Keywords

Deriving atmospheric parameters of a large sample of stars is of vital importance to understand the formation and evolution of the Milky Way. Photometric surveys, especially those with near-ultraviolet filters, can offer accurate measurements of stellar parameters, with the precision comparable to that from low/medium resolution spectroscopy. In this study, we explore the capability of measuring stellar atmospheric parameters from Chinese Space Station Telescope (CSST) broad-band photometry (particularly in the near-ultraviolet bands), based on synthetic colors derived from model spectra. We find that colors from the optical and near-ultraviolet filter systems adopted by CSST show significant sensitivities to the stellar atmospheric parameters, especially the metallicity. According to our mock data tests, the precision of the photometric metallicity is quite high, with typical values of 0.17 and 0.20 dex for dwarf and giant stars, respectively. The precision of the effective temperature estimated from broad-band colors are within 50 K.

Pulsar search is always the basis of pulsar navigation, gravitational wave detection and other research topics. Currently, the volume of pulsar candidates collected by the Five-hundred-meter Aperture Spherical radio Telescope (FAST) shows an explosive growth rate that has brought challenges for its pulsar candidate filtering system. Particularly, the multi-view heterogeneous data and class imbalance between true pulsars and non-pulsar candidates have negative effects on traditional single-modal supervised classification methods. In this study, a multi-modal and semi-supervised learning based on a pulsar candidate sifting algorithm is presented, which adopts a hybrid ensemble clustering scheme of density-based and partition-based methods combined with a feature-level fusion strategy for input data and a data partition strategy for parallelization. Experiments on both High Time Resolution Universe Survey II (HTRU2) and actual FAST observation data demonstrate that the proposed algorithm could excellently identify pulsars: On HTRU2, the precision and recall rates of its parallel mode reach 0.981 and 0.988 respectively. On FAST data, those of its parallel mode reach 0.891 and 0.961, meanwhile, the running time also significantly decreases with the increment of parallel nodes within limits. Thus, we can conclude that our algorithm could be a feasible idea for large scale pulsar candidate sifting for FAST drift scan observation.

We conduct a statistical analysis of the hardness ratio (HR) for bright sources in the 4 yr Galactic Plane Scanning Survey catalog of Insight-HXMT. Depending on the stable (variable) flux F_s (F_v) or spectrum S_s(S_v) of each source, the bright sources are classified into three groups: F_v&S_v, F_v&S_s, and F_s&S_s. Our study of the HR characteristics in different types of sources reveals that accretion-powered neutron star (NS) low-mass X-ray binaries (LMXBs) exhibit softer energy spectra than NS high-mass X-ray binaries (HMXBs), but harder energy spectra than black hole binaries in most cases. This difference is probably due to their different magnetic field strengths. Additionally, F_v&S_v LMXBs tend to be harder than F_v&S_s LMXBs below 7 keV, while the opposite is true for HMXBs. Our results suggest that LMXBs may dominate unclassified sources, and NS binaries are likely to be the primary type of X-ray binaries with ambiguous compact stars. By comparing the HR of transient sources in their outburst and low-flux states, it is found that the averaged HR of four sources in the two states are roughly comparable within uncertainties. We also investigate the spatial properties of the three groups and find that F_v&S_v sources are mainly located in the longitude of −20° < l < 9°, F_v&S_s sources cross the Galactic Plane, and F_s&S_s sources are predominantly concentrated in 19° < l < 42°. In addition, analyzing the HR spatial distributions shows the absorption of soft X-rays (primarily below 2 keV) in the Galactic Plane.

Aiming at improving the survey efficiency of the Wide Field Survey Telescope, we have developed a basic scheduling strategy that takes into account the telescope characteristics, observing conditions, and weather conditions at the Lenghu site. The sky area is divided into rectangular regions, referred to as "tiles," with a size of 2577 × 2634 slightly smaller than the focal area of the mosaic CCDs. These tiles are continuously filled in annulars parallel to the equator. The brightness of the sky background, which varies with the moon phase and distance from the moon, plays a significant role in determining the accessible survey fields. Approximately 50 connected tiles are grouped into one block for observation. To optimize the survey schedule, we perform simulations by taking into account the length of exposures, data readout, telescope slewing, and all relevant observing conditions. We utilize the Greedy Algorithm for scheduling optimization. Additionally, we propose a dedicated dithering pattern to cover the gaps between CCDs and the four corners of the mosaic CCD array, which are located outside of the 3° field of view. This dithering pattern helps to achieve relatively uniform exposure maps for the final survey outputs.

We have carried out the Galactic Plane Pulsar Snapshot (GPPS) survey by using the Five-hundred-meter Aperture Spherical radio Telescope (FAST), the most sensitive systematic pulsar survey in the Galactic plane. In addition to more than 500 pulsars already discovered through normal periodical search, we report here the discovery of 76 new transient radio sources with sporadic strong pulses, detected by using the newly developed module for a sensitive single-pulse search. Their small DM values suggest that they all are Galactic rotating radio transients (RRATs). They show different properties in the follow-up observations. More radio pulses have been detected from 26 transient radio sources but no periods can be found due to a limited small number of pulses from all FAST observations. The follow-up observations show that 16 transient sources are newly identified as being the prototypes of RRATs with a period already determined from more detected sporadic pulses, and 10 sources are extremely nulling pulsars, and 24 sources are weak pulsars with sparse strong pulses. On the other hand, 48 previously known RRATs have been detected by the FAST, either during verification observations for the GPPS survey or through targeted observations of applied normal FAST projects. Except for one RRAT with four pulses detected in a session of 5-minute observation and four RRATs with only one pulse detected in a session, sensitive FAST observations reveal that 43 RRATs are just generally weak pulsars with sporadic strong pulses or simply very nulling pulsars, so that the previously known RRATs always have an extreme emission state together with a normal hardly detectable weak emission state. This is echoed by the two normal pulsars J1938+2213 and J1946+1449 with occasional brightening pulses. Though strong pulses of RRATs are very outstanding in the energy distribution, their polarization angle variations follow the polarization angle curve of the averaged normal pulse profile, suggesting that the predominant sparse pulses of RRATs are emitted in the same region with the same geometry as normal weak pulsars.

The Zone of Avoidance (ZoA) is a region of low galactic latitude that is heavily obscured by the Milky Way. Observations with radio telescopes are basically unaffected by dust extinction and can unveil the structure behind it through the Milky Way. One of the scientific goals of the Five-hundred-meter Aperture Spherical radio Telescope (FAST) is to search for the neutral hydrogen and understand the large-scale physics to explore the origin and evolution of the universe. We take the 15,500 IRAS (the Infrared Astronomical Satellite) galaxies from PSCz ("Point Source Catalog") survey to reconstruct the density field of the local universe, obtain the distribution of the relative density of galaxies in the ZoA region with a redshift z below 0.07, and the number of detectable galaxies with FAST is estimated by using the neutral hydrogen mass function of the ALFA (Arecibo L-band Feed Array) survey. We conclude that FAST can observe more than 2000 ZoA galaxies within a distance of 300 Mpc${\,h}_{70}^{-1}$ , and present preliminary results of the partial GPPS (the FAST Galactic Plane Pulsar Snapshot survey) data, compared with ALFA ZoA (The Arecibo L-band Feed Array Zone of Avoidance), show that FAST has a higher detection sensitivity to search for H i galaxies in the ZoA area.

Detached and wide-orbit black hole-star binaries (BHSBs) can generate three types of periodic photometric signals: Ellipsoidal Variation, Doppler beaming and Self-Lensing (SL), providing a proxy to discover these black holes. We estimate the relative amplitude of the three signals for such systems and the detectability for black holes of a photometric telescope like Kepler in several steps. We estimate the searchable star number by assuming every star has a black hole companion, and apply the occurrence of BHSBs in field stars to estimate the detectable black hole signals. We consider three types of Initial Mass Function (IMF) model with different high end exponential slopes. "When spot and white noise are both considered, there is about one detectable signal for SL and less than one event is expected for beaming and Ellipsoidal Variation signal in Kepler Input Catalog stars with the standard IMF model.” to “Due to contamination by stellar spots and white noise, one may expect one detectable signal for SL and less than one detectable signal for both beaming and Ellipsoidal Variation in Kepler Input Catalog stars with the standard IMF model." On the other hand, if we assume that only white noise affects the detection efficiency of the BHSBs, we expect about 10 Ellipsoidal Variation signals and 17 beaming signals to be detectable while the number of SL signals remains unchanged.

This paper presents an automatic multi-band source cross-identification method based on deep learning to identify the hosts of extragalactic radio emission structures. The aim is to satisfy the increased demand for automatic radio source identification and analysis of large-scale survey data from next-generation radio facilities such as the Square Kilometre Array and the Next Generation Very Large Array. We demonstrate a 97% overall accuracy in distinguishing quasi-stellar objects, galaxies and stars using their optical morphologies plus their corresponding mid-infrared information by training and testing a convolutional neural network on Pan-STARRS imaging and WISE photometry. Compared with an expert-evaluated sample, we show that our approach has 95% accuracy at identifying the hosts of extended radio components. We also find that improving radio core localization, for instance by locating its geodesic center, could further increase the accuracy of locating the hosts of systems with a complex radio structure, such as C-shaped radio galaxies. The framework developed in this work can be used for analyzing data from future large-scale radio surveys.

We have started a systematic survey of molecular clumps with infall motions to study the very early phase of star formation. Our first step is to utilize the data products by MWISP to make an unbiased survey for blue asymmetric line profiles of CO isotopical molecules. Within a total area of ∼2400 square degrees nearby the Galactic plane, we have found 3533 candidates showing blue-profiles, in which 3329 are selected from the ¹²CO&¹³CO pair and 204 are from the ¹³CO&C¹⁸O pair. Exploration of the parametric spaces suggests our samples are in the cold phase with relatively high column densities ready for star formation. Analysis of the spatial distribution of our samples suggests that they exist virtually in all major components of the galaxy. The vertical distribution suggest that the sources are located mainly in the thick disk of ∼85 pc, but still a small part are located far beyond Galactic midplane. Our follow-up observation indicates that these candidates are a good sample to start a search for infall motions, and to study the condition of very early phase of star formation.

Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) has completed the observation of nearly 20 million celestial objects, including a class of spectra labeled "Unknown." Besides low signal-to-noise ratio, these spectra often show some anomalous features that do not work well with current templates. In this paper, a total of 637,889 "Unknown" spectra from LAMOST DR5 are selected, and an unsupervised-based analytical framework of "Unknown" spectra named SA-Frame (Spectra Analysis-Frame) is provided to explore their origins from different perspectives. The SA-Frame is composed of three parts: NAPC-Spec clustering, characterization and origin analysis. First, NAPC-Spec (Nonparametric density clustering algorithm for spectra) characterizes different features in the "unknown" spectrum by adjusting the influence space and divergence distance to minimize the effects of noise and high dimensionality, resulting in 13 types. Second, characteristic extraction and representation of clustering results are carried out based on spectral lines and continuum, where these 13 types are characterized as regular spectra with low S/Ns, splicing problems, suspected galactic emission signals, contamination from city light and un-gregarious type respectively. Third, a preliminary analysis of their origins is made from the characteristics of the observational targets, contamination from the sky, and the working status of the instruments. These results would be valuable for improving the overall data quality of large-scale spectral surveys.