two ($\sim\!0.3 \rm \ dex$) for $\sim\!70{{\ \rm per\ cent}}$ of the sample. We discuss the implications of our work for application to surveys as well as how measurements of these galaxy parameters can be improved with deep learning.
    Type of Medium: Online Resource
    ISSN: 0035-8711 , 1365-2966
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 2016084-7
    SSG: 16,12
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