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Correlating BASS DR3 catalogue with ALLWISE database, the data from optical and infrared information are obtained. The quasars from SDSS are taken as training and test samples while those from LAMOST are considered as external test sample. We propose two schemes to construct the redshift estimation models with XGBoost, CatBoost and Random forest. One scheme (namely one-step model) is to predict photometric redshifts directly based on the optimal models created by these three algorithms; the other scheme (namely two-step model) is to firstly classify the data into low- and high- redshift datasets, and then predict photometric redshifts of these two datasets separately. For one-step model, the performance of these three algorithms on photometric redshift estimation is compared with different training samples, and CatBoost is superior to XGBoost and Random forest. For two-step model, the performance of these three algorithms on the classification of low- and high-redshift subsamples are compared, and CatBoost still shows the best performance. Therefore CatBoost is regard as the core algorithm of classification and regression in two-step model. By contrast with one-step model, two-step model is optimal when predicting photometric redshift of quasars, especially for high redshift quasars. Finally the two models are applied to predict photometric redshifts of all quasar candidates of BASS DR3. The number of high redshift quasar candidates is 3938 (redshift $\ge 3.5$) and 121 (redshift $\ge 4.5$) by two-step model. The predicted result will be helpful for quasar research and follow up observation of high redshift quasars., 16 pages, 8 figures, 12 tables, accepted for publication in Monthly Notices of the Royal Astronomical Society Main Journal

LAMOST Data Release 5, covering $\sim$17,000 $deg^2$ from $-10^{\circ}$ to $80^{\circ}$ in declination, contains 9 millions co-added low resolution spectra of celestial objects, each spectrum combined from repeat exposure of two to tens of times during Oct 2011 to Jun 2017. In this paper, We present the spectra of individual exposures for all the objects in LAMOST Data Release 5. For each spectrum, equivalent width of 60 lines from 11 different elements are calculated with a new method combining the actual line core and fitted line wings. For stars earlier than F type, the Balmer lines are fitted with both emission and absorption profiles once two components are detected. Radial velocity of each individual exposure is measured by minimizing ${\chi}^2$ between the spectrum and its best template. Database for equivalent widths of spectral lines and radial velocities of individual spectra are available online. Radial velocity uncertainties with different stellar type and signal-to-noise ratio are quantified by comparing different exposure of the same objects. We notice that the radial velocity uncertainty depends on the time lag between observations. For stars observed in the same day and with signal-to-noise ratio higher than 20, the radial velocity uncertainty is below 5km/s, and increase to 10km/s for stars observed in different nights., Comment: 21 pages, 15 figures

Astronomical observation data require long-term preservation, and the rapid accumulation of observation data makes it necessary to consider the cost of long-term archive storage. In addition to low-speed disk-based online storage, optical disk or tape-based offline storage can be used to save costs. However, for astronomical research that requires historical data (particularly time-domain astronomy), the performance and energy consumption of data-accessing techniques cause problems because the requested data (which are organized according to observation time) may be located across multiple storage devices. In this study, we design and develop a tool referred to as AstroLayout to redistribute the observation data using spatial aggregation. The core algorithm uses graph partitioning to generate an optimized data placement according to the original observation data statistics and the target storage system. For the given observation data, AstroLayout can copy the long-term archive in the target storage system in accordance with this placement. An efficiency evaluation shows that AstroLayout can reduce the number of devices activated when responding to data-access requests in time-domain astronomy research. In addition to improving the performance of data-accessing techniques, AstroLayout can also reduce the storage system’s power consumption. For enhanced adaptability, it supports storage systems of any media, including optical disks, tapes, and hard disks.

The three Antarctic Survey Telescopes (AST3) aim to carry out time domain imaging survey at Dome A, Antarctica. The first of the three telescopes (AST3-1) was successfully deployed on January 2012. AST3-1 is a 500\,mm aperture modified Schmidt telescope with a 680\,mm diameter primary mirror. AST3-1 is equipped with a SDSS $i$ filter and a 10k $\times$ 10k frame transfer CCD camera, reduced to 5k $\times$ 10k by electronic shuttering, resulting in a 4.3 deg$^2$ field-of-view. To verify the capability of AST3-1 for a variety of science goals, extensive commissioning was carried out between March and May 2012. The commissioning included a survey covering 2000 deg$^2$ as well as the entire Large and Small Magellanic Clouds. Frequent repeated images were made of the center of the Large Magellanic Cloud, a selected exoplanet transit field, and fields including some Wolf-Rayet stars. Here we present the data reduction and photometric measurements of the point sources observed by AST3-1. We have achieved a survey depth of 19.3\,mag in 60 s exposures with 5\,mmag precision in the light curves of bright stars. The facility achieves sub-mmag photometric precision under stable survey conditions, approaching its photon noise limit. These results demonstrate that AST3-1 at Dome A is extraordinarily competitive in time-domain astronomy, including both quick searches for faint transients and the detection of tiny transit signals., 12 pages, 8 figures, accepted for publication in MNRAS, the dataset is public in http://explore.china-vo.org/

This paper presents the second data release (DR2) of the Beijing-Arizona Sky Survey (BASS). BASS is an imaging survey of about 5400 deg$^2$ in $g$ and $r$ bands using the 2.3 m Bok telescope. DR2 includes the observations as of July 2017 obtained by BASS and Mayall $z$-band Legacy Survey (MzLS). This is our first time to include the MzLS data covering the same area as BASS. BASS and MzLS have respectively completed about 72% and 76% of their observations. The two surveys will be served for the spectroscopic targeting of the upcoming Dark Energy Spectroscopic Instrument. Both BASS and MzLS data are reduced by the same pipeline. We have updated the basic data reduction and photometric methods in DR2. In particular, source detections are performed on stacked images, and photometric measurements are co-added from single-epoch images based on these sources. The median 5$\sigma$ depths with corrections of the Galactic extinction are 24.05, 23.61, and 23.10 mag for $g$, $r$, and $z$ bands, respectively. The DR2 data products include stacked images, co-added catalogs, and single-epoch images and catalogs. The BASS website (http://batc.bao.ac.cn/BASS/) provides detailed information and links to download the data., Comment: 23 pages, published in AJ

The Beijing-Arizona Sky Survey (BASS) is a wide-field two-band photometric survey of the Northern Galactic Cap using the 90Prime imager on the 2.3 m Bok telescope at Kitt Peak. It is a four-year collaboration between the National Astronomical Observatory of China and Steward Observatory, the University of Arizona, serving as one of the three imaging surveys to provide photometric input catalogs for target selection of the Dark Energy Spectroscopic Instrument (DESI) project. BASS will take up to 240 dark/grey nights to cover an area of about 5400 deg$^2$ in the $g$ and $r$ bands. The 5$\sigma$ limiting AB magnitudes for point sources in the two bands, corrected for the Galactic extinction, are 24.0 and 23.4 mag, respectively. BASS, together with other DESI imaging surveys, will provide unique science opportunities that cover a wide range of topics in both Galactic and extragalactic astronomy., Comment: 10 pages, submitted to PASP

The SCUSS is a deep $u$-band imaging survey in the south Galactic cap using the 2.3m Bok telescope. The survey observations were completed in the end of 2013, covering an area of about 5000 square degrees. We release the data in the region with an area of about 4000 deg$^2$ that is mostly covered by the Sloan digital sky survey. The data products contain calibrated single-epoch images, stacked images, photometric catalogs, and a catalog of star proper motions derived by Peng et al, 2015. The median seeing and magnitude limit ($5\sigma$) are about 2".0 and 23.2 mag, respectively. There are about 8 million objects having measurements of absolute proper motions. All the data and related documentations can be accessed through the SCUSS data release website of \url{http://batc.bao.ac.cn/Uband/data.html}., Comment: 13 pages, 7 figures, accepted by AJ

The South Galactic Cap u-band Sky Survey (SCUSS) is a deep u-band imaging survey in the Southern Galactic Cap, using the 90Prime wide-field imager on the 2.3m Bok telescope at Kitt Peak. The survey observations started in 2010 and ended in 2013. The final survey area is about 5000 deg2 with a median 5-sigma point source limiting magnitude of about 23.2. This paper describes the survey data reduction process, which includes basic imaging processing, astrometric and photometric calibrations, image stacking, and photometric measurements. Survey photometry is performed on objects detected both on SCUSS u-band images and in the SDSS database. Automatic, aperture, point-spread function (PSF), and model magnitudes are measured on stacked images. Co-added aperture, PSF, and model magnitudes are derived from measurements on single-epoch images. We also present comparisons of the SCUSS photometric catalog with those of the SDSS and CFHTLS., 24 pages, 20 figures, published online (AJ, 150, 104)