Wide-field Infrared Survey Explorer Research Articles

Photometric Redshift Estimation of Quasars by a Cross-modal Contrast Learning Method

Estimating photometric redshifts (photo-z) of quasars is crucial for measuring cosmic distances and monitoring cosmic evolution. While numerous point estimation methods have successfully determined photo-z, they often struggle with the inherently ill-posed nature of the problem and frequently overlook significant morphological features in the probability density functions (pdfs) of photo-z, such as calibration and sharpness. To address these challenges, we introduce a cross-modal contrastive learning probabilistic model that employs adversarial training, contrastive loss functions, and a mixture density network to estimate the pdf of photo-z. This method facilitates the conversion between multiband photometric data attributes, such as magnitude and color, and photometric image features, while extracting features invariant across modalities. We utilize the continuous ranked probability score (CRPS) and the probability integral transform (PIT) as metrics to assess the quality of the pdf. Our approach demonstrates robust performance across various survey bands, image qualities, and redshift distributions. Specifically, in a comprehensive data set from the Sloan Digital Sky Survey and the Wide-field Infrared Survey Explorer (WISE) survey, our probabilistic model achieved a CRPS of 0.1187. Additionally, in a combined data set from SkyMapper and WISE, it reached a CRPS of 0.0035. Our probabilistic model also produced well-calibrated PIT histograms for both data sets, indicating nearly uniform distributions. We further tested our approach in classification tasks within the SkyMapper data set. Despite the absence of u, v, and g bands, it effectively distinguished between quasars, galaxies, and stars with an accuracy of 98.96%. This versatile method can be extended to other scenarios, such as analyzing extended sources like galaxies, across different surveys and varying redshift distributions.

An Independent Measure of the Kinematic Dipole from SDSS

We utilize the Sloan Digital Sky Survey (SDSS) extended Baryon Oscillation Spectroscopic Survey and Baryon Oscillation Spectroscopic Survey catalogs with precise spectroscopic redshifts to estimate the kinematic redshift dipole caused by the proper motion of the solar system. We find that the velocity extracted from the kinematic dipole is consistent with cosmic microwave background (CMB) inferred values. Although the small sky coverage and limited number density of the SDSS sources constrain us from obtaining precise and robust measurements, we leverage the redshift dipole method to estimate the kinematic dipole. The velocity measurements in this study are insensitive to intrinsic clustering, associated with the source count dipole. The kinematic dipole measured in this work and its consistency with CMB values do not guarantee isotropy at large scales. The anisotropy (excess dipole) measured with the NRAO VLA Sky Survey and the Wide-field Infrared Survey Explorer Catalog could be due to the intrinsic distribution of galaxies. The results in this work focus solely on the kinematic dipole term.

Machine Learning–based Search of High-redshift Quasars

We present a machine learning search for high-redshift (5.0 < z < 6.5) quasars using the combined photometric data from the Dark Energy Spectroscopic Instrument (DESI) Imaging Legacy Surveys and the Wide-field Infrared Survey Explorer survey. We explore the imputation of missing values for high-redshift quasars, discuss the feature selections, compare different machine learning algorithms, and investigate the selections of class ensemble for the training sample, then we find that the random forest model is very effective in separating the high-redshift quasars from various contaminators. The 11 class random forest model can achieve a precision of 96.43% and a recall of 91.53% for high-redshift quasars for the test set. We demonstrate that the completeness of the high-redshift quasars can reach as high as 82.20%. The final catalog consists of 216,949 high-redshift quasar candidates with 476 high probable ones in the entire Legacy Surveys DR9 footprint, and we make the catalog publicly available. Using Multi Unit Spectroscopic Explorer (MUSE) and DESI early data release (EDR) public spectra, we find that 14 true high-redshift quasars (11 in the training sample) out of 21 candidates are correctly identified for MUSE, and 20 true high-redshift quasars (11 in the training sample) out of 21 candidates are correctly identified for DESI-EDR. Additionally, we estimate photometric redshift for the high-redshift quasar candidates using a random forest regression model with a high precision.

The Metallicity Dilution in Local Massive Early-type Galaxies

We derive a sample of 114 Baldwin–Phillips–Terlevich-diagram star-forming and Wide-field Infrared Survey Explorer (WISE) low-star-formation-rate early-type galaxies (ETGs) by utilizing the criterion W2 − W3 < 2.5 (where W2 and W3 are the wavelengths of 4.6 and 12 μm in the WISE four bands) and cross matching the Galaxy Zoo 1 and the catalog of the Sloan Digital Sky Survey (SDSS) Data Release 7 Max Planck Institute for Astrophysics-Johns Hopkins University emission-line measurements. We find that ∼28% of our ETGs exhibit a metallicity that is at least 2 standard deviation (0.26 dex) below the mass–metallicity (MZ) relation of star-forming galaxies (SFGs) from the SDSS. We demonstrate that almost all of our ETGs locate below the “main sequence” of SFGs. We find that these ETGs with larger metallicity deviation from the MZ relation tend to have lower SFR and redder color. By exploring the dilution properties of these massive ETGs, we report that the dilution effect may be mainly attributed to the inflow of metal-poor gas from mergers/interaction or the intergalactic medium.

A Closer Look at Dwarf Galaxies Exhibiting Mid-infrared Variability: Active Galactic Nuclei Confirmation and Comparison With Nonvariable Dwarf Galaxies

Detecting active black holes in dwarf galaxies has proven to be a challenge due to their small size and weak electromagnetic signatures. Mid-infrared variability has emerged as a promising tool that can be used to detect active low-mass black holes in dwarf galaxies. We analyzed 10.4 yr of photometry from the AllWISE/NEOWISE multiepoch catalogs, identifying 25 objects with active galactic nuclei (AGN)-like variability. Independent confirmation of AGN activity was found in 68% of these objects using optical and near-infrared diagnostics. Notably, we discover a near-infrared coronal line [S ix] λ 1.252 μm in J1205, the galaxy with the lowest stellar mass (log M * = 7.5 M ⊙) and low metallicity (12 + log(O/H) = 7.46) in our sample. Additionally, we find broad Paα potentially from the broad-line region in two targets, and their implied black hole masses are consistent with black hole-stellar mass relations. Comparing nonvariable galaxies with similar stellar masses and Wide-field Infrared Survey Explorer W1 − W2 colors, we find no clear trends between variability and large-scale galaxy properties. However, we find that AGN activity likely causes redder W1 − W2 colors in variable targets, while for the nonvariable galaxies, the contribution stems from strong star formation activity. A high incidence of optical broad lines was also observed in variable targets. Our results suggest that mid-infrared variability is an effective method for detecting AGN activity in low-mass galaxies and can help uncover a larger sample of active low-mass (<106 M ⊙) black holes in the Universe.

A machine learning approach to estimate mid-infrared fluxes from WISE data

While the Wide-field Infrared Survey Explorer (WISE) is the largest, best quality infrared all-sky survey to date, a smaller coverage mission Spitzer was designed to have better sensitivity and spatial resolution at similar wavelengths. Confusion and contamination in WISE data result in discrepancies between them. We aim to present a novel approach to work with WISE measurements with the goal of maintaining both its high coverage and vast amount of data while, at the same time, taking full advantage of the higher sensitivity and spatial resolution of Spitzer We have applied machine learning (ML) techniques to a complete WISE data sample of open cluster members, using a training set of paired data from high-quality Spitzer Enhanced Imaging Products (SEIP), MIPS and IRAC, and allWISE catalogs, W1 (3.4 mu m) to W4 (22 mu m) bands. We have tested several ML regression models with the aim of predicting mid-infrared fluxes at MIPS1 (24 mu m) and IRAC4 (8 mu m) bands from WISE variables (fluxes and quality flags). In addition, to improve the prediction quality, we have implemented feature selection techniques to remove irrelevant WISE variables. We have notably enhanced WISE detection capabilities, mostly for the targets with the lowest magnitudes, which previously showed the largest discrepancies with Spitzer . In our particular case, extremely randomized trees was found to be the best algorithm to predict mid-infrared fluxes from WISE variables, attaining coefficients of determination $R^2 and $R^2 for 24 mu m (MIPS1) and 8 mu m (IRAC4), respectively. We have tested our results in members of IC 348 and compared their observed fluxes with the predicted ones in their spectral energy distributions. We show discrepancies in the measurements of Spitzer and WISE and demonstrate the good concordance of our predicted mid-infared fluxes with the real ones. Machine learning is a fast and powerful tool that can be used to find hidden relationships between datasets, as the ones we have shown to exist between WISE and Spitzer fluxes. We believe this approach could be employed for other samples from the allWISE catalog with SEIP positional counterparts, and in other astrophysical studies in which analogous discrepancies might arise when using datasets from different instruments.

Discovery of 118 New Ultracool Dwarf Candidates Using Machine-learning Techniques

We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine-learning tool, named SMDET, applied to time-series images from the Wide-field Infrared Survey Explorer. We gathered photometric and astrometric data to estimate each candidate’s spectral type, distance, and tangential velocity. This sample has a photometrically estimated spectral class distribution of 28 M dwarfs, 64 L dwarfs, and 18 T dwarfs. We also identify a T-subdwarf candidate, two extreme T-subdwarf candidates, and two candidate young ultracool dwarfs. Five objects did not have enough photometric data for any estimations to be made. To validate our estimated spectral types, spectra were collected for two objects, yielding confirmed spectral types of T5 (estimated T5) and T3 (estimated T4). Demonstrating the effectiveness of machine-learning tools as a new large-scale discovery technique.

The rate of extreme coronal line emitting galaxies in the Sloan Digital Sky Survey and their relation to tidal disruption events

ABSTRACT High-ionization iron coronal lines (CLs) are a rare phenomenon observed in galaxy and quasi-stellar object spectra that are thought to be created by high-energy emission from active galactic nuclei and certain types of transients. In cases known as extreme coronal line emitting galaxies (ECLEs), these CLs are strong and fade away on a time-scale of years. The most likely progenitors of these variable CLs are tidal disruption events (TDEs), which produce sufficient high-energy emission to create and sustain the CLs over these time-scales. To test the possible connection between ECLEs and TDEs, we present the most complete variable ECLE rate calculation to date and compare the results to TDE rates from the literature. To achieve this, we search for ECLEs in the Sloan Digital Sky Survey (SDSS). We detect sufficiently strong CLs in 16 galaxies, more than doubling the number previously found in SDSS. Using follow-up spectra from the Dark Energy Spectroscopic Instrument and Gemini Multi-Object Spectrograph, Wide-field Infrared Survey Explorer mid-infrared observations, and Liverpool Telescope optical photometry, we find that none of the nine new ECLEs evolve in a manner consistent with that of the five previously discovered variable ECLEs. Using this sample of five variable ECLEs, we calculate the galaxy-normalized rate of variable ECLEs in SDSS to be $R_\mathrm{G}=3.6~^{+2.6}_{-1.8}~(\mathrm{statistical})~^{+5.1}_{-0.0}~(\mathrm{systematic})\times 10^{-6}~\mathrm{galaxy}^{-1}~\mathrm{yr}^{-1}$. The mass-normalized rate is $R_\mathrm{M}=3.1~^{+2.3}_{-1.5}~(\mathrm{statistical})~^{+4.4}_{-0.0}~(\mathrm{systematic})\times 10^{-17}~\mathrm{M_\odot ^{-1}}~\mathrm{yr}^{-1}$ and the volumetric rate is $R_\mathrm{V}=7~^{+20}_{-5}~(\mathrm{statistical})~^{+10}_{-0.0}~(\mathrm{systematic})\times 10^{-9}~\mathrm{Mpc}^{-3}~\mathrm{yr}^{-1}$. Our rates are one to two orders of magnitude lower than TDE rates from the literature, which suggests that only 10–40 per cent of all TDEs produce variable ECLEs. Additional uncertainties in the rates arising from the structure of the interstellar medium have yet to be included.

Galaxy Classification Using EWGC

The Enhanced Wide-field Galaxy Classification Network (EWGC) is a novel architecture designed to classify spiral and elliptical galaxies using Wide-field Infrared Survey Explorer (WISE) images. The EWGC achieves an impressive classification accuracy of 90.02%, significantly outperforming the previously developed WGC network and underscoring its superior performance in galaxy morphology classification. Remarkably, the network demonstrates a consistent accuracy of 90.02% when processing both multi-target and single-target images. Such robustness indicates the EWGC’s versatility and potential for various applications in galaxy classification tasks.

Evidence of a Forming Nucleus in the Fourcade–Figueroa Galaxy

We analyze data from the IRAS, Wide-field Infrared Survey Explorer, and Planck satellites, revealing an unresolved dust condensation at the center of the Fourcade–Figueroa galaxy (ESO270-G017), which may correspond to a forming nucleus. We model the condensation’s continuum spectrum in the spectral range from 3 to 1300 μm using the DUSTY code. The best-fit model, based on the chi-square test, indicates that the condensation is a shell with an outer temperature of T out ≈ 12 K and an inner boundary temperature of T i ≈ 500 K. The shell’s outer radius is r o = 86.2 pc, and the inner cavity radius is r i = 0.082 pc. The condensation produces an extinction A V = 50 mag, and its luminosity is L c = 1.08 × 1034 W, which would correspond to a burst of massive star formation approximately similar to the central 5 pc of R 136 in the LMC and NGC 3603, the ionizing cluster of a giant Carina arm H ii region. The comparison with normal, luminous, and ultraluminous IR galaxies leads us to consider this obscured nucleus as the nearest and weakest object of this category.

A Gamma-Ray Flare from TXS 1508+572: Characterizing the Jet of a z = 4.31 Blazar in the Early Universe

Blazars can be detected from very large distances due to their high luminosity. However, the detection of γ-ray emission of blazars beyond z = 3 has only been confirmed for a small number of sources. Such observations probe the growth of supermassive black holes close to the peak of star formation in the history of galaxy evolution. As a result from a continuous monitoring of a sample of 80 z > 3 blazars with the Fermi Large Area Telescope (Fermi-LAT), we present the first detection of a γ-ray flare from the z = 4.31 blazar TXS 1508+572. This source showed high γ-ray activity from 2022 February to August, reaching a peak luminosity comparable to the most luminous flares ever detected with Fermi-LAT. We conducted a multiwavelength observing campaign involving XMM-Newton, the Neil Gehrels Swift Observatory, the Effelsberg 100 m radio telescope, and the Very Long Baseline Array. In addition, we make use of the monitoring programs by the Zwicky Transient Facility and the Near-Earth Object Wide-field Infrared Survey Explorer at optical and infrared wavelengths, respectively. We find that the source is particularly variable in the infrared band on daily timescales. The spectral energy distribution collected during our campaign is well described by a one-zone leptonic model, with the γ-ray flare originating from an increase of external Compton emission as a result of a fresh injection of accelerated electrons.

A Census of the β Pic Moving Group and Other Nearby Associations with Gaia* * Based on observations made with the Gaia mission, the Two Micron All Sky Survey, the Wide-field Infrared Survey Explorer, the NASA Infrared Telescope Facility, Cerro Tololo Inter-American Observatory, the Southern Astrophysical Research Telescope, Gemini Observatory, the Spitzer Space Telescope, and the eROSITA instrument on the

I have used the third data release of the Gaia mission to improve the reliability and completeness of membership samples in the β Pic moving group (BPMG) and other nearby associations with ages of 20–50 Myr (Sco Body, Carina, Columba, χ 1 For, Tuc-Hor, IC 2602, IC 2391, NGC 2547). I find that Carina, Columba, and χ 1 For are physically related and coeval, and that Carina is the closest fringe of a much larger association. Similarly, Tuc-Hor and IC 2602 form a coeval population that is spatially and kinematically continuous. Both results agree with hypotheses from Gagné et al. I have used the new catalogs to study the associations in terms of their initial mass functions, X-ray emission, ages, and circumstellar disks. For instance, using the model for Li depletion from Jeffries et al., I have derived an age of 24.7−0.6+0.9 Myr for BPMG, which is similar to estimates from previous studies. In addition, I have used infrared photometry from the Wide-field Infrared Survey Explorer to check for excess emission from circumstellar disks among the members of the associations, which has resulted in a dramatic increase in the number of known disks around M stars at ages of 30–50 Myr and a significant improvement in measurements of excess fractions for those spectral types and ages. Most notably, I find that the W3 excess fraction for M0–M6 initially declines with age to a minimum in BPMG (<0.015), increases to a maximum in Carina/Columba/χ 1 For ( 0.041−0.007+0.009 , 34 Myr), and declines again in the oldest two associations (40–50 Myr). The origin of that peak and the nature of the M dwarf disks at >20 Myr are unclear.

A Data-driven Search For Mid-infrared Excesses Among Five Million Main-sequence FGK Stars

Stellar infrared excesses can indicate various phenomena of interest, from protoplanetary disks to debris disks, or (more speculatively) techno-signatures along the lines of Dyson spheres. In this paper, we conduct a large search for “extreme” infrared excesses, designed as a data-driven contextual anomaly detection pipeline. We focus our search on FGK stars close to the main sequence to favor nonyoung host stars. We look for excess in the mid-infrared, unlocking a large sample to search in while favoring extreme IR excess akin to the ones produced by extreme debris disks (EDDs) and/or planetary collision events. We combine observations from ESA Gaia Data Release 3, the Two Micron All-Sky Survey, and the unWISE version of NASA’s Wide-field Infrared Survey Explorer (WISE), and create a catalog of 4,898,812 stars with G < 16 mag. We consider a star to have an excess if it is substantially brighter in the W1 and W2 bands than what is predicted from an ensemble of machine learning models trained on the data, taking optical and near-infrared information as input features. We apply a set of additional cuts (derived from the machine learning models and the objects’ astronomical features) to avoid false positives and identify a set of 53 objects, including one previously identified EDD candidate. The typical infrared-excess fractional luminosities we find are in the range 0.005–0.1, consistent with previous EDD candidates and potential planetary collision events.

CO spectra of the ISM in the Host Galaxies of the most luminous WISE-selected AGNs

Abstract We present observations of mid-J (J = 4–3 or J = 5–4) carbon monoxide (CO) emission lines and continuum emission from a sample of ten of the most luminous (Lbol ≥ 1014 L$\rm \odot$) Hot Dust-Obscured Galaxies (Hot DOGs) discovered by the Wide-field Infrared Survey Explorer (WISE) with redshifts up to 4.6. We uncover broad spectral lines (FWHM ≥ 400 km s−1) in these objects, suggesting a turbulent molecular interstellar medium (ISM) may be ubiquitous in Hot DOGs. A halo of molecular gas, extending out to a radius of 5 kpc is observed in W2305–0039, likely supplied by 940 km s−1 molecular outflows. W0831+0140 is plausibly the host of a merger between at least two galaxies, consistent with observations made using ionized gas. These CO(4–3) observations contrast with previous CO(1–0) studies of the same sources: the CO(4–3) to CO(1–0) luminosity ratios exceed 300 in each source, suggesting that the lowest excited states of CO are underluminous. These findings show that the molecular gas in Hot DOGs is consistently turbulent, plausibly a consequence of AGN feedback, triggered by galactic mergers.

A Comprehensive Study on the Mid-Infrared Variability of Blazars

We present a comprehensive investigation of mid-infrared (MIR) flux variability at 3.4 μm (W1 band) for a large sample of 3816 blazars, using Wide-field Infrared Survey Explorer (WISE) data through December 2022. The sample consists of 1740 flat-spectrum radio quasars (FSRQs), 1281 BL Lac objects (BL Lacs), and 795 blazars of uncertain type (BCUs). Considering Fermi Large Area Telescope detection, we classify 2331 as Fermi blazars and 1485 as non-Fermi blazars. Additionally, based on synchrotron peak frequency, the sample includes 2264 low-synchrotron peaked (LSP), 512 intermediate-synchrotron peaked (ISP), and 655 high-synchrotron peaked (HSP) sources. We conduct a comparative analysis of short- and long-term intrinsic variability amplitude (σm), duty cycle (DC), and ensemble structure function (ESF) across blazar subclasses. The median short-term σm values were 0.181−0.106+0.153, 0.104−0.054+0.101, 0.135−0.076+0.154, 0.173−0.097+0.158, 0.177−0.100+0.156, 0.096−0.050+0.109, and 0.106−0.058+0.100 mag for FSRQs, BL Lacs, Fermi blazars, non-Fermi blazars, LSPs, ISPs, and HSPs, respectively. The median DC values were 71.03−22.48+14.17, 64.02−22.86+16.97, 68.96−25.52+15.66, 69.40−22.17+14.42, 71.24−21.36+14.25, 63.03−33.19+16.93, and 64.63−24.26+15.88 percent for the same subclasses. The median long-term σm values were 0.137−0.105+0.408, 0.171−0.132+0.206, 0.282−0.184+0.332, 0.071−0.062+0.143, 0.218−0.174+0.386, 0.173−0.132+0.208, and 0.101−0.077+0.161 mag for the same subclasses, respectively. Our results reveal significant differences in 3.4 μm flux variability among these subclasses. FSRQs (LSPs) exhibit larger σm and DC values compared to BL Lacs (ISPs and HSPs). Fermi blazars display higher long-term σm but lower short-term σm relative to non-Fermi blazars, while DC distributions between the two groups are similar. ESF analysis further confirms the greater variability of FSRQs, LSPs, and Fermi blazars across a wide range of time scales compared to BL Lacs, ISPs/HSPs, and non-Fermi blazars. These findings highlight a close correlation between MIR variability and blazar properties, providing valuable insights into the underlying physical mechanisms responsible for their emission.

On the Correlation between Young Massive Star Clusters and Gamma-Ray Unassociated Sources

Star clusters (SCs) are potential cosmic-ray accelerators and therefore are expected to emit high-energy radiation. However, a clear detection of gamma-ray emission from this source class has only been possible for a handful of cases. This could in principle result from two different reasons: either detectable SCs are limited to a small fraction of the total number of Galactic SCs, or gamma-ray-emitting SCs are not recognized as such and therefore are listed in the ensemble of unidentified sources. In this Letter we investigate this latter scenario by comparing available catalogs of SCs and H ii regions, obtained from Gaia and Wide-field Infrared Survey Explorer observations, to the gamma-ray GeV and TeV catalogs built from Fermi Large Area Telescope (LAT), H.E.S.S., and LHAASO data. The significance of the correlation between catalogs is evaluated by comparing the results with simulations of synthetic populations. A strong correlation emerges between Fermi-LAT-unidentified sources and H ii regions that trace massive SCs in the earliest (≲1–2 Myr) phase of their life, where no supernova explosions have happened yet, confirming that winds of massive stars can alone accelerate particles and produce gamma-ray emission at least up to GeV energies. The association with TeV energy sources is less evident. Similarly, no significant association is found between Gaia SCs and GeV nor TeV sources. We ascribe this fact to the larger extension of these objects but also to an intrinsic bias in the Gaia selection toward SCs surrounded by a lower target gas density, which would otherwise hinder the detection in the optical wave band.

Lyα Imaging around the Hyperluminous Dust-obscured Quasar W2246–0526 at z = 4.6

Hot dust-obscured galaxies (hot DOGs) are a population of hyperluminous, heavily obscured quasars discovered by the Wide-field Infrared Survey Explorer all-sky survey at high redshift. Observations suggested the growth of these galaxies may be driven by mergers. Previous environmental studies have statistically shown hot DOGs may reside in dense regions. Here we use the Very Large Telescope narrowband and broadband imaging to search for Lyα emitters (LAEs) in the 6.′8×6.′8 field of the hot DOG W2246−0526 at z = 4.6. W2246−0526 is the most distant hot DOG. We find that there is an overdensity of LAEs in the W2246−0526 field compared with the blank fields. This is direct evidence that this most distant hot DOG is in an overdense environment on the Mpc scale, and the result relates to the merger origin of hot DOGs.

The Nearly Universal Disk Galaxy Rotation Curve

The universal rotation curve (URC) of disk galaxies was originally proposed to predict the shape and amplitude of any rotation curve (RC) based solely on photometric data. Here, the URC is investigated with an extensive set of spatially resolved RCs drawn from the PROBES-I, PROBES-II, and MaNGA databases with matching multiband surface brightness profiles from the DESI-LIS and Wide-Field Infrared Survey Explorer surveys for 3846 disk galaxies. Common URC formulations fail to achieve an adequate level of accuracy to qualify as truly universal over fully sampled RCs. We develop neural network (NN) equivalents for the proposed URCs that predict RCs with higher accuracy, showing that URC inaccuracies are not due to insufficient data but rather nonoptimal formulations or sampling effects. This conclusion remains even if the total RC sample is pruned for symmetry. The latest URC prescriptions and their NN equivalents trained on our subsample of 579 disk galaxies with symmetric RCs perform similarly to the URC/NN trained on the complete data sample. We conclude that a URC with an acceptable level of accuracy (ΔV circ ≲ 15%) at all radii would require a detailed modeling of a galaxy’s central regions and outskirts (e.g., for baryonic effects leading to contraction or expansion of any dark-matter-only halo).

An Empirical Extinction Curve Revealed by Gaia XP Spectra and LAMOST

We present a direct measurement of extinction curves using corrected Gaia XP spectra of the common sources in Gaia DR3 and LAMOST DR7. Our analysis of approximately 370,000 high-quality samples yielded a high-precision average extinction curve for the Milky Way. After incorporating infrared photometric data from Two Micron All Sky Survey and Wide-field Infrared Survey Explorer, the extinction curve spans wavelengths from 0.336 to 4.6 μm. We determine an average R 55 of 2.730 ± 0.007, corresponding to R V = 3.073 ± 0.009, and a near-infrared power-law index α of 1.935 ± 0.037. Our study confirmed some intermediate-scale structures within the optical range. One new feature was identified at 540 nm, and its intensity exhibited a correlation with extinction. This extinction curve can be used to investigate the characteristics of dust and enhance the extinction correction of Milky Way stars. A Python package for this extinction curve is available.

Black Hole Mass and Eddington Ratio Distribution of Hot Dust-obscured Galaxies

Hot dust-obscured galaxies (Hot DOGs) are a rare population of hyperluminous infrared galaxies discovered by the Wide-field Infrared Survey Explorer mission. Despite the significant obscuration of the active galactic nucleus (AGN) by dust in these systems, pronounced broad and blueshifted emission lines are often observed. Previous work has shown that eight Hot DOGs, referred to as blue-excess Hot DOGs (BHDs), present a blue excess consistent with type 1 quasar emission in their UV–optical spectral energy distributions (SEDs), which has been shown to originate from the light of the obscured central engine scattered into the line of sight. We present an analysis of the rest-frame optical emission characteristics for 172 Hot DOGs through UV–mid-IR SED modeling and spectroscopic details, with a particular focus on the identification of BHDs. We find that while the optical emission observed in Hot DOGs is in most cases dominated by a young stellar population, 26% of Hot DOGs show a significant enough blue excess emission to be classified as BHDs. Based on their broad C iv and Mg ii lines, we find that the mass of the black hole M BH in a BHD ranges from 108.7 to 1010 M ⊙. When using the same emission lines in regular Hot DOGs, we find the M BH estimates cover the entire range found for BHDs while also extending to somewhat lower values. This agreement may imply that the broad lines in regular Hot DOGs also originate from scattered light from the central engine, just as in BHDs, although a more detailed study would be needed to rule out an outflow-driven nature. Similar to z ∼ 6 quasars, we find that Hot DOGs sit above the local relation between stellar and black hole masses, suggesting either that AGN feedback has not yet significantly suppressed the stellar mass growth in the host galaxies or that they will be outliers of the relation when reaching z = 0.