ORCID Profile
0000-0002-4478-1270
Current Organisation
The University of Edinburgh
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Publisher: EDP Sciences
Date: 03-2021
DOI: 10.1051/0004-6361/202040237
Abstract: The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on an accurate knowledge of the galaxy mean redshift ⟨ z ⟩. We investigate the possibility of measuring ⟨ z ⟩ with an accuracy better than 0.002 (1 + z ) in ten tomographic bins spanning the redshift interval 0.2 z 2.2, the requirements for the cosmic shear analysis of Euclid . We implement a sufficiently realistic simulation in order to understand the advantages and complementarity, as well as the shortcomings, of two standard approaches: the direct calibration of ⟨ z ⟩ with a dedicated spectroscopic s le and the combination of the photometric redshift probability distribution functions ( z PDFs) of in idual galaxies. We base our study on the Horizon-AGN hydrodynamical simulation, which we analyse with a standard galaxy spectral energy distribution template-fitting code. Such a procedure produces photometric redshifts with realistic biases, precisions, and failure rates. We find that the current Euclid design for direct calibration is sufficiently robust to reach the requirement on the mean redshift, provided that the purity level of the spectroscopic s le is maintained at an extremely high level of 99.8%. The z PDF approach can also be successful if the z PDF is de-biased using a spectroscopic training s le. This approach requires deep imaging data but is weakly sensitive to spectroscopic redshift failures in the training s le. We improve the de-biasing method and confirm our finding by applying it to real-world weak-lensing datasets (COSMOS and KiDS+VIKING-450).
Publisher: EDP Sciences
Date: 03-2023
DOI: 10.1051/0004-6361/202245042
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 s le 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.
Publisher: EDP Sciences
Date: 25-10-2019
DOI: 10.1051/0004-6361/201936427
Abstract: We provide predictions of the yield of 7 z 9 quasars from the Euclid wide survey, updating the calculation presented in the Euclid Red Book in several ways. We account for revisions to the Euclid near-infrared filter wavelengths we adopt steeper rates of decline of the quasar luminosity function (QLF Φ) with redshift, Φ ∝ 10 k ( z − 6) , k = −0.72, and a further steeper rate of decline, k = −0.92 we use better models of the contaminating populations (MLT dwarfs and compact early-type galaxies) and we make use of an improved Bayesian selection method, compared to the colour cuts used for the Red Book calculation, allowing the identification of fainter quasars, down to J AB ∼ 23. Quasars at z 8 may be selected from Euclid O Y J H photometry alone, but selection over the redshift interval 7 z 8 is greatly improved by the addition of z -band data from, e.g., Pan-STARRS and LSST. We calculate predicted quasar yields for the assumed values of the rate of decline of the QLF beyond z = 6. If the decline of the QLF accelerates beyond z = 6, with k = −0.92, Euclid should nevertheless find over 100 quasars with 7.0 z 7.5, and ∼25 quasars beyond the current record of z = 7.5, including ∼8 beyond z = 8.0. The first Euclid quasars at z 7.5 should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, 7 z 8, M 1450 −25, using 8 m class telescopes to confirm candidates, but follow-up with JWST or E-ELT will be required to measure the faint-end slope. Contamination of the candidate lists is predicted to be modest even at J AB ∼ 23. The precision with which k can be determined over 7 z 8 depends on the value of k , but assuming k = −0.72 it can be measured to a 1 σ uncertainty of 0.07.
Publisher: EDP Sciences
Date: 03-2023
DOI: 10.1051/0004-6361/202245041
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.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Bryan Gillis.