Digital Sky Survey Data Release Research Articles

Properties of isolated galaxies in the Digital Survey Isolated Galaxies (DSIG) catalogue within a redshift range (0.005 < z < 0.080)

ABSTRACT Evolution of galaxies is known to be influenced by a number of factors such as the environment that hosts the galaxy as well as the galaxies intrinsic properties. The environmental effects on galaxy properties have not been fully quantified. In our study, we analysed a sample of isolated galaxies within 0.005 < z < 0.080 from Sloan Digital Sky Survey data release 16, as part of a Digital Survey Isolated Galaxies catalogue. The aim was to investigate intrinsic physical properties of singly isolated galaxies in low-density environment. We investigated the galaxies morphology, colour, luminosity, stellar masses, and star formation rates (SFRs). A concentration index, Cr, of 2.65 separates our isolated sample into early and late types, with the late-types (spiral galaxies) dominating the isolated sample at 68 per cent as confirmed from the visually classified sample obtained from Galaxy Zoo. Our isolated ellipticals are redder, massive, and more luminous, while the isolated spirals are blue, less massive, and less luminous. Both the isolated spirals and ellipticals have steeper colour relations indicating a fast transition to the red sequence. In the colour–colour analysis, most ellipticals were quiescent with the majority of spirals being star forming. 5 per cent of the isolated ellipticals have recently quenched their star formation and are transiting to the red sequence. The isolated spirals experiences higher star-forming activities, with a small fraction of passively evolving high-mass isolated spirals. Similarly, isolated ellipticals exhibit low SFRs indicating passive evolution, with a fraction being actively star forming.

Quasar Factor Analysis—An Unsupervised and Probabilistic Quasar Continuum Prediction Algorithm with Latent Factor Analysis

Since their first discovery, quasars have been essential probes of the distant Universe. However, due to our limited knowledge of its nature, predicting the intrinsic quasar continua has bottlenecked their usage. Existing methods of quasar continuum recovery often rely on a limited number of high-quality quasar spectra, which might not capture the full diversity of the quasar population. In this study, we propose an unsupervised probabilistic model, quasar factor analysis (QFA), which combines factor analysis with physical priors of the intergalactic medium to overcome these limitations. QFA captures the posterior distribution of quasar continua through generatively modeling quasar spectra. We demonstrate that QFA can achieve the state-of-the-art performance, ∼2% relative error, for continuum prediction in the Lyα forest region compared to previous methods. We further fit 90,678 2 < z < 3.5, signal-to-noise ratio >2 quasar spectra from Sloan Digital Sky Survey Data Release 16 and found that for ∼30% quasar spectra where the continua were ill-determined with previous methods, QFA yields visually more plausible continua. QFA also attains ≲1% error in the 1D Lyα power spectrum measurements at z ∼ 3 and ∼4% in z ∼ 2.4. In addition, QFA determines latent factors representing more physical motivation than principal component analysis. We investigate the evolution of the latent factors and report no significant redshift or luminosity dependency except for the Baldwin effect. The generative nature of QFA also enables outlier detection robustly; we showed that QFA is effective in selecting outlying quasar spectra, including damped Lyα systems and potential Type II quasar spectra.

NGC 5216: An interesting galaxy with a sign of merging activity

We present results of isophotal shape analysis of an interesting elliptical galaxy NGC 5216 with a clear sign of merging activity with its companion galaxy NGC 5218. We have used r-bands image analysis of the galaxy from Sloan Digital Sky Survey Data Release 9 (i.e. SDSS DR9) to perform bulge-disk decomposition of the light profile of the galaxy. We look for the correlation between systematic departure of isophotes from pure ellipses along the semi-major axis of the galaxies. The contour image of the galaxy clearly indicates that stellar mass exchange is taking place via a star forming bridge. The estimated B/T value confirms its morphology as an elliptical galaxy.

Mass Dependence of Galaxy–Halo Alignment in LOWZ and CMASS

We measure the galaxy-ellipticity (GI) correlations for the Sloan Digital Sky Survey Data Release 12 LOWZ and CMASS samples with the shape measurements from the DESI Legacy Imaging Surveys. We model the GI correlations in an N-body simulation with our recent accurate stellar–halo mass relation from the Photometric object Around Cosmic webs (PAC) method. The large data set and our accurate modeling turns out an accurate measurement of the alignment angle between central galaxies and their host halos. We find that the alignment of central elliptical galaxies with their host halos increases monotonically with galaxy stellar mass or host halo mass, which can be well described by a power law for the massive galaxies. We also find that central elliptical galaxies are more aligned with their host halos in LOWZ than in CMASS, which might indicate an evolution of galaxy–halo alignment, though future studies are needed to verify this is not induced by the sample selections. In contrast, central disk galaxies are aligned with their host halos about 10 times more weakly in the GI correlation. These results have important implications for intrinsic alignment (IA) correction in weak lensing studies, IA cosmology, and theory of massive galaxy formation.

Efficient galaxy classification through pretraining

Deep learning has increasingly been applied to supervised learning tasks in astronomy, such as classifying images of galaxies based on their apparent shape (i.e., galaxy morphology classification) to gain insight regarding the evolution of galaxies. In this work, we examine the effect of pretraining on the performance of the classical AlexNet convolutional neural network (CNN) in classifying images of 14,034 galaxies from the Sloan Digital Sky Survey Data Release 4. Pretraining involves designing and training CNNs on large labeled image datasets unrelated to astronomy, which takes advantage of the vast amounts of such data available compared to the relatively small amount of labeled galaxy images. We show a statistically significant benefit of using pretraining, both in terms of improved overall classification success and reduced computational cost to achieve such performance.

Fantastic Fits with fantasy of Active Galactic Nuclei Spectra: Exploring the Fe ii Emission near the Hα Line

In this study, a refined approach for multicomponent fitting of active galactic nuclei (AGNs) spectra is presented utilizing the newly developed Python code Fully Automated pythoN Tool for AGN Spectra analYsis (fantasy). AGN spectra are modeled by simultaneously considering the underlying broken power-law continuum, predefined emission line lists, and an Fe ii model, which is here extended to cover the wavelength range 3700–11000 Å. The Fe ii model, founded solely on atomic data, effectively describes the extensive emission of the complex iron ion in the vicinity of the Hγ and Hβ lines, as well as near the Hα line, which was previously rarely studied. The proposed spectral fitting approach is tested on a sample of high-quality AGN spectra from the Sloan Digital Sky Survey Data Release 17. The results indicate that when Fe ii emission is present near Hβ, it is also detected redward from Hα, potentially contaminating the broad Hα line wings and thus affecting the measurements of its flux and width. The production of Fe ii emission is found to be strongly correlated with Eddington luminosity and appears to be controlled by a similar mechanism as the hydrogen Balmer lines. The study highlights the benefits of fitting type 1 AGN spectra with the fantasy code, pointing that it may be used as a robust tool for analyzing a large number of AGN spectra in the coming spectral surveys.

Constraining the spatial curvature with cosmic expansion history in a cosmological model with a non-standard sound horizon

Spatial curvature is one of the most fundamental parameters in our current concordance flat ΛCDM model of the Universe. The goal of this work is to investigate how the constraint on the spatial curvature is affected by an assumption on the sound horizon scale. The sound horizon is an essential quantity to use the standard ruler from the Cosmic Microwave Background (CMB) and Baryon Acoustic Oscillations (BAOs). As an example, we study the curvature constraint in an axion-like Early Dark Energy (EDE) model in light of recent cosmological datasets from Planck, the South Pole Telescope (SPT), and the Atacama Cosmology Telescope (ACT), as well as BAO data compiled in Sloan Digital Sky Survey Data Release 16. We find that, independent of the CMB datasets, the EDE model parameters are constrained only by the CMB power spectra as precisely and consistently as the flat case in previous work, even with the spatial curvature. We also demonstrate that combining CMB with BAO is extremely powerful to constrain the curvature parameter even with a reduction of the sound-horizon scale in an EDE model, resulting in Ω K = -0.0058± 0.0031 in the case of ACT+BAO after marginalizing over the parameters of the EDE model. This constraint is as competitive as the Planck+BAO result in a ΛCDM model, Ω K = -0.0001± 0.0018.

The impact of environmental effects on active galactic nuclei: A decline in the incidence of ionized outflows

Active galactic nuclei (AGNs) have generally been considered to be less frequent in denser environments due to a lower number of galaxy-galaxy interactions and/or the removal of their gas-rich reservoirs by the dense intergalactic medium. However, recent observational and theoretical works suggest that the effect of ram-pressure stripping acting on galaxies in dense environments might reduce the angular momentum of their gas, causing it to infall towards the super massive black hole at their centre, activating the AGN phase. In this work we explore the connection between environment and nuclear activity by evaluating the variation in the incidence of ionized outflows, a common phenomenon associated with nuclear activity, in AGNs across different environments. We select a sample of approximately 3300 optical AGNs from the Sloan Digital Sky Survey Data Release 13, which we match with a group catalogue to identify galaxies in isolation or residing in groups. We further probe their environments through the projected distance to the central galaxy of the group or cluster and the projected surface density to the fifth neighbour (δ5). The presence of ionized outflows is determined through the modelling of the [O III] λ5007 emission line. We find that at lower masses (&lt; 1010.3 M⊙), the fraction of ionized outflows is significantly lower in satellite AGNs (∼7%) than in isolated (∼22%) AGNs, probably due to their different AGN luminosity, L[O III], in this stellar mass range. The fraction of outflows decreases at distances closer to the central galaxy of the group or cluster for all satellite AGNs; however, only the lower-mass ones (109 − 1010.3 M⊙) display a significant decline with δ5. Although this study does not include AGNs in the densest regions of galaxy clusters, our findings suggest that AGNs in dense environments accrete less gas than those in the field, potentially due to the removal of the gas reservoirs via stripping or starvation, leading to a negative connection between environment and AGN activity. Based on our results, we propose that the observed change in the incidence of outflows when moving towards denser regions of groups and clusters could contribute to the higher gas metallicities of cluster galaxies compared to field galaxies, especially at lower masses.

Investigation of Stellar Kinematics and Ionized Gas Outflows in Local (U)LIRGs

We explore the properties of stellar kinematics and ionized gas in a sample of 1106 local (U)LIRGs from the AKARI telescope. We combine data from Wide-field Infrared Survey Explorer and Sloan Digital Sky Survey Data Release 13 to fit the spectral energy distribution (SED) of each source to constrain the contribution of active galactic nuclei (AGNs) to the total IR luminosity and estimate physical parameters such as stellar mass and star formation rate (SFR). We split our sample into AGNs and weak/non-AGNs. We find that our sample is considerably above the main sequence. The highest SFRs and stellar masses are associated with ULIRGs. We also fit the Hβ and Hα regions to characterize the outflows. We find that the incidence of ionized gas outflows in AGN (U)LIRGs (∼72%) is much higher than that in weak/non-AGN ones (∼39%). The AGN ULIRGs have extreme outflow velocities (up to ∼2300 km s−1) and high mass-outflow rates (up to ∼60 M ⊙ yr−1). Our results suggest that starbursts are insufficient to produce such powerful outflows. We explore the correlations of SFR and specific SFR (sSFR) with ionized gas outflows. We find that AGN hosts with the highest SFRs exhibit a negative correlation between outflow velocity and sSFR. Therefore, in AGNs containing large amounts of gas, the negative feedback scenario might be suggested.

Catalog of Planetary Nebulae Detected by GALEX and Corollary Optical Surveys

Planetary nebulae (PNs) consist of an ionized envelope surrounding a hot central star (CSPN) that emits mostly at ultraviolet (UV) wavelengths. UV observations, therefore, provide important information on both the CSPN and the nebula. We have matched the PNs in the Hong Kong/Australian Astronomical Observatory/Strasbourg Hα catalog with the Galaxy Evolution Explorer (GALEX) UV sky surveys, the Sloan Digital Sky Survey (SDSS) data release 16, and the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) PS1 second release. A total of 671 PNs were observed by GALEX with the far-UV (FUV; 1344 Å–1786 Å) and/or the near-UV (NUV; 1771 Å–2831 Å) detectors on (GUVPNcat); 83 were observed by SDSS (PNcatxSDSSDR16) and 1819 by Pan-STARRS (PNcatxPS1MDS). We merged a distilled version of these matched catalogs into GUVPNcatxSDSSDR16xPS1MDS, which contains a total of 375 PNs with both UV and optical photometry over a total spectral coverage of ∼1540 Å–9610 Å. We analyzed separately 170 PNs resolved in GALEX images and determined their UV radius by applying a flux profile analysis. The CSPN flux could be extracted separately from the PN emission for 8 and 50 objects with SDSS and Pan-STARRS counterparts, respectively. The multiband photometry was used to distinguish between compact and extended PNs and CSPNs (binary CSPNs) by color–color diagram analysis. We found that compact PN candidates could be identified by using the r − i < − 0.4 and −1 < FUV−NUV < 1 colors, whereas binary CSPN candidates in given T eff ranges (all with color r−i > −0.4) can be identified in the color region (FUV−NUV) ≤ 6(r−i)+1.3, −0.8 < FUV−NUV < 0.4, and r−i < 0.75.

The shape of dark matter haloes: results from weak lensing in the ultraviolet near-infrared optical Northern survey (UNIONS)

ABSTRACT Cold dark matter haloes are expected to be triaxial and so appear elliptical in projection. We use weak gravitational lensing from the Canada–France Imaging Survey (CFIS) component of the Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) to measure the ellipticity of the dark matter haloes around Luminous Red Galaxies (LRGs) from the Sloan Digital Sky Survey Data Release 7 (DR7) and from the CMASS and LOWZ samples of the Baryon Oscillation Spectroscopic Survey (BOSS), assuming their major axes are aligned with the stellar light. We find that DR7 LRGs with masses M ∼ 2.7 × 1013 M⊙ h−1 have halo ellipticities e = 0.46 ± 0.10. Expressed as a fraction of the galaxy's ellipticity, we find fh = 2.2 ± 0.6. For BOSS LRGs, the detection is of marginal significance: e = 0.20 ± 0.10 and fh = 0.7 ± 0.7. These results are in agreement with other measurements of halo ellipticity from weak lensing and, taken together with previous results, suggest an increase in halo ellipticity of 0.10 ± 0.06 per decade in halo mass. This trend agrees with the predictions from hydrodynamical simulations, which find that at higher halo masses, not only do dark matter haloes become more elliptical, but that the misalignment between the major axis of the stellar light in the central galaxy and that of the dark matter decreases.

Applied Machine-Learning Models to Identify Spectral Sub-Types of M Dwarfs from Photometric Surveys

M dwarfs are the most abundant stars in the Solar Neighborhood and they are prime targets for searching for rocky planets in habitable zones. Consequently, a detailed characterization of these stars is in demand. The spectral sub-type is one of the parameters that is used for the characterization and it is traditionally derived from the observed spectra. However, obtaining the spectra of M dwarfs is expensive in terms of observation time and resources due to their intrinsic faintness. We study the performance of four machine-learning (ML) models—K-Nearest Neighbor (KNN), Random Forest (RF), Probabilistic Random Forest (PRF), and Multilayer Perceptron (MLP)—in identifying the spectral sub-types of M dwarfs at a grand scale by deploying broadband photometry in the optical and near-infrared. We trained the ML models by using the spectroscopically identified M dwarfs from the Sloan Digital Sky Survey (SDSS) Data Release (DR) 7, together with their photometric colors that were derived from the SDSS, Two-Micron All-Sky Survey, and Wide-field Infrared Survey Explorer. We found that the RF, PRF, and MLP give a comparable prediction accuracy, 74%, while the KNN provides slightly lower accuracy, 71%. We also found that these models can predict the spectral sub-type of M dwarfs with ∼99% accuracy within ±1 sub-type. The five most useful features for the prediction are r − z, r − i, r − J, r − H , and g − z, and hence lacking data in all SDSS bands substantially reduces the prediction accuracy. However, we can achieve an accuracy of over 70% when the r and i magnitudes are available. Since the stars in this study are nearby (d ≲ 1300 pc for 95% of the stars), the dust extinction can reduce the prediction accuracy by only 3%. Finally, we used our optimized RF models to predict the spectral sub-types of M dwarfs from the Catalog of Cool Dwarf Targets for the Transiting Exoplanet Survey Satellite, and we provide the optimized RF models for public use.

The shape distribution of superclusters in SDSS DR12

ABSTRACTGalaxy superclusters, the largest galaxy structures in the cosmic web, are formed due to the gravitational collapse (although they are not usually gravitationally bound). Their geometrical properties can shed light on the structure formation process on cosmological scales, hence on the fundamental properties of gravity itself. In this work we study the distributions of the shape, topology, and morphology of the superclusters extracted from Sloan Digital Sky Survey Data Release 12 (SDSS DR12) main galaxy sample and defined in two different ways – using fixed and adaptive density threshold in the luminosity-density field. To assess the geometry and topology of each individual supercluster, we employ Minkowski functionals and Shapefinders, precisely calculated by the shape diagnostic tool SURFGEN2. Both supercluster samples produce similar shape distributions. Perhaps not surprisingly, most superclusters are spherical in shape with trivial topology. However, large superclusters with volumes V ≳ 104 Mpc3 are statistically found to be filamentary with non-zero genus values. The results, supercluster catalogues and shape distributions are publicly available.

Chemical abundances in Seyfert galaxies – X. Sulphur abundance estimates

ABSTRACT For the first time, the sulphur abundance relative to hydrogen (S/H) in the narrow-line regions of a sample of Seyfert 2 nuclei (Sy 2s) has been derived via direct estimation of the electron temperature. Narrow emission-line intensities from the Sloan Digital Sky Survey (SDSS) Data Release 17 (DR17) [in the wavelength range 3000 &amp;lt; λ(Å) &amp;lt; 9100] and from the literature for a sample of 45 nearby (z &amp;lt; 0.08) Sy 2s were considered. Our direct estimates indicate that Sy 2s have similar temperatures in the gas region where most of the $\rm S\rm ^{+}$ ions are located in comparison with that of star-forming regions (SFs). However, Sy 2s present higher temperature values (${\sim} 10\, 000$ K) in the region where most of the $\rm S\rm ^{2+}$ ions are located relative to that of SFs. We derive the total sulphur abundance in the range of $6.2 \: \lesssim 12+\log (\rm S/H) \: \lesssim \: 7.5$, corresponding to 0.1–1.8 times the solar value. These sulphur abundance values are lower by ∼0.4 dex than those derived in SFs with similar metallicity, indicating a distinct chemical enrichment of the interstellar medium (ISM) for these object classes. The sulphur abundance relative to oxygen (S/O) values for our Sy 2 sample present an abrupt (∼0.5 dex) decrease with increasing oxygen abundance relative to hydrogen (O/H) for the high-metallicity regime [$\rm 12+\log (O/H) \: \gtrsim 8.7)$], what is not seen for the SFs. However, when our Sy 2 estimates are combined with those from a large sample of SFs, we did not find any dependence between S/O and O/H.

CLASS Survey Description: Coronal-line Needles in the SDSS Haystack

Coronal lines are a powerful, yet poorly understood, tool to identify and characterize active galactic nuclei. There have been few large-scale surveys of coronal lines in the general galaxy population in the literature so far. Using a novel preselection technique with a flux-to-rms ratio , followed by Markov Chain Monte Carlo fitting, we searched for the full suite of 20 coronal lines in the optical spectra of almost 1 million galaxies from the Sloan Digital Sky Survey Data Release 8. We present a catalog of the emission-line parameters for the resulting 258 galaxies with detections. The Coronal Line Activity Spectroscopic Survey includes line properties, host-galaxy properties, and selection criteria for all galaxies in which at least one line is detected. This comprehensive study reveals that a significant fraction of coronal-line activity is missed in past surveys based on a more limited set of coronal lines; ∼60% of our sample do not display the more widely surveyed [Fe x] λ6374. In addition, we discover a strong correlation between coronal-line and Wide-field Infrared Survey Explorer W2 luminosities, suggesting that the mid-infrared flux can be used to predict coronal-line fluxes. For each line we also provide a confidence level that the line is present, generated by a novel neural network, trained on fully simulated data. We find that after training the network to detect individual lines using 100,000 simulated spectra, we achieve an overall true-positive rate of 75.49% and a false-positive rate of only 3.96%.

Updated Void Catalogs of the SDSS DR7 Main Sample

We produce several public void catalogs using a volume-limited subsample of the Sloan Digital Sky Survey Data Release 7 (SDSS DR7). Using new implementations of three different void-finding algorithms, VoidFinder and two ZOBOV-based algorithms (VIDE and REVOLVER), we identify 1163, 531, and 518 cosmic voids with radii >10 h −1 Mpc, respectively, out to a redshift of z = 0.114 assuming a Planck 2018 cosmology, and 1184, 535, and 519 cosmic voids assuming a WMAP5 cosmology. We compute effective radii and centers for all voids and find none with an effective radius >54 h −1 Mpc. The median void effective radius is 15–19 h −1 Mpc for all three algorithms. We extract and discuss several properties of the void populations, including radial density profiles, the volume fraction of the catalog contained within voids, and the fraction of galaxies contained within voids. Using 64 mock galaxy catalogs created from the Horizon Run 4 N-body simulation, we compare simulated and observed void properties and find good agreement between the SDSS DR7 and mock catalog results.

Hickson-like compact groups inhabiting different environments

ABSTRACT Although compact groups (CGs) of galaxies have been envisioned as isolated extremely dense structures in the Universe, it is accepted today that many of them could be not as isolated as thought. In this work, we study Hickson-like CGs identified in the Sloan Digital Sky Survey Data Release 16 to analyse these systems and their galaxies when embedded in different cosmological structures. To achieve this goal, we identify several cosmological structures where CGs can reside: nodes of filaments, loose groups, filaments, and cosmic voids. Our results indicate that 45 per cent of CGs do not reside in any of these structures, i.e. they can be considered non-embedded or isolated systems. Most of the embedded CGs are found inhabiting loose groups and nodes, while there are almost no CGs residing well inside cosmic voids. Some physical properties of CGs vary depending on the environment they inhabit. CGs in nodes show the largest velocity dispersions, the brightest absolute magnitude of the first-ranked galaxy, and the smallest crossing times, while the opposite occurs in non-embedded CGs. When comparing galaxies in all the environments and galaxies in CGs, CGs show the highest fractions of red/early-type galaxy members in most of the absolute magnitudes ranges. The variation between galaxies in CGs inhabiting one or another environment is not as significant as the differences caused by belonging or not to a CG. Our results suggest a plausible scenario for galaxy evolution in CGs in which both large-scale and local environments play essential roles.

A Multiwavelength Study of Active Galactic Nuclei in Post-merger Remnants

We investigate the role of galaxy mergers in triggering active galactic nuclei (AGN) in the nearby universe. Our analysis is based on a sample of 79 post-merger remnant galaxies with deep X-ray observations from Chandra/XMM-Newton capable of detecting a low-luminosity AGN of ≥1040.5 erg s−1. This sample is derived from a visually classified, volume-limited sample of 807 post-mergers identified in the Sloan Digital Sky Survey Data Release 14 with log M */M ⊙ ≥ 10.5 and 0.02 ≤ z ≤ 0.06. We find that the X-ray AGN fraction in this sample is 55.7% ± 5.6% compared to 23.6% ± 2.8% for a mass- and redshift-matched noninteracting control sample. The multiwavelength AGN fraction (identified as an AGN in one of X-ray, IR, radio or optical diagnostics) for post-mergers is 76.6% ± 4.8% compared to 39.1% ± 3.2% for controls. Thus post-mergers exhibit a high overall AGN fraction with an excess between 2 and 4 depending on the AGN diagnostics used. In addition, we find most optical, IR, and radio AGN are also identified as X-ray AGN while a large fraction of X-ray AGN are not identified in any other diagnostic. This highlights the importance of deep X-ray imaging to identify AGN. We find that the X-ray AGN fraction of post-mergers is independent of the stellar mass above log M */M ⊙ ≥ 10.5 unlike the trend seen in control galaxies. Overall, our results show that post-merger galaxies are a good tracer of the merger–AGN connection and strongly support the theoretical expectations that mergers trigger AGN.

Statistical analysis of Al III and C III] emission lines as virial black hole mass estimators in quasars

Aims. We test the usefulness of the intermediate ionisation lines Al IIIλ1860 and C III]λ1909 as reliable virial mass estimators for quasars. Methods. We identified a sample of 309 quasars from the Sloan Digital Sky Survey Data Release 16 (SDSS DR16) in the redshift range 1.2 ≤ z ≤ 1.4 that have [O II]λ3728 recorded on the same spectrum as Al IIIλ1860, Si III]λ1892, and C III]λ1909. We set the systemic quasar redshift using careful measurements of [O II]λ3728. We then classified the sources as Population A (Pop. A), extreme Population A (Pop. xA), and Population B (Pop. B), and analysed the 1900 Å blend using multi-component models to look for systematic line shifts of Al IIIλ1860 and C III]λ1909 along the quasar main sequence. Results. We do not find significant shifts of the Al IIIλ1860 line peak in Pop. B or in the vast majority of Pop. A. For Pop. xA, a small median blueshift of −250 km s−1 was observed, motivating a decomposition of the Al III line profile into a virialised component centred at rest frame and a blueshifted component for an outflow emission. For Pop. B objects, we proved the empirical necessity to fit a redshifted very broad component, clearly seen in C III], and analysed the physical implications on a Pop. B composite spectrum using CLOUDY simulations. We find consistent black hole mass estimations using Al III and C III] as virial estimators for the bulk of Pop. A. Conclusions. Al III (and even C III]) is a reliable virial black hole mass estimator for Pop. A and Pop. B objects. The Pop. xA sources deserve special attention due to the significant blueshifted excess observed in the line profile of Al III, although it is not as large as the excess observed in C IVλ1549.

Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities

Nonparametric estimation for a probability density function that describes multivariate data has typically been addressed by kernel density estimation (KDE). A novel density estimator recently developed by Farmer and Jacobs offers an alternative high-throughput automated approach to univariate nonparametric density estimation based on maximum entropy and order statistics, improving accuracy over univariate KDE. This article presents an extension of the single variable case to multiple variables. The univariate estimator is used to recursively calculate a product array of one-dimensional conditional probabilities. In combination with interpolation methods, a complete joint probability density estimate is generated for multiple variables. Good accuracy and speed performance in synthetic data are demonstrated by a numerical study using known distributions over a range of sample sizes from 100 to 106 for two to six variables. Performance in terms of speed and accuracy is compared to KDE. The multivariate density estimate developed here tends to perform better as the number of samples and/or variables increases. As an example application, measurements are analyzed over five filters of photometric data from the Sloan Digital Sky Survey Data Release 17. The multivariate estimation is used to form the basis for a binary classifier that distinguishes quasars from galaxies and stars with up to 94% accuracy.