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C. Dolding

Publications and source records attributed to C. Dolding.

At least 55 records · Page 3Linked to original sources

Euclid Quick Data Release (Q1). First Euclid statistical study of the active galactic nuclei contribution fraction

Active galactic nuclei (AGN) play a key role in galaxy evolution but are challenging to identify due to their varied observational signatures. Furthermore, understanding their impact requires quantifying their strength relative to their host galaxies. We developed a deep learning (DL) model for identifying AGN in imaging data by deriving the contribution of the central point source. Trained on Euclidised mock galaxy images with injected AGN levels, in the form of varying contributions of the point-spread function (PSF), our model can precisely and accurately recover the injected AGN contribution fraction $f_{\rm PSF}$, with a mean difference between the predicted and true $f_{\rm PSF}$ of $-0.0078$ and an overall root mean square error (RMSE) of 0.051. This method moves beyond binary AGN classification, enabling precise AGN contribution measurements. Applying our model to a stellar-mass-limited sample ($M_{\ast} \ge 10^{9.8} M_{\odot}$, $0.5 \le z \le 2.0$) from the first \Euclid quick data release (Q1), we identify $48,840 \pm 78$ AGN over 63.1 deg$^2$ ($7.8\pm0.1$%) using a threshold of $f_{\rm PSF} > 0.2$. We compare our DL-selected AGN with those identified in X-ray, mid-infrared (MIR), and optical spectroscopy and investigate their overlapping fractions depending on different thresholds on the PSF contribution. We find that the overlap increases with increasing X-ray or bolometric AGN luminosity. The AGN luminosity in the $I_{\rm E}$ filter correlates with host galaxy stellar mass, suggesting faster supermassive black hole (SMBH) growth in more massive galaxies. Moreover, the mean relative contribution of the AGN is higher in quiescent galaxies than in star-forming ones. Starburst galaxies and the most massive galaxies (across the star-formation main sequence) tend to host the most luminous AGN, indicating concomitant assembly of the SMBH and the host galaxy.

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Euclid Quick Data Release (Q1) First study of red quasars selection

Red quasars constitute an important but elusive phase in the evolution of supermassive black holes, where dust obscuration can significantly alter their observed properties. They have broad emission lines, like other quasars, but their optical continuum emission is significantly reddened, which is why they were traditionally identified based on near- and mid-infrared selection criteria. This work showcases the capability of the \Euclid space telescope to find a large sample of red quasars, using \Euclid near infrared (NIR) photometry. We first conduct a forecast analysis, comparing a synthetic catalogue of red QSOs with COSMOS2020. Using template fitting, we reconstruct \Euclid-like photometry for the COSMOS sources and identify a sample of candidates in a multidimensional colour-colour space achieving $98\%$ completeness for mock red QSOs with $30\%$ contaminants. To refine our selection function, we implement a probabilistic Random Forest classifier, and use UMAP visualisation to disentangle non-linear features in colour-space, reaching $98\%$ completeness and $88\%$ purity. A preliminary analysis of the candidates in the \Euclid Deep Field Fornax (EDF-F) shows that, compared to VISTA+DECAm-based colour selection criteria, \Euclid's superior depth, resolution and optical-to-NIR coverage improves the identification of the reddest, most obscured sources. Notably, the \Euclid exquisite resolution in the $I_E$ filter unveils the presence of a candidate dual quasar system, highlighting the potential for this mission to contribute to future studies on the population of dual AGN. The resulting catalogue of candidates, including more the 150 000 sources, provides a first census of red quasars in \Euclid Q1 and sets the groundwork for future studies in the Euclid Wide Survey (EWS), including spectral follow-up analyses and host morphology characterisation.

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Euclid Quick Data Release (Q1). The active galaxies of Euclid

We present a catalogue of candidate active galactic nuclei (AGN) in the $Euclid$ Quick Release (Q1) fields. For each $Euclid$ source we collect multi-wavelength photometry and spectroscopy information from Galaxy Evolution Explorer (GALEX), $Gaia$, Dark Energy Survey (DES), Wise-field Infrared Survey Explorer (WISE), $Spitzer$, Dark Energy Survey (DESI), and Sloan Digital Sky Survey (SDSS), including spectroscopic redshift from public compilations. We investigate the AGN contents of the Q1 fields by applying selection criteria using $Euclid$ colours and WISE-AllWISE cuts finding respectively 292,222 and 65,131 candidates. We also create a high-purity QSO catalogue based on $Gaia$ DR3 information containing 1971 candidates. Furthermore, we utilise the collected spectroscopic information from DESI to perform broad-line and narrow-line AGN selections, leading to a total of 4392 AGN candidates in the Q1 field. We investigate and refine the Q1 probabilistic random forest QSO population, selecting a total of 180,666 candidates. Additionally, we perform SED fitting on a subset of sources with available $z_{\text{spec}}$, and by utilizing the derived AGN fraction, we identify a total of 7766 AGN candidates. We discuss purity and completeness of the selections and define two new colour selection criteria ($JH$_$I_{\text{E}}Y$ and $I_{\text{E}}H$_$gz$) to improve on purity, finding 313,714 and 267,513 candidates respectively in the Q1 data. We find a total of 229,779 AGN candidates equivalent to an AGN surface density of 3641 deg$^{-2}$ for $18<I_{\text{E}}\leq 24.5$, and a subsample of 30,422 candidates corresponding to an AGN surface density of 482 deg$^{-2}$ when limiting the depth to $18<I_{\text{E}}\leq 22$. The surface density of AGN recovered from this work is in line with predictions based on the AGN X-ray luminosity functions.

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Euclid Quick Data Release (Q1). An investigation of optically faint, red objects in the Euclid Deep Fields

Our understanding of cosmic star-formation at $z>3$ used to largely rely on rest-frame UV observations. However, these observations overlook dusty and massive sources, resulting in an incomplete census of early star-forming galaxies. Recently, infrared data from Spitzer and the James Webb Space Telescope (JWST) have revealed a hidden population at $z\sim$3-6 with extreme red colours. Taking advantage of the overlap between imaging in the Euclid Deep Fields (EDFs), covering $\sim$ 60 deg$^2$, and ancillary Spitzer observations, we identified 27000 extremely red objects with $H_E-{\rm IRAC}2>2.25$ (dubbed HIEROs) down to a $10σ$ completeness magnitude limit of IRAC2 $=$ 22.5 AB. After a visual inspection to discard artefacts and objects with troubling photometry, we ended up with a final sample of 3900 candidates. We retrieved the physical parameter estimates for these objects from the SED-fitting tool CIGALE. Our results confirm that HIERO galaxies may populate the high-mass end of the stellar mass function at $z>3$, with some reaching extreme stellar masses ($M_*>10^{11}M_\odot$) and exhibiting high dust attenuation ($A_V>3$). However, we consider stellar mass estimates unreliable for $z>3.5$, favouring a lower-z solution. The challenges faced by SED-fitting tools in characterising these objects highlight the need for further studies, incorporating shorter-wavelength and spectroscopic data. Euclid spectra will help resolve degeneracies and better constrain the physical properties of the brightest galaxies. Given the extreme nature of this population, characterising these sources is crucial for understanding galaxy evolution. This work demonstrates Euclid's potential to provide statistical samples of rare, massive, dust-obscured galaxies at $z>3$, which will be prime targets for JWST, ALMA, and ELT.

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Euclid Quick Data Release (Q1) The Strong Lensing Discovery Engine B -- Early strong lens candidates from visual inspection of high velocity dispersion galaxies

We present a search for strong gravitational lenses in Euclid imaging with high stellar velocity dispersion ($σ_ν> 180$ km/s) reported by SDSS and DESI. We performed expert visual inspection and classification of $11\,660$ \Euclid images. We discovered 38 grade A and 40 grade B candidate lenses, consistent with an expected sample of $\sim$32. Palomar spectroscopy confirmed 5 lens systems, while DESI spectra confirmed one, provided ambiguous results for another, and help to discard one. The \Euclid automated lens modeler modelled 53 candidates, confirming 38 as lenses, failing to model 9, and ruling out 6 grade B candidates. For the remaining 25 candidates we could not gather additional information. More importantly, our expert-classified non-lenses provide an excellent training set for machine learning lens classifiers. We create high-fidelity simulations of \Euclid lenses by painting realistic lensed sources behind the expert tagged (non-lens) luminous red galaxies. This training set is the foundation stone for the \Euclid galaxy-galaxy strong lensing discovery engine.

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Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine D -- Double-source-plane lens candidates

Strong gravitational lensing systems with multiple source planes are powerful tools for probing the density profiles and dark matter substructure of the galaxies. The ratio of Einstein radii is related to the dark energy equation of state through the cosmological scaling factor $β$. However, galaxy-scale double-source-plane lenses (DSPLs) are extremely rare. In this paper, we report the discovery of four new galaxy-scale double-source-plane lens candidates in the Euclid Quick Release 1 (Q1) data. These systems were initially identified through a combination of machine learning lens-finding models and subsequent visual inspection from citizens and experts. We apply the widely-used {\tt LensPop} lens forecasting model to predict that the full \Euclid survey will discover 1700 DSPLs, which scales to $6 \pm 3$ DSPLs in 63 deg$^2$, the area of Q1. The number of discoveries in this work is broadly consistent with this forecast. We present lens models for each DSPL and infer their $β$ values. Our initial Q1 sample demonstrates the promise of \Euclid to discover such rare objects.

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Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine E -- Ensemble classification of strong gravitational lenses: lessons for Data Release 1

The Euclid Wide Survey (EWS) is expected to identify of order $100\,000$ galaxy-galaxy strong lenses across $14\,000$deg$^2$. The Euclid Quick Data Release (Q1) of $63.1$deg$^2$ Euclid images provides an excellent opportunity to test our lens-finding ability, and to verify the anticipated lens frequency in the EWS. Following the Q1 data release, eight machine learning networks from five teams were applied to approximately one million images. This was followed by a citizen science inspection of a subset of around $100\,000$ images, of which $65\%$ received high network scores, with the remainder randomly selected. The top scoring outputs were inspected by experts to establish confident (grade A), likely (grade B), possible (grade C), and unlikely lenses. In this paper we combine the citizen science and machine learning classifiers into an ensemble, demonstrating that a combined approach can produce a purer and more complete sample than the original individual classifiers. Using the expert-graded subset as ground truth, we find that this ensemble can provide a purity of $52\pm2\%$ (grade A/B lenses) with $50\%$ completeness (for context, due to the rarity of lenses a random classifier would have a purity of $0.05\%$). We discuss future lessons for the first major Euclid data release (DR1), where the big-data challenges will become more significant and will require analysing more than $\sim300$ million galaxies, and thus time investment of both experts and citizens must be carefully managed.

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Euclid Quick Data Release (Q1). The first catalogue of strong-lensing galaxy clusters

We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering $63.1\,\mathrm{deg^2}$). This catalogue is the result of the visual inspection of 1260 cluster fields. Each galaxy cluster was ranked with a probability, $\mathcal{P}_{\mathrm{lens}}$, based on the number and plausibility of the identified strong lensing features. Specifically, we identified 83 gravitational lenses with $\mathcal{P}_{\mathrm{lens}}>0.5$, of which 14 have $\mathcal{P}_{\mathrm{lens}}=1$, and clearly exhibiting secure strong lensing features, such as giant tangential and radial arcs, and multiple images. Considering the measured number density of lensing galaxy clusters, approximately $0.3\,\mathrm{deg}^{-2}$ for $\mathcal{P}_{\mathrm{lens}}>0.9$, we predict that \Euclid\ will likely see more than 4500 strong lensing clusters over the course of the mission. Notably, only three of the identified cluster-scale lenses had been previously observed from space. Thus, \Euclid has provided the first high-resolution imaging for the remaining $80$ galaxy cluster lenses, including those with the highest probability. The identified strong lensing features will be used for training deep-learning models for identifying gravitational arcs and multiple images automatically in \Euclid observations. This study confirms the huge potential of \Euclid for finding new strong lensing clusters, enabling exciting new discoveries on the nature of dark matter and dark energy and the study of the high-redshift Universe.

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Euclid Quick Data Release (Q1). Galaxy shapes and alignments in the cosmic web

Galaxy morphologies and shape orientations are expected to correlate with their large-scale environment, since they grow by accreting matter from the cosmic web and are subject to interactions with other galaxies. Cosmic filaments are extracted in projection from the Euclid Quick Data Release 1 (covering 63.1 $\mathrm{deg}^2$) at $0.5 10^{10} M_\odot$) in the projected cosmic web is analysed as a function of morphology measured from VIS data. Specifically, the 2D alignment of galaxy shapes with large-scale filaments is quantified as a function of Sérsic indices and masses. We find the known trend that more massive galaxies are closer to filament spines. At fixed stellar masses, morphologies correlate both with densities and distances to large-scale filaments. In addition, the large volume of this data set allows us to detect a signal indicating that there is a preferential alignment of the major axis of massive early-type galaxies along projected cosmic filaments. Overall, these results demonstrate our capabilities to carry out detailed studies of galaxy environments with Euclid, which will be extended to higher redshift and lower stellar masses with the future Euclid Deep Survey.

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Euclid: Quick Data Release (Q1) -- Photometric studies of known transients

We report on serendipitous Euclid observations of previously known transients, using the Euclid Q1 data release. By cross-matching with the Transient Name Server (TNS) we identify 164 transients that coincide with the data release. Although the Euclid Q1 release only includes single-epoch data, we are able to make Euclid photometric measurements at the location of 161 of these transients. Euclid obtained deep photometric measurements or upper limits of these transients in the $I_E$, $Y_E$, $J_E$, and $H_E$ bands at various phases of the transient light-curves, including before, during, and after the observations of ground-based transient surveys. Approximately 70\% of known transients reported in the six months before the Euclid observation date and with discovery magnitude brighter than 24 were detected in Euclid $\IE$ images. Our observations include one of the earliest near-infrared detections of a Type~Ia supernova (SN 2024pvw) 15 days prior to its peak brightness, and the late-phase (435.9 days post peak) observations of the enigmatic core-collapse SN 2023aew. Euclid deep photometry provides valuable information on the nature of these transients such as their progenitor systems and power sources, with late time observations being a uniquely powerful contribution. In addition, Euclid is able to detect the host galaxies of some transients that were previously classed as hostless. The Q1 data demonstrate the power of the Euclid data even with only single-epoch observations available, as will be the case for much larger areas of sky in the Euclid Wide Survey.

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Euclid: Quick Data Release (Q1) -- A census of dwarf galaxies across a range of distances and environments

The Euclid Q1 fields were selected for calibration purposes in cosmology and are therefore relatively devoid of nearby galaxies. However, this is precisely what makes them interesting fields in which to search for dwarf galaxies in local density environments. We take advantage of the unprecedented depth, spatial resolution, and field of view of the Euclid Quick Release (Q1) to build a census of dwarf galaxies in these regions. We have identified dwarfs in a representative sample of 25 contiguous tiles in the Euclid Deep Field North (EDF-N), covering an area of 14.25 sq. deg. The dwarf candidates were identified using a semi-automatic detection method, based on properties measured by the Euclid pipeline and listed in the MER catalogue. A selection cut in surface brightness and magnitude was used to produce an initial dwarf candidate catalogue, followed by a cut in morphology and colour. This catalogue was visually classified to produce a final sample of dwarf candidates, including their morphology, number of nuclei, globular cluster (GC) richness, and presence of a blue compact centre. We identified 2674 dwarf candidates, corresponding to 188 dwarfs per sq. deg. The visual classification of the dwarfs reveals a slightly uneven morphological mix of 58% ellipticals and 42% irregulars, with very few potentially GC-rich (1.0%) and nucleated (4.0%) candidates but a noticeable fraction (6.9%) of dwarfs with blue compact centres. The distance distribution of 388 (15%) of the dwarfs with spectroscopic redshifts peaks at about 400 Mpc. Their stellar mass distribution confirms that our selection effectively identifies dwarfs while minimising contamination. The most prominent dwarf overdensities are dominated by dEs, while dIs are more evenly distributed. This work highlights Euclid's remarkable ability to detect and characterise dwarf galaxies across diverse masses, distances, and environments.

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Solid confirmation of the broad DIB around 864.8 nm using stacked Gaia-RVS spectra

Studies of the correlation between different diffuse interstellar bands (DIBs) are important for exploring their origins. However, the Gaia-RVS spectral window between 846 and 870 nm contains few DIBs, the strong DIB at 862 nm being the only convincingly confirmed one. Here we attempt to confirm the existence of a broad DIB around 864.8 nm and estimate its characteristics using the stacked Gaia-RVS spectra of a large number of stars. We study the correlations between the two DIBs at 862 nm and 864.8 nm, as well as the interstellar extinction. We obtained spectra of the interstellar medium absorption by subtracting the stellar components using templates constructed from real spectra at high Galactic latitudes with low extinctions. We then stacked the ISM spectra in Galactic coordinates, pixelized by the HEALPix scheme, to measure the DIBs. The stacked spectrum is modeled by the profiles of the two DIBs, Gaussian for $λ$862 and Lorentzian for $λ$864.8, and a linear continuum. We obtain 8458 stacked spectra in total, of which 1103 (13%) have reliable fitting results after applying numerous conservative filters. This work is the first of its kind to fit and measure $λ$862 and $λ$864.8 simultaneously in cool-star spectra. We find that the EWs and CDs of the two DIBs are well correlated with each other. The full width at half maximum (FWHM) of $λ$864.8 is estimated as $1.62 \pm 0.33$ nm which compares to $0.55 \pm 0.06$ nm for $λ$862. We also measure the vacuum rest-frame wavelength of $λ$864.8 to be $λ_0 = 864.53 \pm 0.14$ nm, smaller than previous estimates. We find a solid confirmation of the existence of the DIB around 864.8 nm based on an exploration of its correlation with $λ$862 and estimation of its FWHM. $λ$862 correlates better with E(BP-RP) than $λ$864.8.

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Gaia Data Release 3: Properties of the line broadening parameter derived with the Radial Velocity Spectrometer (RVS)

The third release of the Gaia catalogue contains the radial velocities for 33,812,183 stars having effective temperatures ranging from 3100 K to 14,500 K. The measurements are based on the comparison of the observed RVS spectrum (wavelength coverage: 846--870 nm, median resolving power: 11,500) to synthetic data broadened to the adequate Along-Scan Line Spread Function. The additional line-broadening, fitted as it would only be due to axial rotation, is also produced by the pipeline and is available in the catalogue (field name gaia_source:vbroad). To describe the properties of the line-broadening information extracted from the RVS and published in the catalogue, as well as to analyse the limitations imposed by the adopted method, wavelength range, and instrument. We use simulations to express the link existing between the line broadening measurement provided in Gaia Data Release 3 and Vsin(i). We then compare the observed values to the measurements published by various catalogues and surveys (GALAH, APOGEE, LAMOST, ...). While we recommend being cautious in the interpretation of the vbroad measurement, we also find a reasonable global agreement between the Gaia Data Release 3 line broadening values and those found in the other catalogues. We discuss and establish the validity domain of the published vbroad values. The estimate tends to be overestimated at the lower vsini end, and at $T_\mathrm{eff}>7500\,\mathrm{K}$ its quality and significance degrade rapidly when $G_\mathrm{RVS}>10$. Despite all the known and reported limitations, the Gaia Data Release 3 line broadening catalogue contains the measurements obtained for 3,524,677 stars with $T_\mathrm{eff}$\ ranging from 3500 to 14,500 K, and $G_\mathrm{RVS}<12$. It gathers the largest stellar sample ever considered for the purpose, and allows a first mapping of the \Gaia\ line broadening parameter across the HR diagram.

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Gaia Data Release 3 Properties and validation of the radial velocities

Gaia Data Release 3 (Gaia DR3) contains the second release of the combined radial velocities. It is based on the spectra collected during the first 34 months of the nominal mission. The longer time baseline and the improvements of the pipeline made it possible to push the processing limit, from Grvs = 12 in Gaia DR2, to Grvs = 14 mag. In this article, we describe the new functionalities implemented for Gaia DR3, the quality filters applied during processing and post-processing and the properties and performance of the published velocities. For Gaia DR3, several functionalities were upgraded or added. (Abridged) Gaia DR3 contains the combined radial velocities of 33 812 183 stars. With respect to Gaia DR2, the interval of temperature has been expanded from Teff \in [3600, 6750] K to Teff \in [3100, 14500] K for the bright stars ( Grvs \leq 12 mag) and [3100, 6750] K for the fainter stars. The radial velocities sample a significant part of the Milky Way: they reach a few kilo-parsecs beyond the Galactic centre in the disc and up to about 10-15 kpc vertically into the inner halo. The median formal precision of the velocities is of 1.3 km/s at Grvs = 12 and 6.4 km/s at Grvs = 14 mag. The velocity zero point exhibits a small systematic trend with magnitude starting around Grvs = 11 mag and reaching about 400 m/s at Grvs = 14 mag. A correction formula is provided, which can be applied to the published data. The Gaia DR3 velocity scale is in satisfactory agreement with APOGEE, GALAH, GES and RAVE, with systematic differences that mostly do not exceed a few hundreds m/s. The properties of the radial velocities are also illustrated with specific objects: open clusters, globular clusters as well as the Large Magellanic Cloud (LMC). For example, the precision of the data allows to map the line-of-sight rotational velocities of the globular cluster 47 Tuc and of the LMC.

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Gaia Data Release 3: G_RVS photometry from the RVS spectra

Gaia Data Release 3 (DR3) contains the first release of magnitudes estimated from the integration of Radial Velocity Spectrometer (RVS) spectra for a sample of about 32.2 million stars brighter than G_RVS~14 mag (or G~15 mag). In this paper, we describe the data used and the approach adopted to derive and validate the G_RVS magnitudes published in DR3. We also provide estimates of the G_RVS passband and associated G_RVS zero-point. We derived G_RVS photometry from the integration of RVS spectra over the wavelength range from 846 to 870 nm. We processed these spectra following a procedure similar to that used for DR2, but incorporating several improvements that allow a better estimation of G_RVS. These improvements pertain to the stray-light background estimation, the line spread function calibration, and the detection of spectra contaminated by nearby relatively bright sources. We calibrated the G_RVS zero-point every 30 hours based on the reference magnitudes of constant stars from the Hipparcos catalogue, and used them to transform the integrated flux of the cleaned and calibrated spectra into epoch magnitudes. The G_RVS magnitude of a star published in DR3 is the median of the epoch magnitudes for that star. We estimated the G_RVS passband by comparing the RVS spectra of 108 bright stars with their flux-calibrated spectra from external spectrophotometric libraries. The G_RVS magnitude provides information that is complementary to that obtained from the G, G_BP, and G_RP magnitudes, which is useful for constraining stellar metallicity and interstellar extinction. The median precision of G_RVS measurements ranges from about 0.006 mag for the brighter stars (i.e. with 3.5 < G_RVS < 6.5 mag) to 0.125 mag at the faint end. The derived G_RVS passband shows that the effective transmittance of the RVS is approximately 1.23 times better than the pre-launch estimate.

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Gaia Data Release 3: Hot-star radial velocities

The second Gaia data release, DR2, contained radial velocities of stars with effective temperatures up to Teff = 6900 K. The third data release, Gaia DR3, extends this up to Teff = 14,500 K. We derive the radial velocities for hot stars (i.e. in the Teff = 6900 - 14,500 K range) from data obtained with the Radial Velocity Spectrometer (RVS) on board Gaia. The radial velocities were determined by the standard technique of measuring the Doppler shift of a template spectrum that was compared to the observed spectrum. The RVS wavelength range is very limited. The proximity to and systematic blueward offset of the calcium infrared triplet to the hydrogen Paschen lines in hot stars can result in a systematic offset in radial velocity. For the hot stars, we developed a specific code to improve the selection of the template spectrum, thereby avoiding this systematic offset. With the improved code, and with the correction we propose to the DR3 archive radial velocities, we obtain values that agree with reference values to within 3 km/s (in median). Because of the required S/N for applying the improved code, the hot star radial velocities in DR3 are mostly limited to stars with a magnitude in the RVS wavelength band <= 12 mag.

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Gaia Early Data Release 3: Updated radial velocities from Gaia DR2

Gaia's Early Third Data Release (EDR3) does not contain new radial velocities because these will be published in Gaia's full third data release (DR3), expected in the first half of 2022. To maximise the usefulness of EDR3, Gaia's second data release (DR2) sources (with radial velocities) are matched to EDR3 sources to allow their DR2 radial velocities to also be included in EDR3. This presents two considerations: (i) arXiv:1901.10460 (hereafter B19) published a list of 70,365 sources with potentially contaminated DR2 radial velocities; and (ii) EDR3 is based on a new astrometric solution and a new source list, which means sources in DR2 may not be in EDR3. EDR3 contains 7,209,831 sources with a DR2 radial velocity, which is 99.8% of sources with a radial velocity in DR2. 14,800 radial velocities from DR2 are not propagated to any EDR3 sources because (i) 3871 from the B19 list are found to either not have an unpublished, preliminary DR3 radial velocity or it differs significantly from its DR2 value, and 5 high-velocity stars not in the B19 list are confirmed to have contaminated radial velocities; and (ii) 10,924 DR2 sources could not be satisfactorily matched to any EDR3 sources, so their DR2 radial velocities are also missing from EDR3. The reliability of radial velocities in EDR3 has improved compared to DR2 because the update removes a small fraction of erroneous radial velocities (0.05% of DR2 radial velocities and 5.5% of the B19 list). Lessons learnt from EDR3 (e.g. bright star contamination) will improve the radial velocities in future Gaia data releases. The main reason for radial velocities from DR2 not propagating to EDR3 is not related to DR2 radial velocity quality. It is because the DR2 astrometry is based on one component of close binary pairs, while EDR3 astrometry is based on the other component, which prevents these sources from being unambiguously matched. (Abridged)

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Gaia Photometric Science Alerts

Since July 2014, the Gaia mission has been engaged in a high-spatial-resolution, time-resolved, precise, accurate astrometric, and photometric survey of the entire sky. Aims: We present the Gaia Science Alerts project, which has been in operation since 1 June 2016. We describe the system which has been developed to enable the discovery and publication of transient photometric events as seen by Gaia. Methods: We outline the data handling, timings, and performances, and we describe the transient detection algorithms and filtering procedures needed to manage the high false alarm rate. We identify two classes of events: (1) sources which are new to Gaia and (2) Gaia sources which have undergone a significant brightening or fading. Validation of the Gaia transit astrometry and photometry was performed, followed by testing of the source environment to minimise contamination from Solar System objects, bright stars, and fainter near-neighbours. Results: We show that the Gaia Science Alerts project suffers from very low contamination, that is there are very few false-positives. We find that the external completeness for supernovae, $C_E=0.46$, is dominated by the Gaia scanning law and the requirement of detections from both fields-of-view. Where we have two or more scans the internal completeness is $C_I=0.79$ at 3 arcsec or larger from the centres of galaxies, but it drops closer in, especially within 1 arcsec. Conclusions: The per-transit photometry for Gaia transients is precise to 1 per cent at $G=13$, and 3 per cent at $G=19$. The per-transit astrometry is accurate to 55 milliarcseconds when compared to Gaia DR2. The Gaia Science Alerts project is one of the most homogeneous and productive transient surveys in operation, and it is the only survey which covers the whole sky at high spatial resolution (subarcsecond), including the Galactic plane and bulge.

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