I. A. Zinchenko’s research while affiliated with Ludwig-Maximilians-Universität in Munich and other places

In this paper, we present a semi-empirical calibration between the oxygen abundance and the N 2 emission-line ratio for low ionisation nuclear emission regions (LINERs). This relation was derived by comparing the optical spectroscopic data of 118 nuclear spaxels classified as LINERs using three different BPT diagrams from the Mapping Nearby Galaxies survey (MaNGA) and sub-classified as weak (wAGN, 84 objects) and strong (sAGN, 34 objects) active galactic nucleus (AGN) from the WHAN diagnostic diagram and photoionisation model results obtained with the cloudy code assuming gas accretion into a black hole (representing an AGN). We found that our wAGN LINERs exhibit an oxygen abundance in the range of $8.50 \lesssim \mathrm{12+\log(O/H)} \lesssim 8.90$ , with an average value of $\mathrm{12+\log(O/H)}=8.68$ , while our sAGN LINERs exhibit an oxygen abundance in the range of $8.51 \lesssim \: \mathrm{12+\log(O/H)} \: \lesssim \: 8.81$ , with an average value of $\mathrm{12+\log(O/H)}=8.65$ . Our abundance estimations are in good agreement with those derived for another two different samples one of them with 463 Seyfert 2 objects and the other with 43 LINERs galaxies ionised by post-AGB stars, showing that the assumptions of our models are likely suitable for wAGN and sAGN LINERs. A relation between the equivalent width of the observed H $\alpha$ emission-line and the estimated ionisation parameter provided by models was obtained. Our results also suggest that LINERs does not show a clear correlation between oxygen abundances and the stellar mass of the hosting galaxies.

The chemical enrichment in low-ionization nuclear emission-line regions (LINERs) is still an issue with spatial resolution spectroscopic data because we lack studies and because the nature of their ionizing source is uncertain, although they are the most abundant type of active galaxies in the nearby Universe. Considering different scenarios for the ionizing source (hot old stellar populations, active galactic nuclei, or inefficient accretion disks), we analyze the implications of these assumptions to constrain the chemical content of the gas-phase interstellar medium. We used a sample of 105 galaxies from the survey called Mapping Nearby Galaxies at Apache Point Observatory (MaNGA), whose nuclear central spaxels show LINER-like emission. For each scenario we considered, we built a grid of photoionization models (4928 models for each considered ionizing source) that were later used in the open-source code HII-CHI-Mistry . This allowed us to estimate chemical abundance ratios such as 12+log(O/H) or log(N/O) and to constrain the ionization parameters that characterize the ionized interstellar medium in these galaxies. The oxygen abundances in the nuclear region of LINER-like galaxies are spread over a wide range 8.08 $<$ 12+log(O/H) $<$ 8.89, with a median solar value (in agreement with previous studies) when models for active galactic nuclei are considered. Nevertheless, the nitrogen-to-oxygen ratio we derived is much less affected by the assumptions on the ionizing source and indicates suprasolar values (log(N/O) = -0.69). By comparing the different scenarios, we show that if hot old stellar populations caused the ionization of the interstellar medium, a complex picture (e.g., outflows and/or inflows that scale with the galaxy chemical abundance) would be needed to explain the chemical enrichment history, whereas the assumption of active galactic nucleus activity is compatible with the standard scenario that is found in most galaxies.

Extragalactic globular clusters (EGCs) are an abundant and powerful tracer of galaxy dynamics and formation, and their own formation and evolution is also a matter of extensive debate. The compact nature of globular clusters means that they are hard to spatially resolve and thus study outside the Local Group. In this work we have examined how well EGCs will be detectable in images from the telescope, using both simulated pre-launch images and the first early-release observations of the Fornax galaxy cluster. The Euclid Wide Survey will provide high-spatial resolution VIS imaging in the broad band as well as near-infrared photometry ( and We estimate that the 24 719 known galaxies within 100 Mpc in the footprint of the survey host around 830 000 EGCs of which about 350 000 are within the survey's detection limits. For about half of these EGCs, three infrared colours will be available as well. For any galaxy within 50 Mpc the brighter half of its GC luminosity function will be detectable by the Euclid Wide Survey. The detectability of EGCs is mainly driven by the residual surface brightness of their host galaxy. We find that an automated machine-learning EGC-classification method based on real data of the Fornax galaxy cluster provides an efficient method to generate high purity and high completeness GC candidate catalogues. We confirm that EGCs are spatially resolved compared to pure point sources in VIS images of Fornax. Our analysis of both simulated and first on-sky data show that Euclid will increase the number of GCs accessible with high-resolution imaging substantially compared to previous surveys, and will permit the study of GCs in the outskirts of their hosts. is unique in enabling systematic studies of EGCs in a spatially unbiased and homogeneous manner and is primed to improve our understanding of many understudied aspects of GC astrophysics.

The chemical enrichment in low-ionization nuclear emission-line regions (LINERs) is still an issue with spatial resolution spectroscopic data due to the lack of studies and the uncertainties in the nature of their ionizing source, despite being the most abundant type of active galaxies in the nearby Universe. Considering different scenarios for the ionizing source (hot old stellar populations, active galactic nuclei (AGN) or inefficient accretion disks), we analyze the implications of these assumptions to constrain the chemical content of the gas-phase interstellar medium (ISM). We used a sample of 105 galaxies from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, whose nuclear central spaxels show LINER-like emission. For each scenario considered, we built a grid of photoionization models (4928 models for each considered ionizing source) which are later used in the open-source code HII-CHI-Mistry, allowing us to estimate chemical abundance ratios such as 12+log(O/H) or log(N/O) and constrain the ionization parameter that characterize the ionized ISM in those galaxies. We obtain that oxygen abundances in the nuclear region of LINER-like galaxies spread over a wide range 8.08 < 12+log(O/H) < 8.89, with a median solar value (in agreement with previous studies) if AGN models are considered. Nevertheless, the derived nitrogen-to-oxygen ratio is much less affected by the assumptions on the ionizing source, and point towards suprasolar values (log(N/O) = -0.69). By comparing the different analyzed scenarios, we show that if hot old stellar populations were responsible of the ionization of the ISM a complex picture (such as outflows and/or inflows scaling with galaxy chemical abundance) would be needed to explain the chemical enrichment history, whereas the assumption of AGN activity is compatible with the standard scenario found in most galaxies.

We forecast the expected population of active galactic nuclei (AGN) observable in the Euclid Wide Survey (EWS) and Euclid Deep Survey (EDS). Starting from an X-ray luminosity function (XLF), we generated volume-limited samples of the AGN expected in the survey footprints. Each AGN was assigned a spectral energy distribution (SED) appropriate for its X-ray luminosity and redshift, with perturbations sampled from empirical distributions. The photometric detectability of each AGN was assessed via mock observations of the assigned SED. We estimate 40 million AGN will be detectable in at least one band in the EWS and 0.24 million in the EDS, corresponding to surface densities of and . The relative uncertainty on our expectation for detectable AGN is 6.7 for the EWS and 12.5 for the EDS, driven by the uncertainty of the XLF. Employing colour selection criteria on our simulated data we select a sample of $) AGN in the EWS and$) in the EDS, amounting to 10 and 8 of the AGN detectable in the EWS and EDS. Including ancillary Rubin/LSST bands improves the completeness and purity of AGN selection. These data roughly double the total number of selected AGN to comprise 21 and 15 of the detectable AGN in the EWS and EDS. The total expected sample of colour-selected AGN contains 6.0\,times \,106 (74 ) unobscured AGN and 2.1\,times \,106 (26 ) obscured AGN, covering $0.02 z 5.2$ and $43 (L_ bol erg s 47$. With these simple colour cuts expected surface densities are already comparable to the yield of modern X-ray and mid-infrared surveys of similar area. The EWS sample is most comparable to the WISE C75 AGN selection and the EDS sample is most similar to the yield of the collated Spitzer cryogenic surveys when considering bands alone, or the XXL-3XLSS survey AGN sample when also considering selection with ancillary optical bands We project that 15 (7.6 ) of the total detectable population in the EWS (EDS) will exhibit X-ray fluxes that could be detected in the XMM-COSMOS survey, showing that the vast majority of AGN would not be detectable in modern medium-depth X-ray surveys.

This paper presents the specification, design, and development of the Visible Camera (VIS) on the European Space Agency's mission. VIS is a large optical-band imager with a field of view of 0.54 deg$^2$ sampled at with an array of 609 Megapixels and a spatial resolution of . It will be used to survey approximately 14 000 deg$^2$ of extragalactic sky to measure the distortion of galaxies in the redshift range z=0.1--1.5 resulting from weak gravitational lensing, one of the two principal cosmology probes leveraged by With photometric redshifts, the distribution of dark matter can be mapped in three dimensions, and the extent to which this has changed with look-back time can be used to constrain the nature of dark energy and theories of gravity. The entire VIS focal plane will be transmitted to provide the largest images of the Universe from space to date, specified to reach AB with a signal-to-noise ratio S/N in a single broad E (r+i+z)$band over a six-year survey. The particularly challenging aspects of the instrument are the control and calibration of observational biases, which lead to stringent performance requirements and calibration regimes. With its combination of spatial resolution, calibration knowledge, depth, and area covering most of the extra-Galactic sky, VIS will also provide a legacy data set for many other fields. This paper discusses the rationale behind the conception of VIS and describes the instrument design and development, before reporting the prelaunch performance derived from ground calibrations and brief results from the in-orbit commissioning. VIS should reach fainter than AB =25$ with $S/N 10$ for galaxies with a full width at half maximum of in a diameter aperture over the Wide Survey, and $m_ AB for a Deep Survey that will cover more than 50 deg$^2$. The paper also describes how the instrument works with the telescope and survey, and with the science data processing, to extract the cosmological information.

will collect an enormous amount of data during the mission's lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting methods, numerous machine learning (ML) algorithms have been presented for computing their photometric redshifts and physical parameters (PPs), requiring significantly less computing effort while producing equivalent performance measures. However, their performance is limited by the quality and amount of input information entering the model (the features), to a level where the recovery of some well-established physical relationships between parameters might not be guaranteed -- for example, the star-forming main sequence (SFMS). To forecast the reliability of photo-zs and PPs calculations, we produced two mock catalogs simulating the photometry with the UNIONS ugriz and filters. We simulated the Euclid Wide Survey (EWS) and Euclid Deep Fields (EDF), alongside two auxiliary fields. We tested the performance of a template-fitting algorithm ( and four ML methods in recovering photo-zs, PPs (stellar masses and star formation rates), and the SFMS on the simulated fields. To mimic the processing as closely as possible, the models were trained with labels and tested on the simulated ground truth. For the EWS, we found that the best results are achieved with a mixed labels approach, training the models with wide survey features and labels from the results on deeper photometry, that is, with the best possible set of labels for a given photometry. This imposes a prior to the input features, helping the models to better discern cases in degenerate regions of feature space, that is, when galaxies have similar magnitudes and colors but different redshifts and PPs, with performance metrics even better than those found with We found no more than 3 performance degradation using a COSMOS-like reference sample or removing u band data, which will not be available until after data release DR1. The best results are obtained for the EDF, with appropriate recovery of photo-z, PPs, and the SFMS.

The Euclid mission is expected to image millions of galaxies at high resolution, providing an extensive dataset with which to study galaxy evolution. Because galaxy morphology is both a fundamental parameter and one that is hard to determine for large samples, we investigate the application of deep learning in predicting the detailed morphologies of galaxies in Euclid using Zoobot, a convolutional neural network pretrained with 450 000 galaxies from the Galaxy Zoo project. We adapted Zoobot for use with emulated Euclid images generated based on Hubble Space Telescope COSMOS images and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We experimented with different numbers of galaxies and various magnitude cuts during the training process. We demonstrate that the trained Zoobot model successfully measures detailed galaxy morphology in emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features, such as spiral arms, clumps, bars, discs, and central bulges. When compared to volunteer classifications, Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy of above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes, such as disc or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. On the other hand, for more detailed structures and complex tasks, such as detecting and counting spiral arms or clumps, the deviations are slightly higher, of namely around 12% with 60 000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowd sourcing. We estimate that, with our model, the detailed morphology of approximately 800 million galaxies of the Euclid Wide Survey could be reliably measured and that approximately 230 million of these galaxies would display features. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images.

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. is a medium-class mission in the Cosmic Vision 2015--2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14\,000\,deg$^2$ of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.

Euclid will cover over 14000 $deg^{2}$ with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution and AGN. In this work we identify the best colour selection criteria for AGN, based only on Euclid photometry or including ancillary photometric observations, such as the data that will be available with the Rubin legacy survey of space and time (LSST) and observations already available from Spitzer/IRAC. The analysis is performed for unobscured AGN, obscured AGN, and composite (AGN and star-forming) objects. We make use of the spectro-photometric realisations of infrared-selected targets at all-z (SPRITZ) to create mock catalogues mimicking both the Euclid Wide Survey (EWS) and the Euclid Deep Survey (EDS). Using these catalogues we estimate the best colour selection, maximising the harmonic mean (F1) of completeness and purity. The selection of unobscured AGN in both Euclid surveys is possible with Euclid photometry alone with F1=0.22-0.23, which can increase to F1=0.43-0.38 if we limit at z>0.7. Such selection is improved once the Rubin/LSST filters (a combination of the u, g, r, or z filters) are considered, reaching F1=0.84 and 0.86 for the EDS and EWS, respectively. The combination of a Euclid colour with the [3.6]-[4.5] colour, which is possible only in the EDS, results in an F1-score of 0.59, improving the results using only Euclid filters, but worse than the selection combining Euclid and LSST. The selection of composite ($f_{{\rm AGN}}$=0.05-0.65 at 8-40 $\mu m$) and obscured AGN is challenging, with F1<0.3 even when including ancillary data. This is driven by the similarities between the broad-band spectral energy distribution of these AGN and star-forming galaxies in the wavelength range 0.3-5 $\mu m$.