Early Data Release Research Articles

Semi-supervised spectral classification of DESI white dwarfs by dimensionality reduction

Abstract As a new generation of large-sky spectroscopic surveys comes online, the enormous data volume poses unprecedented challenges in classifying spectra. Modern unsupervised techniques have the power to group spectra based on their dominant features, circumventing the complete reliance on training data suffered by supervised methods. We outline the use of dimensionality reduction to generate a 2D map of the structure of an intermediate-resolution spectroscopic dataset. This technique efficiently separates white dwarfs of different spectral classes in the Dark Energy Spectroscopic Instrument’s Early Data Release (DESI EDR), identifying spectral features that had been missed even by visual classification. By focusing the method on particular spectral regions, we identify white dwarfs with helium features at 90percnt recall, and cataclysmic variables at 100percnt recall, illustrating rapid selection of low-contamination samples from spectroscopic surveys. We also demonstrate the use of dimensionality reduction in a supervised manner, outlining a procedure to classify any white dwarf spectrum in comparison with those in the DESI EDR. With upcoming surveys promising tens of millions of spectra, our work highlights the potential for semi-supervised techniques as an efficient means of classification and dataset visualisation.

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.

Surviving the waves: evidence for a dark matter cusp in the tidally disrupting Small Magellanic Cloud

ABSTRACT We use spectroscopic data for ${\sim }6000$ red giant branch stars in the Small Magellanic Cloud (SMC), together with proper motion data from Gaia Early Data Release 3, to build a mass model of the SMC. We test our Jeans mass modelling method (binulator + gravsphere) on mock data for an SMC-like dwarf undergoing severe tidal disruption, showing that we are able to successfully remove tidally unbound interlopers, recovering the dark matter density and stellar velocity anisotropy profiles within our 95 per cent confidence intervals. We then apply our method to real SMC data, finding that the stars of the cleaned sample are isotropic at all radii (at 95 per cent confidence) and that the inner dark matter density profile is dense, $\rho _{\rm DM}(150\ {\rm pc}) = 1.58_{-0.58}^{+0.80}\times 10^8 \ {\rm M}_{\odot }\, \rm kpc^{-3}$, consistent with a $\Lambda$ cold dark matter cusp. Our model gives a new estimate of the SMC’s total mass within 3 kpc $(M_{\rm tot} \le 3\ {\rm kpc})$ of $2.29\pm 0.46 \times 10^9 \ {\rm M}_{\odot }$. We also derive an astrophysical ‘J-factor’ of $18.99\pm 0.16$ GeV$^2$ cm$^{-5}$ and a ‘D-factor’ of $18.73\pm 0.04$ GeV$^2$ cm$^{-5}$, making the SMC a promising target for dark matter annihilation and decay searches. Finally, we combine our findings with literature measurements to test models in which dark matter is ‘heated up’ by baryonic effects. We find good qualitative agreement with the Di Cintio et al. model but we deviate from the Lazar et al. model at high $M_*/M_{200} &amp;gt; 10^{-2}$. We provide a new, analytical, density profile that reproduces dark matter heating behaviour over the range $10^{-4} &amp;lt; M_*/M_{200} &amp;lt; 10^{-1}$.

J-PLUS: Bayesian object classification with a strum of BANNJOS

With its 12 optical filters, the Javalambre-Photometric Local Universe Survey (J-PLUS) provides an unprecedented multicolor view of the local Universe. The third data release (DR3) covers 3,192 deg$^2$ and contains 47.4 million objects. However, the classification algorithms currently implemented in the J-PLUS pipeline are deterministic and based solely on the morphology of the sources. Our goal is to classify the sources identified in the J-PLUS DR3 images as stars, quasi-stellar objects (QSOs), or galaxies. For this task, we present a machine learning pipeline that utilizes Bayesian neural networks to provide the full probability distribution function (PDF) of the classification. has been trained on photometric, astrometric, and morphological data from J-PLUS DR3 DR3, and using over 1.2 million objects with spectroscopic classification from DR18 DR9, the Early Data Release, and DR3. Results were validated on a test set of about $1.4 10^5$ objects and cross-checked against theoretical model predictions. outperforms all previous classifiers in terms of accuracy, precision, and completeness across the entire magnitude range. It delivers over $95&lt;!PCT!&gt;$ accuracy for objects brighter than $r = 21.5$ mag and $ 90&lt;!PCT!&gt;$ accuracy for those up to $r = 22$ mag, where J-PLUS completeness is $ 25&lt;!PCT!&gt;$. is also the first object classifier to provide the full PDF of the classification, enabling precise object selection for high purity or completeness, and for identifying objects with complex features, such as active galactic nuclei with resolved host galaxies. effectively classified J-PLUS sources into around 20 million galaxies, one million QSOs, and 26 million stars, with full PDFs for each, which allow for later refinement of the sample. The upcoming J-PAS survey, with its 56 color bands, will further enhance 's ability to detail the nature of each source.

Galactic-Seismology Substructures and Streams Hunter with LAMOST and Gaia. I. Methodology and Local Halo Results

We present a novel, deep-learning-based method—dubbed Galactic-Seismology Substructures and Streams Hunter, or GS3 Hunter for short—to search for substructures and streams in stellar kinematics data. GS3 Hunter relies on a combined application of Siamese neural networks to transform the phase space information and the K-means algorithm for the clustering. As a validation test, we apply GS3 Hunter to a subset of the Feedback in Realistic Environments (FIRE) cosmological simulations. The stellar streams and substructures thus identified are in good agreement with corresponding results reported earlier by the FIRE team. In the same vein, we apply our method to a subset of local halo stars from the Gaia Early Data Release 3 and GALAH DR3 data sets and recover several previously known dynamical groups, such as Thamnos 1+2, the hot thick disk, ED-1, L-RL3, Helmi 1+2, Gaia-Sausage-Enceladus, Sequoia, Virgo Radial Merger, Cronus, and Nereus. Finally, we apply our method without fine-tuning to a subset of K giant stars located in the inner halo region, obtained from the LAMOST Data Release 5 data set. We recover three previously known structures (Sagittarius, Hercules-Aquila Cloud, and the Virgo Overdensity), but we also discover a number of new substructures. We anticipate that GS3 Hunter will become a useful tool for the community dedicated to the search for stellar streams and structures in the Milky Way (MW) and the Local Group, thus helping advance our understanding of the stellar inner and outer halos and the assembly and tidal stripping history in and around the MW.

A spectroscopic and kinematic survey of fast hot subdwarfs

Hot subdwarfs (sdO/B) are the stripped helium cores of red giants formed via binary interactions. Close hot subdwarf binaries with massive white dwarf companions have been proposed as possible progenitors of thermonuclear supernovae type Ia (SN Ia). If the supernova is triggered by stable mass transfer from the helium star, the companion should survive the explosion and should be accelerated to high velocities. The hypervelocity star US 708 is regarded as the prototype for such an ejected companion. To find more of those objects we conducted an extensive spectroscopic survey. Candidates for such fast stars have been selected from the spectroscopic database of the Sloan Digital Sky Survey (SDSS) and several ground-based proper-motion surveys. Follow-up spectroscopy has been obtained with several 4m- to 10m-class telescopes. Combining the results from quantitative spectroscopic analyses with space-based astrometry from Gaia Early Data Release 3 (EDR3) we determined the atmospheric and kinematic parameters of 53 fast hot subdwarf stars. None of these stars is unbound to the Galaxy, although some have Galactic restframe velocities close to the Galactic escape velocity. 21 stars are apparently single objects, that crossed the Galactic disc within their lifetimes in the sdO/B stage and could be regarded as potential candidates for the SN Ia ejection scenario. However, the properties of the full sample are more consistent with a pure old Galactic halo population. We therefore conclude that the fast sdO/B stars we found are likely to be extreme halo stars.

Probing dark energy evolution post-DESI 2024

We study the evidence for dark energy (DE) evolution at low redshift, using baryonic acoustic oscillations (BAOs) from the DESI Early Data Release, Pantheon+ Type Ia supernovae (SNe-Ia), and redshift space distortions (RSDs) to constrain cosmological parameters. Furthermore, we make use of the angular acoustic scale to analyse the effect of introducing condensed CMB information on the cosmological parameters informing DE evolution. The analysis is divided into cases based on the variability of priors inferred from early-time physics. Using a quadratic parametrisation, X(z), for DE density, we find evidence for DE evolution in all cases, both with and without the angular acoustic scale. We reconstruct X(z) using best fit parameters and find that DE density starts to exhibit dynamical behaviour at z∼0.5, assuming negative values beyond z∼1.5. The data show no significant preference for X(z)CDM over a ΛCDM, with both models performing equally well according to our chosen metrics of reduced χ2 and the Durbin–Watson statistic.

Characterizing chemical abundance ratios in extremely metal-poor star-forming galaxies in DESI EDR

We present a search for galaxies in the local Universe with extremely low oxygen abundance, that is, more than 25 times lower than solar, which corresponds to 12 + log(O/H) &lt; 7.3. To determine the oxygen abundance, we apply the direct Te method for objects where the [O III]λ4363 line is detected. We identified 21 extremely metal-poor galaxies in the early data release of the Dark Energy Spectroscopic Instrument (DESI EDR), for some of which we also derived N/O, Ne/O, Ar/O, and S/O ratios. We find that many DESI galaxies with extremely low oxygen abundance exhibit a higher N/O ratio in comparison to the reference low-metallicity sample collected from the literature. We suggest that the elevation in N/O ratio may be explained by a contamination with metal-rich gas caused by gas inflow or a merger event. Moreover, contrary to some recent studies, we find that Ar/O and S/O ratios are enhanced as well, while the Ne/O ratio does not show such elevation. One of the galaxies, J0713+5608, has a remarkably low oxygen abundance of 6.978 ± 0.095 dex. This measurement aligns with the lowest known oxygen abundances in galaxies to date. Given the relatively high uncertainty, this galaxy may have the lowest oxygen abundance ever found. Additionally, J0713+5608 exhibited an enhanced N/O ratio compared to the typical N/O ratio observed in metal-poor galaxies within the local Universe.

The DESI Early Data Release white dwarf catalogue

Abstract The Early Data Release (EDR) of the Dark Energy Spectroscopic Instrument (DESI) comprises spectroscopy obtained from 2020 December 14 to 2021 June 10. White dwarfs were targeted by DESI both as calibration sources and as science targets and were selected based on Gaia photometry and astrometry. Here we present the DESI EDR white dwarf catalogue, which includes 2706 spectroscopically confirmed white dwarfs of which approximately 60 percnt have been spectroscopically observed for the first time, as well as 66 white dwarf binary systems. We provide spectral classifications for all white dwarfs, and discuss their distribution within the Gaia Hertzsprung–Russell diagram. We provide atmospheric parameters derived from spectroscopic and photometric fits for white dwarfs with pure hydrogen or helium photospheres, a mixture of those two, and white dwarfs displaying carbon features in their spectra. We also discuss the less abundant systems in the sample, such as those with magnetic fields, and cataclysmic variables. The DESI EDR white dwarf sample is significantly less biased than the sample observed by the Sloan Digital Sky Survey, which is skewed to bluer and therefore hotter white dwarfs, making DESI more complete and suitable for performing statistical studies of white dwarfs.

Optical polarimetry study of the Lambda-Orionis star-forming region

We present an optical polarimetry study of the nearby star-forming region Lambda-Orionis to map the plane-of-the-sky magnetic field geometry to understand the magnetized evolution of the HII region and the associated small molecular clouds. We made multiwavelength polarization observations of 34 bright stars distributed across the region. We also present the R-band polarization measurements that focused on the small molecular clouds, bright-rimmed clouds (BRC), BRC 17, and BRC 18, which are located at the periphery of the HII region. The magnetic field lines exhibit a large-scale ordered orientation consistent with the Planck submillimeter polarization measurements. The magnetic field lines in the two BRCs are found to be roughly in north-south directions. However, a larger dispersion is noted in the orientation for BRC 17 compared to BRC 18. Using a structure-function analysis, we estimate the strength of the plane-of-the-sky component of the magnetic field as ∼28 μG for BRC 17 and ∼40 μG for BRC 18. The average dust grain size and the mean value of the total-to-selective extinction ratio (RV) in the HII region are found to be ∼0.51 ± 0.05 μm and ∼2.9 ± 0.3, respectively. The distance of the whole HII region is estimated as ∼392 ± 8 pc by combining astrometry information from Global Astrometric Interferometer for Astrophysics (Gaia) early data release 3 (EDR3) for young stellar objects associated with BRCs and confirmed members of the central cluster Collinder 69.

DESI Early Data Release Milky Way Survey value-added catalogue

ABSTRACT We present the stellar value-added catalogue based on the Dark Energy Spectroscopic Instrument (DESI) Early Data Release. The catalogue contains radial velocity and stellar parameter measurements for $\simeq$ 400 000 unique stars observed during commissioning and survey validation by DESI. These observations were made under conditions similar to the Milky Way Survey (MWS) currently carried out by DESI but also include multiple specially targeted fields, such as those containing well-studied dwarf galaxies and stellar streams. The majority of observed stars have $16\lt r\lt 20$ with a median signal-to-noise ratio in the spectra of $\sim$ 20. In the paper, we describe the structure of the catalogue, give an overview of different target classes observed, as well as provide recipes for selecting clean stellar samples. We validate the catalogue using external high-resolution measurements and show that radial velocities, surface gravities, and iron abundances determined by DESI are accurate to 1 km s−1, 0.3 dex, and $\sim$ 0.15 dex respectively. We also demonstrate possible uses of the catalogue for chemo-dynamical studies of the Milky Way stellar halo and Draco dwarf spheroidal. The value-added catalogue described in this paper is the very first DESI MWS catalogue. The next DESI data release, expected in less than a year, will add the data from the first year of DESI survey operations and will contain approximately 4 million stars, along with significant processing improvements.

Investigating the nature of the 2.4 hr-period eclipsing cataclysmic variable W2 in 47 Tuc

) is a cataclysmic variable (CV) in the Galactic globular cluster 47 Tucanae. Its modulation was discovered within the CATS@BAR project. The source shows all the properties of magnetic CVs, but whether it is a polar or an intermediate polar is still a matter of debate. This paper investigates the spectral and temporal properties of the source, using all archival X-ray data from and Early Data Release, to establish whether the source falls within the category of polars or intermediate polars. We fitted archival spectra with three different models: a power law, a bremsstrahlung and an optically thin thermal plasma. We also explored the temporal properties of the source with searches for pulsations with a power spectral density analysis and a Rayleigh test ($Z_n^2$). displays a mean luminosity of $ over a 20-year span, despite lower values in a few epochs. The source is not detected in the latest observation, taken with in 2022, and we infer an X-ray luminosity $ The source spectral shape does not change over time and can be equally well fitted with each of the three models, with a best-fit photon index of 1.6 for the power law and best-fit temperatures of 10 keV for both the bremsstrahlung and the thermal plasma models. We confirm the previously detected period of 8649 s, ascribed to the binary orbital period, and found a cycle-to-cycle variability associated with this periodicity. No other significant pulsation is detected. Considering the source orbital period, luminosity, spectral characteristics, long-term evolution and strong cycle-to-cycle variability, we suggest that is a magnetic CV of the polar type.

Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne

Stellar abundances for a large number of stars provide key information for the study of Galactic formation history. Large spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI) and LAMOST take median-to-low-resolution (R ≲ 5000) spectra in the full optical wavelength range for millions of stars. However, the line-blending effect in these spectra causes great challenges for elemental abundance determination. Here we employ DD-Payne, a data-driven method regularized by differential spectra from stellar physical models, to the DESI early data release spectra for stellar abundance determination. Our implementation delivers 15 labels, including effective temperature T eff, surface gravity logg , microturbulence velocity v mic, and the abundances for 12 individual elements, namely C, N, O, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, and Ni. Given a spectral signal-to-noise ratio of 100 per pixel, the internal precisions of the label estimates are about 20 K for T eff, 0.05 dex for logg , and 0.05 dex for most elemental abundances. These results agree with the theoretical limits from the Crámer–Rao bound calculation within a factor of 2. The majority of the accreted halo stars contributed by the Gaia–Enceladus–Sausage are discernible from the disk and in situ halo populations in the resultant [Mg/Fe]–[Fe/H] and [Al/Fe]–[Fe/H] abundance spaces. We also provide distance and orbital parameters for the sample stars, which spread over a distance out to ∼100 kpc. The DESI sample has a significantly higher fraction of distant (or metal-poor) stars than the other existing spectroscopic surveys, making it a powerful data set for studying the Galactic outskirts. The catalog is publicly available.

The Early Data Release of the Dark Energy Spectroscopic Instrument

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

Broad absorption line quasars in the Dark Energy Spectroscopic Instrument Early Data Release

ABSTRACT Broad absorption line (BAL) quasars are characterized by gas clouds that absorb flux at the wavelength of common quasar spectral features, although blueshifted by velocities that can exceed $0.1c$. BAL features are interesting as signatures of significant feedback, yet they can also compromise cosmological studies with quasars by distorting the shape of the most prominent quasar emission lines, impacting redshift accuracy and measurements of the matter density distribution traced by the Lyman $\alpha$ forest. We present a catalogue of BAL quasars discovered in the Dark Energy Spectroscopic Instrument (DESI) survey Early Data Release, which were observed as part of DESI Survey Validation, as well as the first two months of the main survey. We describe our method to automatically identify BAL quasars in DESI data, the quantities we measure for each BAL, and investigate the completeness and purity of this method with mock DESI observations. We mask the wavelengths of the BAL features and re-evaluate each BAL quasar redshift, finding new redshifts which are $243\, {\rm km}\, {\rm s}^{-1}$ smaller on average for the BAL quasar sample. These new, more accurate redshifts are important to obtain the best measurements of quasar clustering, especially at small scales. Finally, we present some spectra of rarer classes of BALs that illustrate the potential of DESI data to identify such populations for further study.

A sample of 554 white dwarfs showing infrared excess from Gaia EDR3 and CatWISE catalogs

White dwarfs (WDs) are generally intrinsically faint in the infrared (IR). Excess emission in the infrared results from low-mass companions or dusty material, potentially linked to the on-going accretion of planetary material. This work presents a new catalog of white dwarfs with (candidate) infrared excess. The final sample comes from a cross-match between the Gaia Early Data Release (EDR3) white dwarf candidates, and the CatWISE catalog, with candidate infrared excesses determined considering both magnitude and color excess. A magnitude excess is found to be more reliable than a color excess. The final catalog contains 554 infrared excess candidates (446 are presented for the first time here) from 41,020 white-dwarf candidates with a Gaia magnitude of $G&lt;18.5$ mag. Our infrared excess candidate sample extends to a white-dwarf temperature range of 4500--98000 K and a white-dwarf mass range of 0.1--1.2 \( M We caution that these objects should be treated as infrared excess candidates until confirmed with other methods. We present a three-fold increase in the sample of white dwarfs known to have infrared excesses. Among the sample applications is the study of the accretion of planetary material by white dwarfs and the identification of new white-dwarf-brown-dwarf pairs.

UVIT Study of the MAgellanic Clouds (U-SMAC) – I. Recent star formation history and kinematics of the Shell region in the north-eastern Small Magellanic Cloud

ABSTRACT The interactions between the Magellanic Clouds significantly affect the shape and distribution of the young stellar population, particularly in the periphery of the Small Magellanic Cloud (SMC). We present the first far-UV (FUV) map of the north-east SMC-Shell region using the Ultra Violet Imaging Telescope (UVIT) onboard AstroSat. The detected FUV stars are combined with Gaia Early Data Release 3 data to create a FUV–optical catalogue of ∼14 400 stars. FUV–optical colour-magnitude diagrams are used along with isochrones to estimate the stellar ages. The detected stars are formed in multiple episodes. We identified two episodes of star formation (∼60 and ∼260 Myr ago), where the episode at ∼260 Myr is linked to the recent interaction with the Large Magellanic Cloud (LMC) and the episode at ∼60 Myr is linked to the pericentric passage of the SMC around our Galaxy. The median proper motion (PM) and velocity dispersion are found to be similar to the SMC main body, indicating that this region has not experienced significant tidal effects. The FUV stellar surface density and the dispersion in PM suggest that the extent of the inner SMC in the north-east direction to be around 2.2°. We detect arm-like and arc-like structures in the FUV stellar density map, and their kinematics appear to be similar to the SMC main body. These extended outer features are the spatial stellar overdensities formed over multiple episodes of star formation, but without apparent kinematic distinction.

Detection of open cluster members inside and beyond tidal radius by machine learning methods based on Gaia DR3

ABSTRACT In our previous work, we introduced a method that combines two unsupervised algorithms: Density-based spatial clustering of applications with noise (DBSCAN) and Gaussian mixture model (GMM). We applied this method to 12 open clusters based on Gaia Early Data Release 3 (EDR3) data, demonstrating its effectiveness in identifying reliable cluster members within the tidal radius. However, for studying cluster morphology, we need a method capable of detecting members both inside and outside the tidal radius. By incorporating a supervised algorithm into our approach, we successfully identified members beyond the tidal radius. In our current work, we initially applied DBSCAN and GMM to identify reliable members of cluster stars. Subsequently, we trained the random forest algorithm using DBSCAN- and GMM-selected data. Leveraging the random forest, we can identify cluster members outside the tidal radius and observe cluster morphology across a wide field of view. Our method was then applied to 15 open clusters based on Gaia DR3, which exhibit a wide range of metallicity, distances, members, and ages. Additionally, we calculated the tidal radius for each of the 15 clusters using the King profile and detected stars both inside and outside this radius. Finally, we investigated mass segregation and luminosity distribution within the clusters. Overall, our approach significantly improved the estimation of the tidal radius and detection of mass segregation compared to the previous work. We found that in Collinder 463, low-mass stars do not segregate in comparison to high-mass and intermediate-mass stars. Additionally, we detected a peak of luminosity in the clusters, some of which were located far from the centre, beyond the tidal radius.

Galaxy cluster virial-shock sources in eROSITA catalogs

Context. Virial shocks around galaxy clusters and groups are being mapped, thus tracing accretion onto large-scale structure. Aims. Following the recent identification of discrete ROSAT and radio sources associated with the virial shocks of MCXC clusters and groups, we examined the eROSITA-DE Early Data Release (EDR) to see whether it shows virial-shock X-ray sources within its 140 deg2 field. Methods. EDR catalog sources were stacked and radially binned around EDR catalog clusters and groups. The properties of the excess virial-shock sources were inferred statistically by comparing the virial-shock region to the field. Results. We find an excess of X-ray sources narrowly localized at the 2.0 &lt; r/R500 &lt; 2.25 normalized radii, just inside the anticipated virial shocks, of the resolved 532 clusters, for samples of both extended sources (3σ for 534 sources) and bright sources (3.5σ for 5820 sources; 4σ excluding the low cluster-mass quartile). The excess sources are on average extended (∼100 kpc), luminous (LX ≃ 1043 − 44 erg s−1), and hot (keV scales), consistent with infalling gaseous halos crossing the virial shock. The results agree with the stacked ROSAT–MCXC signal, showing the higher LX expected at EDR redshifts and a possible dependence on host mass. Conclusions. Localized virial-shock spikes in the distributions of discrete radio, X-ray, and possibly also γ-ray sources are new powerful probes of accretion from the cosmic web. We expect that data from future all-sky catalogs will allow us to place strong constraints on virial shock physics.

Searching for Hypercompact Star Clusters in the Milky Way Using LAMOST and Gaia

During the early merger of the Milky Way, intermediate-mass black holes (BHs) in merged dwarf galaxies may have been ejected from the center of their host galaxies due to gravitational waves, carrying some central stars along. This process can lead to the formation of hypercompact star clusters, potentially hosting BHs in the mass range of 104–105 solar masses. These clusters are crucial targets for identifying and investigating intermediate-mass BHs. However, no hypercompact star clusters in the Milky Way have been identified so far. In this paper, taking advantage of the high spatial resolution power of Gaia, we used data from Gaia Early Data Release (EDR) 3 and Large-Area Multi-Object Fiber Optic Spectroscopic Telescope Data Release 7, along with additional data from Pan-STARRS and the Sloan Digital Sky Survey, to conduct an initial screening of 6,138,049 sources using various parameters of Gaia EDR3. A total of 4786 sources were selected for in-depth analysis. Each of these sources was meticulously scrutinized by examining their images, spectra, and nearby celestial objects to exclude various false positives, such as contaminations, galaxies, wide binaries, or wrong matches. We finally identified one likely hypercompact star cluster candidate in the Milky Way, laying the foundation for further high-resolution imaging and spectral verification.