Large Sky Area Research Articles

Very metal-poor stars I: a catalogue derived from LAMOST DR9

ABSTRACT In this paper, a semisupervised machining learning technique had been utilized to analyse low-resolution stellar spectra from Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) Data Release 9 (DR9). We identified approximately 111 000 potential very metal-poor stars. Estimation of their stellar parameters ($T_{\rm eff}$, ${\rm log}\, \rm {g}$, [Fe/H]) indicate that over 99 per cent are metal-poor ([Fe/H] < −1.0), comprising 32 631 very metal-poor ([Fe/H] < −2.0), 702 extremely metal-poor ([Fe/H] < −3.0) and 30 ultra metal-poor ([Fe/H] < −4.0) stars. Based on kinematic characteristics, stars were categorized into thick disc-like, thin disc-like, and halo-like groups. We analysed their metallicity distributions (MDs) with respect to vertical height ($|Z|$) and orbital eccentricity (e). Thick disc-like stars in current sample show a clear trend of decreasing metallicty with increasing $|Z|$ or e for the ranges −3.0 $\lt $ [Fe/H] $\lt $ −1.2 and $|Z|$$\lt $ 3 kpc. Conversely, thin disc-like stars in current sample exhibit a slight increase in the fraction of more metal-poor stars with $|Z|$ for the ranges −3.0 $\lt $ [Fe/H] $\lt $ −1.2 and $|Z|$$\lt$ 1 kpc, but no obvious correlation with e. Additionally, we confirmed the presence of two prominent substructures among halo-like stars. One exhibits a high eccentricity ($e\ \gt\ 0.8$) orbit and higher metallicity, while the other follows a retrograde orbit with moderate eccentricity ($e\sim 0.6$) and lower metallicity. We believe they are related to the merger events known as Gaia Sausage and Sequoia, respectively. Furthermore, our observations indicate that the Sequoia has lower eccentricity and metallicity compared to the Gaia Sausage.

Stellar spectral template library construction based on generative adversarial networks

Stellar spectral template libraries play an important role in the automated analysis of stellar spectra. Synthetic template libraries cover a very large parameter space but suffer from poor matching with observed spectra. In this study, we propose a synthetic-to-observed spectral translation (SOST) method based on generative adversarial networks. The SOST method is able to calibrate synthetic spectra by converting them to the corresponding observed spectra. We applied this method to Kurucz synthetic spectra and observed spectra data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). After that, we constructed a stellar spectral library with uniform and broad parameter distributions using the SOST-corrected Kurucz synthetic spectra. Our stellar spectral template library contains 2431 spectra spanning a parameter space of 3500–8000 K for effective temperature (Teff), 0.0–5.0 dex for surface gravity (log g), and −2.0–0.5 dex for metallicity ([Fe/H]). The spectra in the library have a resolution of R ∼ 1800 and cover the wavelength range 3900–8700 Å. In order to verify the accuracy of this template library, we used the template library and the template-matching algorithm to derive the parameters of the PASTEL database. Compared to measurements using the original synthetic template library, the accuracies of the three parameters, Teff, log g, and [Fe/H], are improved, from 140 K, 0.31 dex, and 0.21 dex to 121 K, 0.26 dex, and 0.13 dex, respectively. In addition, we re-parameterised more than six million stellar spectra released by LAMOST DR8.

Data mining techniques on astronomical spectra data – III. Association analysis

ABSTRACT Association analysis is an important task that aims to investigate correlations in astronomical spectral data and mine relationships between different data features. With the rapid development of various sky survey projects, multiple association analysis methods have been applied to efficiently investigate the correlation between spectral data. However, due to the different focuses of analysing the relationships within spectral data, the performance and applicability scenarios of association analysis methods vary. We present the third article in the series to provide a comprehensive review of algorithms for astronomical spectral association analysis. First, this paper outlines the ideas and applications of association analysis algorithms for astronomical spectra in the current literature. Secondly, experiments are conducted on a unified A-type stellar spectral data set constructed based on three different signal-to-noise ratios and data volumes to examine the performance of different algorithms in analysing the correlation between data features. The results indicate that association rule algorithms can more comprehensively and effectively uncover the correlations among different spectral features, while regression analysis algorithms offer a simpler and more intuitive approach to analysing relationships between features. The spectral data used in the experiments are obtained from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope. Finally, the source code of association analysis algorithms and manuals for usage are provided on GitHub.

Method for LAMOST cofocus maintenance based on an Eddy current edge sensor

The current cofocus maintenance strategy of the primary mirror of the Large Sky Area Multi-Object Spectroscopic Telescope (Mb) using Shack–Hartmann Wavefront Sensor (SHWFS) interrupts the observation mission. This study proposed an Eddy current edge sensor with high precision and accuracy to achieve closed-loop cofocus control. Through structural design, interaction matrix deduction, installation parameter analysis, and performance calibration, the edge sensor was validated for use in detecting segment attitudes. The minimum cofocus maintenance system comprising three segments was separated from Mb and established to validate the effectiveness of the closed-loop cofocus control with the novel edge sensor. The closed-loop control system was effective within less than 1.5°C environmental temperature changes after 13 h, which is considerably longer than the maintenance time with the SHWFS. Moreover, continuous observation without interruption is possible during one observation night.

Statistical analysis of asteroseismic indices and stellar parameters of TESS-observed δ Scuti stars

Context. Over the last few years, δ Scuti stars have been at the center of the attention of the asteroseismology community thanks to the derivation of seismic indices connected to stellar parameters. The statistical analysis of the wealth of data offered by a large space survey such as the Transiting Exoplanet Survey Satellite (TESS), the identification of new δ Scuti stars, and the correlation between asteroseismic indices and stellar parameters in the resulting sample are therefore of utmost interest. Aims. The goal of our study is to analyze the statistical properties of stellar parameters and characterize the asteroseismic indices of δ Scuti stars observed in TESS cycle 4. Methods. We used TESS 2 min cadence photometric data and the corresponding Fourier transform to identify δ Scuti stars. The asteroseismic indices for these stars were determined using an empirical relation and a 2D autocorrelation method. Results. We discovered 765 δ Scuti stars from the data obtained by the TESS mission, from Sectors 40–55, corresponding to cycle 4 and observed with a 2 min cadence. Of these stars, 179 δ Scuti stars have low-resolution spectral parameters from LAMOST. We first analyzed the relation between pulsation and stellar parameters from TESS observations and the distribution of δ Scuti stars with two different stellar parameters, TESS Input Catalog (TIC) and Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), within the classical instability strip. Most of the stars lie within the instability strip and follow the period-luminosity relation of δ Scuti stars. Additionally, the majority of the stars exhibit pulsation properties consistent with those expected for δ Scuti stars, including periods falling within the typical range, amplitudes at the millimagnitude level, and fundamental parameters such as spectral type, effective temperature, log g, and luminosity that match the characteristics of δ Scuti stars. This confirms the reliability of the δ Scuti stars we have identified. We subsequently obtained the large frequency separation (∆ν), vmax, and ν(Amax) for 179 δ Scuti stars with LAMOST parameters by using an empirical relation and a 2D autocorrelation method, and obtained the relations between these asteroseismic indices. These stars will provide significant support for a deeper study of the internal structure and evolution of stars.

Stellar Atmospheric Parameters of ∼11,000 RR Lyrae Stars from LAMOST Spectra

Accurate determination of the stellar atmospheric parameters of RR Lyrae stars (RRLs) requires short individual exposures of the spectra to mitigate pulsation effects. We present improved template-matching methods to determine the stellar atmospheric parameters of RRLs from single-epoch spectra of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, also known as the Guoshoujing Telescope (LAMOST). We determine the radial velocities and stellar atmospheric parameters (effective temperature T eff, surface gravity logg , and metallicity [M/H]) of 10,486 and 1027 RRLs from 42,729 LAMOST low-resolution spectra (LRS) and 7064 LAMOST medium-resolution spectra (MRS), respectively. Our results are in good agreement with the parameters of other databases, where the external uncertainties of T eff, logg , and [M/H] for LRS/MRS are estimated to be 207/142 K, 0.21/0.16 dex, and 0.24/0.18 dex, respectively. We conclude with the variation characteristics of the radial velocities (RV) and stellar atmospheric parameters for RRLs during the pulsation phase. There is a significant difference of 28 ± 21 km s−1 between the peak-to-peak amplitude (A ptp) of RV from the Hα line (RVHα ) and from metal lines (RVmetal) for RRab, whereas it is only 4 ± 17 km s−1 for RRc. The A ptp of T eff is 930 ± 456 and 409 ± 375 K for RRab and RRc, respectively. The logg of RRab shows a mild variation of approximately 0.22 ± 0.42 dex near the phase of φ = 0.9, while that of RRc almost remains constant. The [M/H] of RRab and RRc show a minor variation of about 0.25 ± 0.50 and 0.28 ± 0.55 dex, respectively, near the phase of φ = 0.9. We expect that the determined stellar atmospheric parameters would shed new light on the study of stellar evolution and pulsation, the structure of the Milky Way, as well as other research fields.

Motion Planning for the Robotic Fiber Positioners of the Large Sky Area Multiobject Fiber Spectrocopy Telescope

The Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) is one of the most effective multiobject spectroscopic instruments. Its survey efficiency is guaranteed by simultaneously positioning multiple fibers via 4000 robotic fiber positioners (RFPs). With the further updates to LAMOST, the new-generation RFPs will be smaller, and the number of RFPs will increase to 5000. The RFPs are densely packed with shared working space. Thus, they may collide with each other, leading to them damaged and reducing the survey speed. In this study, we propose a new motion planning algorithm that prevents the collision of RFPs. To simplify the collision avoidance problem, we transform the motion planning process from a dynamic one into a static one by selecting one of the RFPs in each collision pair as the waiting robot. Accordingly, we design a method for choosing the waiting robot, and use a rapidly exploring random tree to plan a collision-free path for the waiting robot. However, there may be blocks between the waiting robots and their neighbors. Therefore, we also design methods to resolve these blocks. Simulations suggest that the proposed algorithm can prevent 98.4% of the collisions. About 99.9% of the positioners can reach their targets without collisions. Although developed for LAMOST, we believe that our algorithm can also be used for other instruments with equal-arm theta-phi positioners, such as the Dark Energy Spectroscopic Instrument.

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

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.

Detailed mapping of the Galactic disc structure in the solar neighbourhood through LAMOST K dwarfs

ABSTRACT The Galactic disc is one of the main components of the Milky Way, which contributes most of the luminosity. Its structure is essential for understanding the formation and evolution of the Milky Way. Using 174 443 K-type dwarf stars observed by both Large Sky Area Multi-Object Fiber Spectroscopic Telescope and Gaia Data Release 3, we study the disc density profile in the local volume within 1200 pc. In the azimuthal dimension, we find strong asymmetric signal of the thin disc. The surface density and the scale height of the southern disc significantly change versus the azimuthal angle at the same Galactocentric distance R. Meanwhile, in the vertical dimension, the scale height of the northern disc has quite different trend than that of the southern one. The scale height of the southern disc shows a decreasing trend with ϕ ∼ −2.5°, and change to an increasing one with ϕ ∼ 5.0°. Meanwhile, the scale height of the northern disc has a consistently smaller increase. Finally, we divide the entire sample into three subsamples based on metallicity and all three subsamples show significant non-axisymmetric and north–south asymmetric signals in the Galactic disc. Furthermore, we find that the scale height of the metal-poor ([Fe/H] < −0.4 dex) subsample in the northern disc is greater than that of the metal-rich ([Fe/H] > −0.1 dex) subsample. However, in the southern disc, the scale height exhibits varying relationships across different metallicity slices.

The Near-infrared Ca ii Triplet as a Stellar Activity Indicator: A Library and Comparative Study

We have established and released a new stellar index library of the Ca ii triplet, which serves as an indicator for characterizing the chromospheric activity of stars. The library is based on data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS) Data Release 9. To better reflect the chromospheric activity of stars, we have defined new indices R and R +. The library includes measurements of R and R + for each Ca ii infrared triplet (IRT) from 699,348 spectra of 562,863 F, G, and K-type solar-like stars with a signal-to-noise ratio higher than 100, as well as the stellar atmospheric parameters and basic information inherited from the LAMOST LRS catalog. We compared the differences between the three individual indices of the Ca ii triplet and also conducted a comparative analysis of Rλ8542+ to the Ca ii H and K S and RHK+ index databases. We observe the fraction of less active stars decreases with T eff and the fraction of more active stars first decreases with decreasing temperature and turns to increase with decreasing temperature at 5800 K. We also find that a significant fraction of stars that show a high activity index in both Ca ii H and K and IRT are binaries with low activity; some of them could be discriminated in the Ca ii H and K S index and Rλ8542+ space. This new stellar library serves as a valuable resource for studying chromospheric activity in stars and can be used to improve our comprehension of stellar magnetic activity and other astrophysical phenomena.

CatNorth: An Improved Gaia DR3 Quasar Candidate Catalog with Pan-STARRS1 and CatWISE

A complete and pure sample of quasars with accurate redshifts is crucial for quasar studies and cosmology. In this paper, we present CatNorth, an improved Gaia Data Release 3 (Gaia DR3) quasar candidate catalog with more than 1.5 million sources in the 3π sky built with data from Gaia, Pan-STARRS1, and CatWISE2020. The XGBoost algorithm is used to reclassify the original Gaia DR3 quasar candidates as stars, galaxies, and quasars. To construct training/validation data sets for the classification, we carefully built two different master stellar samples in addition to the spectroscopic galaxy and quasar samples. An ensemble classification model is obtained by averaging two XGBoost classifiers trained with different master stellar samples. Using a probability threshold of p QSO_mean > 0.95 in our ensemble classification model and an additional cut on the logarithmic probability density of zero proper motion, we retrieved 1,545,514 reliable quasar candidates from the parent Gaia DR3 quasar candidate catalog. We provide photometric redshifts for all candidates with an ensemble regression model. For a subset of 89,100 candidates, accurate spectroscopic redshifts are estimated with the convolutional neural network from the Gaia BP/RP spectra. The CatNorth catalog has a high purity of ∼90%, while maintaining high completeness, which is an ideal sample to understand the quasar population and its statistical properties. The CatNorth catalog is used as the main source of input catalog for the Large Sky Area Multi-Object Fiber Spectroscopic Telescope phase III quasar survey, which is expected to build a highly complete sample of bright quasars with i < 19.5.

Lithium Abundances from the LAMOST Medium-resolution Survey Data Release 9

Lithium is a fragile but crucial chemical element in the Universe, and exhibits interesting and complex behaviors. Thanks to the mass of spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) medium-resolution survey (MRS), we can investigate the lithium abundances in a large and diverse sample of stars, which could bring vital help in studying the origin and evolution of lithium. In this work, we use the Li i 6707.8 Å line to derive the lithium abundance through a template-matching method. A catalog of precise lithium abundance is presented for 795,384 spectra corresponding to 455,752 stars from the LAMOST MRS Data Release 9. Comparing our results with those of external high-resolution references, we find good consistency with a typical deviation of σ A(Li) ∼ 0.2 dex. We also analyze the internal errors using stars that have multiple LAMOST MRS observations, which will reach as low as 0.1 dex when the signal-to-noise ratio of the spectra is >20. Besides, our result indicates that a small fraction of giant stars still exhibit a surprisingly high lithium content, and 967 stars are identified as Li-rich giants with A(Li) > 1.5 dex, accounting for ∼2.6% of our samples. If one takes into account the fact that nearly all stars deplete lithium during the main sequence, then the fraction of Li-rich stars may far exceed 2.6%. This new catalog covers a wide range of stellar evolutionary stages from pre-main sequence to giants, and will provide help to the further study of the chemical evolution of lithium.

Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) data release 10 (DR10) provides over 3 million G-type stellar spectra, which are important for the study of chromospheric activity of solar-like stars. We have used the iSpec program to perform spectral subtraction on the G-type stellar spectra obtained from LAMOST DR10 with a signal-to-noise ratio greater than 10. We have calculated the magnetic activity of G-type stars using Hα lines and analyzed the Hα variation. Among the more than 3 million spectra from more than 2.3 million stars, a total of 220,000 stars show excess chromospheric activity. There were a total of about 480,000 stars with repeated observations. About 390,000 stars were found to exhibit variations in the Hα line, and 14,000 stars showed changes in their radial velocity. By using the Gaia data, we determined the distances of these stars above the Galactic disk. We first concluded that the fraction of G-type active stars decreases with increasing distance above the Galactic disk. By using the Transiting Exoplanet Survey Satellite light curves, we obtained the effective fluctuation range of the light curve caused by the starspot and confirmed that there was a positive correlation between the starspot and chromospheric activity. We also concluded that RHα′ tends to be stable for Rossby number (Ro) < 0.13 and that RHα′ decreases as Ro increases in the region Ro ≥ 0.13.

Magnetic activity of radio stars based on TESS and LAMOST surveys

Aims. Stellar flares serve as crucial indicators stellar magnetic activity. Radio emissions were detectable across all stages of stellar evolution. We define radio stars in our paper as stars with radio continuum emission in the frequency region of about 1.4 - 375 GHz from the catalog published by Wendker (1995, 2015). We also include detected radio stars from the LOFAR Two-metre Sky Survey (LoTSS) and the Australian Square Kilometre Array Pathfinder (ASKAP), and VLA Sky Survey (VLASS) surveys, and present comparative discussions. We used the light curves from the Transiting Exoplanet Survey Satellite (TESS) survey coupled with low- and medium-resolution spectra from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) survey to investigate the magnetic activity and statistical properties of radio stars. Methods. We cross-matched the radio stars from the radio star catalog and the LoTSS, ASKAP, and VLASS surveys with the TESS survey. For the stars from the radio star catalog, we obtained a matched sample of 1,537 stars (hereafter Sample 1) and downloaded their TESS light curves, which include 4,001 light curves at a 120s cadence. For the stars from the LoTSS, ASKAP, and VLASS surveys, we obtain a matched sample of 98 stars (hereafter Sample 2) and downloaded their 120s TESS light curves, totaling 260. Subsequently, we employed repeated fitting techniques to distinguish stellar background light curves from flare events. For Sample 1, we successfully identify 12,155 flare events occurring on 856 stars. For Sample 2, we identify a total of 3,992 flare events on 86 stars. Furthermore, by cross-referencing our samples with the Gaia survey, the TESS Input Catalog, and the LAMOST survey, we obtain additional stellar parameters, facilitating the determination of relationships between stellar and flare parameters. Results. For stars in Sample 1, within the 12,155 flare events observed on the 856 flare-active radio stars, a majority of more than 97$&lt;!PCT!&gt;$ have durations of less than 2 hours, while for stars in Sample 2, all 3,992 flare events have a duration of less than 2 hours. We calculated the flare occurrence percentage for each flare-active radio star, observing a decrease as effective temperature increased for both Sample 1 and Sample 2. We derived values of the power-law index (for Sample 1, the alpha value is approximately 1.50pm 0.11 for single stars and 1.38pm 0.09 for binary stars, for Sample 2, the alpha value is about 1.47pm 0.11 for single stars and 1.42pm 0.09 for binary stars) for the cumulative flare frequency distribution. In both Sample 1 and Sample 2, stars with lower effective temperatures tend to exhibit increased activity. Using LAMOST spectra and the Gaia DR3 chromospheric activity index, we note that the Halpha equivalent width and Gaia Ca II IRT activity index of flare-active radio stars is significantly larger than that of nonflaring stars. An intriguing finding is our potential identification of a coronal rain candidate through asymmetry observed in the Halpha line.

Derivative Spectroscopy and its Application at Detecting the Weak Emission/Absorption Lines

The development of spectroscopic survey telescopes like Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), Apache Point Observatory Galactic Evolution Experiment and Sloan Digital Sky Survey has opened up unprecedented opportunities for stellar classification. Specific types of stars, such as early-type emission-line stars and those with stellar winds, can be distinguished by the profiles of their spectral lines. In this paper, we introduce a method based on derivative spectroscopy (DS) designed to detect signals within complex backgrounds and provide a preliminary estimation of curve profiles. This method exhibits a unique advantage in identifying weak signals and unusual spectral line profiles when compared to other popular line detection methods. We validated our approach using synthesis spectra, demonstrating that DS can detect emission signals three times fainter than Gaussian fitting. Furthermore, we applied our method to 579,680 co-added spectra from LAMOST Medium-Resolution Spectroscopic Survey, identifying 16,629 spectra with emission peaks around the Hα line from 10,963 stars. These spectra were classified into three distinct morphological groups, resulting in nine subclasses as follows. (1) Emission peak above the pseudo-continuum line (single peak, double peaks, emission peak situated within an absorption line, P Cygni profile, Inverse P Cygni profile); (2) Emission peak below the pseudo-continuum line (sharp emission peak, double absorption peaks, emission peak shifted to one side of the absorption line); (3) Emission peak between the pseudo-continuum line.

A Study of Broad Emission Line and Doppler Factor Estimation for Fermi Blazars

In this work, we obtained a sample of 979 Fermi blazars with broad emission lines, including 701 objects collected from published works and 278 objects developed in this work. For the 278 objects, we made a crossmatch from three catalogs, the Fermi Large Area Telescope Fourth Source Catalog (4FGL), the Sloan Digital Sky Survey, and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, and calculated the broad-line region (BLR) luminosity. Then, we estimated the Doppler factor and studied the correlations between the BLR luminosities and the γ-ray luminosities, the synchrotron peak frequency (ν p ), and Doppler factor (δ) for the whole sample. Our analyses and discussions came to the following main conclusions: For the 278 blazars, their BLR luminosity (log L BLR) ranges from 40.44 to 45.45 erg s−1, with a mean value of 43.39 erg s−1. The Doppler factor ranges from δ = 0.45 to δ = 88.52, with a mean value of 12.99 for the 979 Fermi blazars, which is consistent with the results in the literature. Both the BLR luminosity and the Doppler factor exhibit positive correlations with the γ-ray luminosity. The BLR luminosity is anticorrelated with synchrotron peak frequency, implying a Compton cooling. A line of logLBLR=1.58logνp−19.46 separating BL Lacertae objects and flat-spectrum radio quasars was obtained in the diagram of logLBLR against logνp using a machine-learning method. Based on the analysis of the equivalent width and the Doppler factors, we proposed five changing-look blazar candidates.

Identification of Carbon Stars from LAMOST DR7

Carbon stars are excellent kinematic tracers of galaxies and play important roles in understanding the evolution of the Galaxy. Therefore, it is worthwhile to search for them in a large number of spectra. In this work, we build a new carbon star catalog based on the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) DR7 spectra. The catalog contains 4542 spectra of 3546 carbon stars, identified through line index and near-infrared color–color diagrams. Through visual inspection of the spectra, we further subclassify them into 925 C–H, 384 C–R, 608 C–N, and 1292 Ba stars. However, 437 stars could not be subclassified due to their low signal-to-noise. Moreover, by comparing with the LAMOST DR7 pipeline we find 567 more carbon stars and visually subclassify them. We find that on the J − H versus H − K s two-color diagram, C–N stars can be reliably distinguished from the other three subtypes. Additionally, by utilizing the Gaia distance, we study the distribution of carbon stars in the H-R diagram and identify 258 dwarf carbon stars by the criterion M G > 5.0 mag. Finally, we present the spatial distribution in Galactic coordinates of the 3546 carbon stars. The majority of C–N, C–R, and Ba stars are distributed at low Galactic latitudes, while most C–H and dwarf carbon stars are distributed at high Galactic latitudes.

The Calibration of theta-phi Fiber Positioners Based on the Differential Evolution Algorithm

Robotic fiber positioner (RFP) arrays are commonly adopted in multiobject spectroscopic instruments. The positioning accuracy is a common but vital issue for RFP as inaccurate fiber placement may heavily affect the observation performance. The calibration of RFP can effectively improve the positioning accuracy. Least-square is a widely used calibration method. However, it has disadvantages, such as sensitivity to the initial values and calculation complexity. To improve the positioning accuracy and reduce the iteration moves, we propose a new calibration method based on the differential evolution algorithm and verify it by calibrating the RFP of the Large Sky Area Multi-Object Fiber Spectroscopy Telescope. We first build the kinematic models of the RFP based on the Denavit–Hartenberg matrix and geometry relationship. Then, we analyze the error components and present the proposed calibration algorithms. The experiments are done with the digital universal tool microscope 19JC and the errors are calculated using the distance between the positions of achieved and target. Results show that the proposed algorithm can achieve higher accuracy than the least-square method and the average positioning accuracy is improved by 78.94% after calibration. Combined with the “pulse reduction” strategy and close-loop compensation, after two moves, the positioners can place the fiber ends within 40 μm of the intended location. The proposed calibration method is also suitable for other similar theta-phi positioners.

EUDS: the SRG/eROSITA X-ray survey of the UKIDSS Ultra Deep Survey field. Catalogue of sources

ABSTRACT The eROSITA X-ray telescope on board the Spectrum-Roentgen-Gamma (SRG) spacecraft observed the field of the UKIDSS Ultra-Deep Survey (UDS) in August–September 2019, during its flight to Sun–Earth L2 point. The resulting eROSITA UDS (or eUDS) survey was thus the first eROSITA X-ray imaging survey, which demonstrated the capability of the telescope to perform uniform observations of large sky areas. With a moderate single-camera exposure of 150 ks, eUDS covered ∼5 deg2 with the limiting flux ranging between 4 × 10−15 and 5 × 10−14 erg s−1 cm−2 in the 0.3–2.3 keV band. We present a catalogue of 647 sources detected at likelihood &amp;gt;10 (∼4σ) during the eUDS. The catalogue provides information on the source fluxes in the main energy band 0.3–2.3 keV and forced photometry in a number of bands between 0.3 and 8 keV. Using the deeper 4XMM-DR12 catalogue, we have identified 22 strongly variable objects that have brightened or faded by at least a factor of ten during the eROSITA observations compared to previous observations by XMM–Newton. We also provide a catalogue of 22 sources detected by eROSITA in the hard energy band of 2.3–5 keV.