GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Andreon, S.  (4)
  • 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
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    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
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 664 ( 2022-08), p. A196-
    Abstract: The Complete Calibration of the Color–Redshift Relation survey (C3R2) is a spectroscopic program designed to empirically calibrate the galaxy color–redshift relation to the Euclid depth ( I E = 24.5), a key ingredient for the success of Stage IV dark energy projects based on weak lensing cosmology. A spectroscopic calibration sample that is as representative as possible of the galaxies in the Euclid weak lensing sample is being collected, selecting galaxies from a self-organizing map (SOM) representation of the galaxy color space. Here, we present the results of a near-infrared H - and K -band spectroscopic campaign carried out using the LUCI instruments at the LBT. For a total of 251 galaxies, we present new highly reliable redshifts in the 1.3 ≤  z  ≤ 1.7 and 2 ≤  z  ≤ 2.7 ranges. The newly-determined redshifts populate 49 SOM cells that previously contained no spectroscopic measurements and almost twice the occupation numbers of an additional 153 SOM cells. A final optical ground-based observational effort is needed to calibrate the missing cells, in particular in the redshift range 1.7 ≤  z  ≤ 2.7, which lack spectroscopic calibration. In the end, Euclid itself will deliver telluric-free near-IR spectra that can complete the calibration.
    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
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    In: Astronomy & Astrophysics, EDP Sciences, Vol. 644 ( 2020-12), p. A31-
    Abstract: Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo- z ) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo- z s at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2 − 2.6 redshift range that the Euclid mission will probe. We designed a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data was divided into two samples: one calibration sample for which photometry and redshifts were provided to the participants; and the validation sample, containing only the photometry to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates the sources they consider unfit for use in cosmological analyses. The performance of each method was assessed through a set of informative metrics, using cross-matched spectroscopic and highly-accurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, that is to say sources for which the photo- z deviates by more than 0.15(1 +  z ) from the spectroscopic-redshift (spec- z ). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. We find that no machine-learning method provides good results in the regions of galaxy color-space that are sparsely populated by spectroscopic-redshifts, for example z   〉  1. However they generally perform better than template-fitting methods at low redshift ( z   〈  0.7), indicating that template-fitting methods do not use all of the information contained in the photometry. We introduce metrics that quantify both photo- z precision and completeness of the samples (post-rejection), since both contribute to the final figure of merit of the science goals of the survey (e.g., cosmic shear from Euclid ). Template-fitting methods provide the best results in these metrics, but we show that a combination of template-fitting results and machine-learning results with rejection criteria can outperform any individual method. On this basis, we argue that further work in identifying how to best select between machine-learning and template-fitting approaches for each individual galaxy should be pursued as a priority.
    Type of Medium: Online Resource
    ISSN: 0004-6361 , 1432-0746
    RVK:
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2020
    detail.hit.zdb_id: 1458466-9
    SSG: 16,12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...