Sky Survey Research Articles

SRG/ all-sky X-ray survey: Catalog of sources detected during the first five surveys

We present an updated catalog of sources detected by the Mikhail Pavlinsky telescope aboard the Spektrum-Roentgen-Gamma (SRG) observatory during its all-sky survey. It is based on the data of the first four and the partially completed fifth scans of the sky ( The catalog comprises 1545 sources detected in the 4--12\,keV energy band. The achieved sensitivity ranges between $ near the ecliptic plane and $ near the ecliptic poles, which is a $ 30$--50<!PCT!> improvement over the previous version of the catalog based on the first two all-sky scans (ARTSS12). There are $ 130$ objects, excluding the expected contribution of spurious detections, that were not known as X-ray sources before the SRG/ all-sky survey. We provide information, partly based on our ongoing follow-up optical spectroscopy program, on the identification and classification of the majority of the sources (1463), of which 173 are tentative at the moment. The majority of the classified objects (964) are extragalactic, a small fraction (30) are located in the Local Group of galaxies, and 469 are Galactic. The dominant classes of objects in the catalog are active galactic nuclei (911) and cataclysmic variables (192).

Estimation of stellar mass and star formation rate based on galaxy images

Abstract It is crucial for a deeper understanding of the formation and evolution of galaxies in the universe to study stellar mass (M*) and star formation rate (SFR). Traditionally, astronomers infer the properties of galaxies from spectra, which are highly informative, but expensive and hard to be obtained. Fortunately, modern sky surveys obtained a vast amount of high spatial-resolution photometric images. The photometric images are obtained relatively economically than spectra, and it is very helpful for related studies if M* and SFR can be estimated from photometric images. Therefore, this paper conducted some preliminary researches and explorations on this regard. We constructed a deep learning model named GalEffNet for estimating integrated M* and specific star formation rate (sSFR) from DESI galaxy images. The GalEffNet primarily consists of a general feature extraction module and a parameter feature extractor. The research results indicate that the proposed GalEffNet exhibits good performance in estimating M* and sSFR, with σ reaching 0.218 dex and 0.410 dex. To further assess the robustness of the network, prediction uncertainty was performed. The results show that our model maintains good consistency within a reasonable bias range. We also compared the performance of various network architectures and further tested the proposed scheme using image sets with various resolutions and wavelength bands. Furthermore, we conducted applicability analysis on galaxies of various sizes, redshifts, and morphological types. The results indicate that our model performs well across galaxies with various characteristics and indicate its potentials of broad applicability.

The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results

We present the final data from the Sloan Digital Sky Survey (SDSS) Reverberation Mapping (RM) project, a precursor to the SDSS-V Black Hole Mapper RM program. This data set includes 11 yr photometric and 7 yr spectroscopic light curves for 849 broad-line quasars over a redshift range of 0.1 < z < 4.5 and a luminosity range of L bol = 1044−47.5 erg s−1, along with spectral and variability measurements. We report 23, 81, 125, and 110 RM lags (relative to optical continuum variability) for broad Hα, Hβ, Mg ii, and C iv using the SDSS-RM sample, spanning much of the luminosity and redshift ranges of the sample. Using 30 low-redshift RM active galactic nuclei with dynamical-modeling black hole masses, we derive a new estimate of the average virial factor of logf=0.62±0.07 for the line dispersion measured from the rms spectrum. The intrinsic scatter of individual virial factors is 0.31 ± 0.07 dex, indicating a factor of 2 systematic uncertainty in RM black hole masses. Our lag measurements reveal significant R–L relations for Hβ and Mg ii at high redshift, consistent with the latest measurements based on heterogeneous samples. While we are unable to robustly constrain the slope of the R–L relation for C iv given the limited dynamic range in luminosity, we found substantially larger scatter in C iv lags at fixed L 1350. Using the SDSS-RM lag sample, we derive improved single-epoch (SE) mass recipes for Hβ, Mg ii, and C iv, which are consistent with their respective RM masses as well as between the SE recipes from two different lines, over the luminosity range probed by our sample. The new Hβ and Mg ii recipes are approximately unbiased estimators at given RM masses, but there are systematic biases in the C iv recipe. The intrinsic scatter of SE masses around RM masses is ∼0.45 dex for Hβ and Mg ii, increasing to ∼0.58 dex for C iv.

CSST Strong-lensing Preparation: A Framework for Detecting Strong Lenses in the Multicolor Imaging Survey by the China Survey Space Telescope (CSST)

Strong gravitational lensing is a powerful tool for investigating dark matter and dark energy properties. With the advent of large-scale sky surveys, we can discover strong-lensing systems on an unprecedented scale, which requires efficient tools to extract them from billions of astronomical objects. The existing mainstream lens-finding tools are based on machine-learning algorithms and applied to cutout-centered galaxies. However, according to the design and survey strategy of optical surveys by the China Space Station Telescope (CSST), preparing cutouts with multiple bands requires considerable efforts. To overcome these challenges, we have developed a framework based on a hierarchical visual transformer with a sliding window technique to search for strong-lensing systems within entire images. Moreover, given that multicolor images of strong-lensing systems can provide insights into their physical characteristics, our framework is specifically crafted to identify strong-lensing systems in images with any number of channels. As evaluated using CSST mock data based on a semianalytic model named CosmoDC2, our framework achieves precision and recall rates of 0.98 and 0.90, respectively. To evaluate the effectiveness of our method in real observations, we have applied it to a subset of images from the DESI Legacy Imaging Surveys and media images from Euclid Early Release Observations. A total of 61 new strong-lensing system candidates are discovered by our method. However, we also identified false positives arising primarily from the simplified galaxy morphology assumptions within the simulation. This underscores the practical limitations of our approach while simultaneously highlighting potential avenues for future improvements.

Efficient identification of broad absorption line quasars using dimensionality reduction and machine learning

Efficient identification of broad absorption line quasars using dimensionality reduction and machine learning

Stellar Classification with Vision Transformer and SDSS Photometric Images

With the development of large-scale sky surveys, an increasing number of stellar photometric images have been obtained. However, most stars lack spectroscopic data, which hinders stellar classification. Vision Transformer (ViT) has shown superior performance in image classification tasks compared to most convolutional neural networks (CNNs). In this study, we propose an stellar classification network based on the Transformer architecture, named stellar-ViT, aiming to efficiently and accurately classify the spectral class for stars when provided with photometric images. By utilizing RGB images synthesized from photometric data provided by the Sloan Digital Sky Survey (SDSS), our model can distinguish the seven main stellar categories: O, B, A, F, G, K, and M. Particularly, our stellar-ViT-gri model, which reaches an accuracy of 0.839, outperforms traditional CNNs and the current state-of-the-art stellar classification network SCNet when processing RGB images synthesized from the gri bands. Furthermore, with the introduction of urz band data, the overall accuracy of the stellar-ViT model reaches 0.863, further demonstrating the importance of additional band information in improving classification performance. Our approach showcases the effectiveness and feasibility of using photometric images and Transformers for stellar classification through simple data augmentation strategies and robustness analysis of training dataset sizes. The stellar-ViT model maintains good performance even in small sample scenarios, and the inclusion of urz band data reduces the likelihood of misclassifying samples as lower-temperature subtypes.

The SRG/eROSITA All-Sky Survey: SRG/eROSITA cross-calibration with Chandra and XMM-Newton using galaxy cluster gas temperatures

Galaxy cluster gas temperatures ($T$) play a crucial role in many cosmological and astrophysical studies. However, it has been shown that $T$ measurements can significantly vary between different X-ray telescopes. These $T$ biases can propagate to several cluster applications in which $T$ can be used, such as measuring hydrostatic cluster masses and constraining the angular variation of cosmological parameters. Thus, it is important to accurately cross-calibrate X-ray instruments to account for systematic biases. In this work, we present the cross-calibration between Spectrum Roentgen Gamma/eROSITA (SRG/eROSITA) and Chandra /ACIS and between SRG/eROSITA and XMM-Newton /EPIC using for the first time a large sample of galaxy cluster $T$. To do so, we used the first eROSITA All-Sky Survey data and the preliminary extremely expanded HIgh FLUx Galaxy Cluster Sample, a large X-ray flux-limited cluster catalog. We spectroscopically measured X-ray $T$ for 186 independent cluster regions with both SRG/eROSITA and Chandra /ACIS in a self-consistent way for three energy bands: 0.7-7 keV (full), 0.5-4 keV (soft), and 1.5-7 keV (hard). We did the same with SRG/eROSITA and XMM-Newton /EPIC for 71 different cluster regions and all three bands. We find that SRG/eROSITA measures systematically lower $T$ than the other two instruments, with hotter clusters deviating more than cooler ones. For the full band, SRG/eROSITA returns 20$&lt;!PCT!&gt;$ and 14$&lt;!PCT!&gt;$ lower $T$ than Chandra /ACIS and XMM-Newton /EPIC, respectively, when the two other instruments each measure $k_ B T 3$ keV. The discrepancy respectively increases to 38&lt;!PCT!&gt; and 32&lt;!PCT!&gt; when Chandra /ACIS and XMM-Newton /EPIC each measure $k_ B T 10$ keV. On the other hand, the discrepancy becomes milder for low-$T$ galaxy groups. Moreover, a broken power law fit demonstrated that there is a break at the SRG/eROSITA- Chandra /ACIS scaling relation at $k_ B T 1.7-2.7$ keV, depending on the energy band. The soft band shows a marginally lower discrepancy compared to the full band. In the hard band, the cross-calibration of SRG/eROSITA and the other instruments show very strong differences. We tested several possible systematic biases (such as multiphase cluster gas, Galactic absorption, non-Gaussian scatter, and selection effects) to identify the reason behind the cross-calibration discrepancies, but none could significantly alleviate the tension. For now, it is most likely that the systematically lower SRG/eROSITA $T$ can be attributed to systematic effective area calibration uncertainties; however, the exact role of multiphase cluster gas in the observed $T$ discrepancies needs to be further investigated. Furthermore, we provide conversion factors between SRG/eROSITA Chandra /ACIS, and XMM-Newton /EPIC $T$ that will be beneficial for future cluster studies that combine SRG/eROSITA $T$ with data from other X-ray instruments. Finally, we also provide conversion functions between the official eRASS1 cluster catalog $T$ and the equivalent core and core-excised Chandra /ACIS and XMM-Newton /EPIC $T$.

Cosmic dipoles of active galactic nuclei at optical and radio wavelengths display much larger amplitudes than the cosmic microwave background dipole

Abstract Sky distributions of large samples of distant active galactic nuclei (AGNs) have shown dipoles significantly larger than the cosmic microwave background (CMB) dipole. However, a recent Bayesian analysis of the QUAIA sample, comprising 1.3 million quasars, has yielded a dipole that seems to be in tandem with the CMB dipole, in contravention of most previous studies of AGN dipoles. Since the question has large cosmological implications, we investigate the QUAIA quasar sample afresh, by directly computing the dipole from asymmetries observed in the source number counts. We instead find a dipole 3-4 times as large as the CMB dipole though in the same direction. Further, it has been claimed elsewhere that the difference between the CMB dipole and the radio dipole estimated from the NRAO VLA Sky Survey (NVSS), the first large catalogue that showed an AGN dipole about four times larger than the CMB dipole, can be fully accounted for by incorporating the shot-noise and clustering contributions to the total NVSS dipole. A careful reinvestigation of the NVSS dipole, however, shows that the random phenomena like shot noise or clustering cannot account for the actually observed NVSS asymmetries, which show a systematic dipole pattern over the sky.

Classification of Astronomical Spectra Based on Multiscale Partial Convolution

The automated and efficient classification of astronomical spectra is an important research issue in the era of large sky surveys. Most current studies on automatic spectral classification primarily focus on specific data sets and demonstrate outstanding performance. However, the diversity in spectra poses formidable challenges for these classification models, as they exhibit limited capability to generalize across more comprehensive data sets. In response to these challenges, we pioneer a method called the multiscale partial convolution net (MSPC-Net), which amalgamates partial, large kernel, and grouped convolution to facilitate multilabel spectral classification. By harnessing the capabilities of partial convolution, MSPC-Net can effectively reduce the number of model parameters, accelerate the training process, and mitigate the overfitting issue. Integrating large kernel and grouped convolution empowers the model to capture local and global features simultaneously, enhancing its overall classification efficacy. To rigorously evaluate the model’s performance, we generate ten different data sets sourced from the Sloan Digital Sky Survey and Large Sky Area Multi-Object Spectroscopic Telescope. These data sets encompass stellar class, stellar subclass, and full classification, providing a comprehensive assessment across various application scenarios. The experimental results reveal that MSPC-Net consistently outperforms the other models across different data sets, especially demonstrating superior performance in the last two data sets with full classification. Consequently, MSPC-Net is poised to find extensive applications in the detailed classification for large-scale sky survey projects. This work not only addresses the challenges of generalization in spectral classification but also contributes significantly to the advancement of robust models for astronomical research.

Massive compact quiescent galaxies in the M⋆ versus σe plane: insights from stellar population properties

ABSTRACT We investigated the stellar population properties of a sample of 1858 massive compact galaxies (MCGs) extracted from the Sloan Digital Sky Survey (SDSS). Motivated by previous results showing that older compact galaxies tend to have larger velocity dispersion at fixed stellar mass, we used the distance to the σe versus Re and M⋆ versus σe relations as selection criteria. We found that MCGs are old (≳10 Gyr), α-enhanced ([α/Fe] ∼ 0.2), and have solar to supersolar stellar metallicities. Metallicity increases with σe, while age and [α/Fe] do not vary significantly. Moreover, at fixed σe, metallicity and stellar mass are correlated. Compared with a control sample of typical quiescent galaxies, MCGs have, on average, lower metallicities than control sample galaxies (CSGs) of similar σe. For σe ≲ 225 km s−1, MCGs are older and more α-enhanced than CSGs, while for higher σe ages and α-enhancement are similar. The differences in age and α-enhancement can be explained by lower σe CSGs being an amalgam of quiescent galaxies with a variety of ages. The origin of the differences in metallicity, however, is not clear. Lastly, we compared the stellar mass within the region probed by the SDSS fibre finding that, at fixed fibre velocity dispersion, MCGs have lower stellar masses on average. Since the velocity dispersion is a tracer of the dynamical mass, this raises the possibility that MCGs have, on average, a bottom-heavier initial mass function or a larger dark matter fraction within the inner ∼1−2 kpc.

Multicolour photometry of LEO mega-constellations Starlink and OneWeb

ABSTRACT The development of low earth orbit (LEO) mega-constellation fundamentally threatens ground-based optical astronomical observations. To study the photometric properties of the LEO mega-constellations, we used the Xinglong 50 cm telescope to conduct a large-sample, high-precision, and multicolour target-tracking photometry of two typical LEO mega-constellations: Starlink and OneWeb. Over a three-month observation period starting on 2022 January 1, we collected 1447 light curves of 404 satellites in four typical versions: Starlink v1.0, DarkSat, VisorSat, Starlink v1.5, and OneWeb. According to data statistics, Starlink v1.0 has the smallest median magnitude at clear and Sloan Digital Sky Survey gri band, and OneWeb is the dimmest bus. The brightness of Starlink v1.5 is slightly brighter than VisorSat. We construct a detailed photometric model with solar phase angle variations by calculating the illumination-visibility geometry based on the orbital parameters. Our data analysis shows that the solar phase angle is the significant characteristic which influencing Starlink satellites’ brightness, but it is not sensitive to OneWeb satellites. VisorSat and Starlink v1.5 versions, which are equipped with deployable visors, have significantly reduced scattered light compared to the previous Starlink v1.0 version. The multiband LOWESS and colour index are analysed in characterizing the energy and colour features of LEO mega-constellation satellites. This work found that the proportion of scattered sunlight mitigation achieved with VisorSat and Starlink v1.5 was 55.1 and 40.4 per cent, respectively. The colour index of different buses shows an evident clustering feature. Our observation and analysis could provide valuable quantitative data and photometric models, which can contribute to assessing the impact of LEO mega-constellations on astronomical observations.

SALT-RSS Multiobject Spectroscopic Data Reduction to Reveal Physical Properties of [O ii]-emitting Galaxies from HETDEX and ODIN

Line flux ratios from [O ii] doublets can probe electron densities in the interstellar medium of galaxies. We employ the Southern African Large Telescope’s (SALT) Robert Stobie Spectrograph (RSS), which provides sufficient resolution (R ∼ 3000) to split the [O ii] doublets, to target galaxies from Hobby-Eberly Telescope Dark Energy Experiment and One-hundred-deg2 DECam Imaging in Narrowbands with emission line fluxes of at least 2 × 10−16 erg cm−2 s−1. Reduction is carried out using RSSMOSPipeline to reduce SALT-RSS data through wavelength calibration. Despite SALT-RSS being known for its difficulty to flux calibrate, we present spectra that have been flux calibrated using alignment stars with Sloan Digital Sky Survey spectra as standards. We combine multiple spectroscopic settings to obtain full 2D spectra across a wavelength range of 3500–9500 Å. A 1D spectrum can then be extracted to calculate flux ratios and line widths, revealing important physical properties of these bright [O ii]-emitters.

The LOFAR Two-metre Sky Survey: The nature of the faint source population and SFR–radio luminosity relation using prospector

ABSTRACT Spectral energy distribution (SED) fitting has been extensively used to determine the nature of the faint radio source population. Recent efforts have combined fits from multiple SED-fitting codes to account for the host galaxy and any active nucleus that may be present. We show that it is possible to produce similar-quality classifications using a single energy-balance SED fitting code, prospector, to model up to 26 bands of UV–far-infrared aperture-matched photometry for ∼31 000 sources in the ELAIS-N1 field from the LOFAR Two-Metre Sky Survey (LoTSS) deep fields first data release. One of a new generation of SED-fitting codes, prospector accounts for potential contributions from radiative active galactic nuclei (AGN) when estimating galaxy properties, including star formation rates (SFRs) derived using non-parametric star formation histories. Combining this information with radio luminosities, we classify 92 per cent of the radio sources as a star-forming galaxy, high-/low-excitation radio galaxy, or radio-quiet AGN and study the population demographics as a function of 150 MHz flux density, luminosity, SFR, stellar mass, redshift, and apparent r-band magnitude. Finally, we use prospector SED fits to investigate the SFR–150 MHz luminosity relation for a sample of ∼133 000 3.6 μm-selected z &amp;lt; 1 sources, finding that the stellar mass dependence is significantly weaker than previously reported, and may disappear altogether at $\log _{10} (\mathrm{SFR}/M_\odot \, \mathrm{yr}^{-1}) \gt 0.5$. This approach makes it significantly easier to classify radio sources from LoTSS and elsewhere, and may have important implications for future studies of star-forming galaxies at radio wavelengths.

Angular correlation function from sample covariance with BOSS and eBOSS LRG

The Baryon Acoustic Oscillations (BAO) are one of the most used probes to understand the accelerated expansion of the Universe. Traditional methods rely on fiducial model information within their statistical analysis, which may be a problem when constraining different families of models. This work aims to provide a method that constrains θBAO\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta _{BAO}$$\\end{document} through a model-independent approach using the covariance matrix from the galaxy sample from thin redshift bins, later validated with a mock sample covariance matrix. 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BOSS1 and BOSS2 showed agreement with Planck 18 and an agreement with Pantheon + SH0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$H_0$$\\end{document}ES when α~\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ilde{\\alpha }$$\\end{document} is based on the bin z=zeff\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$z=z_{eff}$$\\end{document}.

Project Hephaistos – II. Dyson sphere candidates from Gaia DR3, 2MASS, and WISE

ABSTRACT The search for extraterrestrial intelligence is currently being pursued using multiple techniques and in different wavelength bands. Dyson spheres, megastructures that could be constructed by advanced civilizations to harness the radiation energy of their host stars, represent a potential technosignature, that in principle may be hiding in public data already collected as part of large astronomical surveys. In this study, we present a comprehensive search for partial Dyson spheres by analysing optical and infrared observations from Gaia, 2MASS, and WISE. We develop a pipeline that employs multiple filters to identify potential candidates and reject interlopers in a sample of five million objects, which incorporates a convolutional neural network to help identify confusion in WISE data. Finally, the pipeline identifies seven candidates deserving of further analysis. All of these objects are M-dwarfs, for which astrophysical phenomena cannot easily account for the observed infrared excess emission.

Associating LOFAR Galactic Faraday structures with the warm neutral medium

Faraday tomography observations with the Low Frequency Array (LOFAR) have unveiled a remarkable network of structures in polarized synchrotron emission at high Galactic latitudes. The observed correlation between LOFAR structures, dust polarization, and emission suggests a connection to the neutral interstellar medium (ISM). We investigated this relationship by estimating the rotation measure (RM) of the warm neutral (partially ionized) medium (WNM) in the local ISM. Our work combines UV spectroscopy from FUSE and dust polarization observations from with LOFAR data. We derived electron column densities from UV absorption spectra toward nine background stars, within the field of published data from the LOFAR two-meter sky survey. The associated RMs were estimated using a local magnetic field model fitted to the dust polarization data of A comparison with Faraday spectra at the position of the stars suggests that LOFAR structures delineate a slab of magnetized WNM and synchrotron emission, located ahead of the bulk of the warm ionized medium. This conclusion establishes an astrophysical framework for exploring the link between Faraday structures and the dynamics of the magnetized multiphase ISM. It will be possible to test it on a larger sample of stars when maps from the full northern sky survey of LOFAR become available.

Detecting New Visual Binaries in Gaia DR3 with Gaia and Two Micron All Sky Survey (2MASS) Photometry. II. Speckle Observations of 16 Low-separation Systems

Here we present speckle observations of 16 low-separation (s < 30 au) high-probability candidate binaries from the catalog by Medan et al., where secondaries typically lack astrometric solutions in Gaia. From these speckle observations, we find a second component is always detected within the field of view. To determine if the detection is consistent with a physical companion or a chance alignment with a background source, we utilize a statistic from Tokovinin & Kiyaeva that compares the apparent motion of the systems to the expected orbital motion ( μ′ ). Using simulated binary orbits, we construct likelihood distributions of μ′ assuming various total errors on the measurements. With the hypothesis that the system is a true binary, we show that large measurement errors can result in μ′ values higher than expected for bound systems. Using simulated chance alignments, we also create similar likelihoods to test this alternative hypothesis. By combining likelihoods of both true binaries and chance alignments, we find that 15 of the 16 candidates are physical systems regardless of the level of measurement error. Our findings also accommodate all 16 as physical systems if the average, relative measurement error on the binary separations and position angles is ∼4.3%, which is consistent with our knowledge of the Gaia and Gemini speckle pipelines. Importantly, beyond assessing the likelihood of a true binary versus chance alignment, this quantitative assessment of the true average measurement error will allow more robust error estimates of mass determinations from short separation binaries with Gaia and/or Gemini speckle data.

A catalogue of asteroseismically calibrated ages for APOGEE DR17

Context. The formation history and evolution of the Milky Way through cosmological time is a complex field of research requiring the sampling of highly accurate stellar ages for all Galaxy components. Such highly reliable ages are starting to become available thanks to the synergy of asteroseismology, spectroscopy, stellar modelling, and machine learning analysis in the era of all-sky astronomical surveys. Aims. Our goal is to provide an accurate list of ages for the Main Red Star Sample of the APOGEE DR17 catalogue. In order to reach this goal, ages obtained under asteroseismic constraints are used to train a machine learning model. Methods. As our main objective is to obtain reliable age predictions without the need for asteroseismic parameters, the optimal choice of stellar non-asteroseismic parameters was investigated to obtain the best performances on the test set. The stellar parameters Teff and L, the abundances of [CI/N],[Mg/Ce], and [α/Fe], the U(LSR) velocity, and the vertical height from the Galactic plane ‘Z’ were used to predict ages with a categorical gradient boost decision trees model. The model was trained on two merged samples of the TESS Southern Continuous Viewing Zone and the Second APOKASC catalogue to avoid a data shift and to improve the reliability of the predictions. Finally, the model was tested on an independent data set of the K2 Galactic Archaeology Program. Results. A model with a median fractional age error of 20.8% is obtained. Its prediction variance between the validation and the training set is 4.77%. For stars older than 3 Gyr, the median fractional error in age ranges from 7% to 23%. For stars with ages ranging from 1 to 3 Gyr, the median fractional error in age ranges from 26% to 28%. For stars younger than 1 Gyr, the median fractional error is 43%. The optimised model applies to 125 445 stars from the Main Red Star Sample of the APOGEE DR17 catalogue. Our analysis of the ages confirms previous findings regarding the flaring of the young Galactic disc towards its outer regions. Additionally, we find an age gradient among the youngest stars within the Galactic plane. Finally, we identify two groups of a few metal-poor ([Fe/H] &lt; −1 dex) young stars (Age &lt; 2 Gyr) with similar peculiar chemical abundances and halo kinematics. These are likely the outcomes of the predicted third and latest episode of gas infall in the solar vicinity (~2.7 Gyr ago). Conclusions. We make a catalogue of asteroseismically calibrated ages for 125 445 red giants from the APOGEE DR17 catalogue available to the community. The analysis of the associated stellar parameters corroborates the predictions of different literature models.

Constraining multi-field inflation using the SPHEREx all-sky survey power spectra

We investigate how well the SPHEREx all-sky survey can constrain local primordial non-Gaussianity beyond the parameter f NL using galaxy power spectra. We forecast joint constraints on the parameters f NL, g NL and τ NL obtained assuming a simple two-field curvaton model of inflation. The parameters f NL and g NL characterise the squeezed limits of the primordial bispectrum and trispectrum respectively, and lead to a characteristic scale-dependence of the galaxy bias that increases out to arbitrarily large scales. Values of the parameter τ NL > (6/5f NL)2 cause the galaxy power spectrum to have a stochastic component which also increases out to arbitrarily large scales. Our MCMC forecasts indicate that SPHEREx can provide joint constraints on any two of the three parameters f NL, g NL and τ NL. Due to strong degeneracies among these parameters, measurements of the galaxy power spectra alone may not be sufficient to jointly constrain all three. Constraints on f NL, g NL and τ NL obtained from galaxy power spectrum observations depend on the modelling of underlying nuisance parameters. We study the robustness of our forecast constraints to modelling choices and note that even with relatively conservative modelling assumptions, SPHEREx galaxy power spectra can provide strong evidence of local non-Gaussianity, even if the particular values of f NL and g NL cannot be measured precisely.

Infrared Properties of Carbon Stars in Our Galaxy

We explore the characteristics of carbon stars within our Galaxy through a comprehensive analysis of observational data spanning visual and infrared (IR) bands. Leveraging data sets from IRAS, the Infrared Space Observatory, Akari, the Midcourse Space Experiment, the Two Micron All Sky Survey, the Wide-field Infrared Survey Explorer (WISE), Gaia DR3, AAVSO, and the SIMBAD object database, we conduct a detailed comparison between the observational data and theoretical models. To facilitate this comparison, we introduce various IR two-color diagrams (2CDs), IR color–magnitude diagrams (CMDs), and spectral energy distributions (SEDs). We find that the CMDs, which utilize the latest distance and extinction data from Gaia DR3 for a substantial number of carbon stars, are very useful for distinguishing carbon-rich asymptotic giant branch (CAGB) stars from extrinsic carbon stars that are not in the AGB phase. To enhance the accuracy of our analysis, we employ theoretical radiative transfer models for dust shells around CAGB stars. These theoretical dust shell models demonstrate a commendable ability to approximate the observations of CAGB stars across various SEDs, 2CDs, and CMDs. We present the infrared properties of known pulsating variables and explore the infrared variability of the sample stars by analyzing WISE photometric data spanning the last 14 years. Additionally, we present a novel catalog of CAGB stars, offering enhanced reliability and a wealth of additional information.