Calibration of metallicity of LAMOST M dwarf stars Using FGK+M wide binaries

Estimating precise metallicity of M dwarfs is a well-known difficult problem due to their complex spectra. In this work, we empirically calibrate the metallicity using wide binaries with a F, G, or K dwarf and a M dwarf companion. With 1308 FGK+M wide binaries well observed by LAMOST, we calibrated M dwarf's [Fe/H] by using the Stellar LAbel Machine (SLAM) model, a data-driven method based on support vector regression (SVR). The [Fe/H] labels of the training data are from FGK companions in range of [-1,0.5] dex. The Teffs are selected from Li et al. (2021), spanning [3100,4400] K. The uncertainties in SLAM estimates of [Fe/H] and Teff are ~0.15 dex and ~40 K, respectively, at snri > 100, where snri is the signal-to-noise ratio (SNR) at i-band of M dwarf spectra. We applied the trained SLAM model to determine the [Fe/H] and Teff for ~630,000 M dwarfs with low-resolution spectra in LAMOST DR9. Compared to other literature also using FGK+M wide binaries for calibration, our [Fe/H] estimates show no bias but a scatter of ~ 0.14-0.18 dex. However, the [Fe/H] compared to APOGEE shows a systematic difference of ~ 0.10-0.15 dex with a scatter of ~ 0.15-0.20 dex. While the Teff compared to APOGEE has a bias of 3 K with a scatter of 62 K, it is systematically higher by 180 K compared to other calibrations based on the bolometric temperature. Finally, we calculated the zeta index for 1308 M dwarf secondaries and presents a moderate correlation between zeta and [Fe/H].Comment: 18 pages, 15 Figure

Searching for new globular clusters in M 31 with Gaia EDR3

We found 50 new globular cluster (GC) candidates around M\,31 with Gaia Early Data Release 3 (EDR3), with the help from Pan-STARRS1 DR1 magnitudes and Pan-Andromeda Archaeological Survey (PAndAS) images. Based on the latest Revised Bologna Catalog and \textit{simbad}, we trained 2 Random Forest (RF) classifiers, the first one to distinguish extended sources from point sources and the second one to further select GCs from extended sources. From 1.85 million sources of $16^m{<}g{<}19.5^m$ and within a large area of $\sim$392\,deg$^2$ around M\,31, we selected 20,658 extended sources and 1,934 initial GC candidates. After visual inspection of the PAndAS images to eliminate the contamination of non-cluster sources, particularly galaxies, we finally got 50 candidates. These candidates are divided into 3 types (\textbf{a}, \textbf{b}, \textbf{c}) according to their projected distance $D$ to the center of M\,31 and their probability to be a true GC, $P_{GC}$, which is calculated by our second RF classifier. Among these candidates, 14 are found to be associated (in projection) with the large-scale structures within the halo of M\,31. We also provided several simple parameter criteria for selecting extended sources effectively from the Gaia EDR3, which can reach a completeness of 92.1\% with a contamination fraction lower than 10\%

Internal Calibration of LAMOST and Gaia DR3 GSP-Spec Stellar Abundances

Stellar chemical abundances are crucial and fundamental in astrophysics. However, they could suffer from substantial systematic errors according to several investigations but still lack calibrations in bulk. By using Gaia wide binaries, we find the temperature-dependent bias between the two binary components for [Fe/H] and [ α /Fe] measurements from the LAMOST low-resolution spectra and Gaia RVS spectra. At T _eff = 4000 K, the LAMOST [Fe/H] is significantly underestimated by approximately 0.4 dex when compared with its typical uncertainty of 0.1 dex. Its [ α /Fe] is overestimated by about 0.2 dex. For Gaia, the underestimation of [M/H] and overestimation of [ α /Fe] becomes pronounced near 7000 K with smaller magnitudes. We perform an internal calibration by minimizing the differences between the binary components and provide the correction curves. After corrections, the standard deviations of the residuals compared to the PASTEL catalog decrease from about 0.045/0.1 to 0.02/0.043 for LAMOST and Gaia, respectively. The chemical homogeneity of the open cluster M 44 is also improved by a factor of two. We stress that the underestimation of [Fe/H] could lead to an overestimation of binary fractions when selecting binary stars by the excess of luminosity. The method of this work could be applied to other data sets in the future. Our results will benefit statistic studies that use LAMOST and Gaia samples with a wide temperature range

Throughput Improvement by Joint Relay Selection and Link Scheduling in Relay-Assisted Cellular Networks

We consider joint relay selection and link scheduling to maximize the network throughput in relay-assisted cellular networks. The spatial reuse is leveraged by scheduling multiple links to simultaneously transmit. The coupling among relay selection, link scheduling, and the interference that is introduced by simultaneous transmissions makes this problem hard to solve. We summarize spatial reuse into two forms. The first form of spatial reuse exists among second-hop links, where relay stations transmit to mobile users. The second form of spatial reuse exists between second- and first-hop links, where the base station transmits to relay stations or mobile users. A framework is proposed to de-couple the joint problem into the following two subproblems: 1) a frame segmentation problem and 2) a relay selection problem. Under this framework, we propose two algorithms for either only the first form of spatial reuse exists or both forms of spatial reuse exist. Numerical results show that, with the first form of spatial reuse, the performance of the proposed heuristic relay selection algorithm is very close to the optimum. In the given scenario, when both forms of spatial reuse exist and the proposed heuristic frame segmentation algorithm is applied, the throughput is improved by up to more than 50% compared with the case without spatial reuse

Discovery of a Dusty Yellow Supergiant Progenitor for the Type IIb SN 2017gkk

Type IIb supernovae are an important subclass of stripped-envelope supernovae (SNe), which show H lines only at early times. Their progenitors are believed to contain a low-mass H envelope before explosion. This work reports the discovery of a progenitor candidate in preexplosion Hubble Space Telescope images for the Type IIb SN 2017gkk. With detailed analysis of its spectral energy distribution and local environment, we suggest that the progenitor is most likely a yellow supergiant with significant circumstellar extinction and has an initial mass of about 16 M _⊙ , effective temperature log( T _eff /K) = 3.72 ± 0.08, and luminosity log( L / L _⊙ ) = 5.17 ± 0.04. This progenitor is not massive enough to strip envelope through stellar wind, and it supports an interacting binary progenitor channel and adds to the growing list of direct progenitor detections for Type IIb SNe. Future late-time observations will confirm whether this progenitor candidate has disappeared and reveal the putative binary companion that has survived the explosion

The Dusty Red Supergiant Progenitor and the Local Environment of the Type II SN 2023ixf in M101

As one of the closest supernovae (SNe) in the last decade, SN 2023ixf is an unprecedented target to investigate the progenitor star that exploded. However, there is still significant uncertainty in the reported progenitor properties. In this work, we present a detailed study of SN 2023ixf’s progenitor with two independent analyses. We first modeled its spectral energy distribution (SED) based on Hubble Space Telescope optical, Spitzer mid-infrared (IR), and ground-based near-IR data. We find that stellar pulsation and circumstellar extinction have great impacts on SED fitting, and the result suggests a relatively massive red supergiant surrounded by C-rich dust with an initial mass of 16.2–17.4 M _⊙ . The corresponding rate of mass loss occurring at least 3 yr before the SN explosion is about 2 × 10 ^−4 M _⊙ yr ^−1 . We also derived the star formation history of the SN environment based on resolved stellar populations, and the most recent star-forming epoch corresponds to a progenitor initial mass of 17–19 M _⊙ , in agreement with that from our SED fitting. Therefore, we conclude that the progenitor of SN 2023ixf is close to the high-mass end for Type II SN progenitors

A Comprehensive Correction of the Gaia DR3 XP Spectra

By combining spectra from the CALSPEC and NGSL, as well as spectroscopic data from the LAMOST Data Release 7 (DR7), we have analyzed and corrected the systematic errors of the Gaia DR3 BP/RP (XP) spectra. The errors depend on the normalized spectral energy distribution (simplified by two independent “colors”) and G magnitude. Our corrections are applicable in the range of approximately −0.5 < BP − RP < 2, 3 < G < 17.5, and E ( B − V ) < 0.8. To validate our correction, we conduct independent tests by comparisons with the MILES and LEMONY spectra. The results demonstrate that the systematic errors of BP − RP and G have been effectively corrected, especially in the near-ultraviolet. The consistency between the corrected Gaia XP spectra and the MILES and LEMONY is better than 2% in the wavelength range of 336–400 nm and 1% in redder wavelengths. A global absolute calibration is also carried out by comparing the synthetic Gaia photometry from the corrected XP spectra with the corrected Gaia DR3 photometry. Our study opens up new possibilities for using XP spectra in many fields. A Python package is publicly available to do the corrections (doi: https://doi.org/10.12149/101375 or https://github.com/HiromonGON/GaiaXPcorrection )