The first data release(DR1) of the LAMOST regular survey

The Large sky Area Multi-Object Fiber Spectroscopic Telescope（LAMOST） general survey is a spectroscopic survey that will eventually cover approximately half of the celestial sphere and collect 10 million spectra of stars, galaxies and QSOs. Objects in both the pilot survey and the first year regular survey are included in the LAMOST DR1. The pilot survey started in October 2011 and ended in June 2012, and the data have been released to the public as the LAMOST Pilot Data Release in August 2012. The regular survey started in September 2012, and completed its first year of operation in June 2013. The LAMOST DR1 includes a total of 1202 plates containing 2 955 336 spectra, of which 1 790 879 spectra have observed signalto-noise ratio（SNR） ≥ 10. All data with SNR ≥ 2 are formally released as LAMOST DR1 under the LAMOST data policy. This data release contains a total of 2 204 696 spectra, of which 1 944 329 are stellar spectra, 12 082 are galaxy spectra and 5017 are quasars. The DR1 not only includes spectra, but also three stellar catalogs with measured parameters： late A,FGK-type stars with high quality spectra（1 061 918 entries）, A-type stars（100 073 entries）, and M-type stars（121 522 entries）. This paper introduces the survey design, the observational and instrumental limitations, data reduction and analysis, and some caveats. A description of the FITS structure of spectral files and parameter catalogs is also provided.

Data release of the LAMOST pilot survey

This paper describes the data release of the LAMOST pilot survey, which includes data reduction, calibration, spectral analysis, data products and data access. The accuracy of the released data and the information about the FITS headers of spectra are also introduced. The released data set includes 319 000 spectra and a catalog of these objects.

South Galactic Cap u-band Sky Survey(SCUSS):Project Overview

The South Galactic Cap u-band Sky Survey （SCUSS） was established in 2009 in order to provide a photometric input catalog for target selection of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope （LAMOST） project. SCUSS is an international cooperative project between National Astronomical Observatories, Chinese Academy of Sciences, and Steward Observatory at the University of Arizona, using the 90 inch （2.3 m） Bok telescope on Kitt Peak. The telescope is equipped with a prime focus camera that is composed of a mosaic of four 4096 × 4096 CCDs and has a field of view of about 1 deg2. From 2009 to 2013, SCUSS performed a sky survey of an approximately 5000 deg2 field of the South Galactic Cap in u band, including the Galactic anticenter area and the SDSS-IV extended imaging area. The limiting magnitude of SCUSS is deeper than 23 mag （at a signal-to-noise ratio of 5）. In this paper, we briefly describe the goals of this project, method of observations and data reduction, and we also introduce current and potential scientific activities related to the SCUSS project.

Research on scheduling of robotic transient survey for Antarctic Survey Telescopes(AST3)

Antarctic Survey Telescopes（AST3） are designed to be fully robotic telescopes at Dome A,Antarctica,which aim for highly efficient time-domain sky surveys as well as rapid response to special transient events（e.g.,gamma-ray bursts,near-Earth asteroids,supernovae,etc.）.Unlike traditional observations,a well-designed real-time survey scheduler is needed in order to implement an automatic survey in a very efficient,reliable and flexible way for the unattended telescopes.We present a study of the survey strategy for AST3 and implementation of its survey scheduler,which is also useful for other survey projects.

NUV Star Catalog from the Lunar-based Ultraviolet Telescope Survey: First Release

We present a star catalog extracted from the Lunar-based Ultraviolet Telescope （LUT） survey program. LUT＇s observable sky area is a circular belt around the Moon＇s north pole, and the survey program covers a preferred area of about 2400 deg2 which includes a region of the Galactic plane. The data are processed with an automatic pipeline which copes with stray light contamination, artificial sources, cosmic rays, flat field calibration, photometry and so on. In the first release version, the catalog provides high confidence sources which have been cross-identified with the Tycho-2 catalog. All the sources have signalto-noise ratio larger than 5, and the corresponding magnitude limit is typically 14.4 mag, but can be as deep as -16 mag if stray light contamination is at the lowest level. A total of 86 467 stars are recorded in the catalog. The full catalog in electronic form is available online.

The LEGUE high latitude bright survey design for the LAMOST pilot survey

We describe the footprint and input catalog for bright nights in the LAMOST Pilot Survey, which began in October 2011. Targets are selected from two stripes in the north and south Galactic Cap regions, centered at δ = 29°, with 10° width in declination, covering right ascensions of 135° to 290° and -30° to 30° re- spectively. We selected spectroscopic targets from a combination of the SDSS and 2MASS point source catalogs. The catalog of stars defining the field centers （as re- quired by the Shack-Hartmann wavefront sensor at the center of the LAMOST field） consists of all V 〈 8m stars from the Hipparcos catalog. We employ a statistical selection algorithm that assigns priorities to targets based on their positions in mul- tidimensional color/magnitude space. This scheme overemphasizes rare objects and de-emphasizes more populated regions of magnitude and color phase space, while en- suring a smooth, well-understood selection function. A demonstration of plate design is presented based on the Shack-Hartmann star catalog and an input catalog that was generated by our target selection routines.

The LEGUE input catalog for dark night observing in the LAMOST pilot survey

We outline the design of the dark nights portion of the LAMOST Pilot Survey, which began observations in 2011 October. In particular, we focus on Milky Way stellar candidates that are targeted for the LEGUE （LAMOST Experiment for Galactic Understanding and Exploration） survey. We discuss the regions of sky in which spectroscopic candidates were selected, and the motivations for selecting each of these sky areas. Some limitations due to the unique design of the telescope are discussed, including the requirement that a bright （V 〈 8） star be placed at the center of each plate for wavefront sensing and active optics corrections. The target selection categories and scientific goals motivating them are briefly discussed, followed by a detailed overview of how these selection functions were implemented. We illustrate the difference between the overall input catalog - Sloan Digital Sky Survey （SDSS） photometry - and the final targets selected for LAMOST observations.

Automatic determination of stellar atmospheric parameters and construction of stellar spectral templates of the Guoshoujing Telescope (LAMOST)

A number of spectroscopic surveys have been carried out or are planned to study the origin of the Milky Way. Their exploitation requires reliable automated methods and softwares to measure the fundamental parameters of the stars. Adopting the ULySS package, we have tested the effect of different resolutions and signal-to- noise ratios （SNR） on the measurement of the stellar atmospheric parameters （effective temperature Teff, surface gravity log g, and metaUicity [Fe/H]）. We show that ULySS is reliable for determining these parameters with medium-resolution spectra （R ～2000）. Then, we applied the method to measure the parameters of 771 stars selected in the commissioning database of the Guoshoujing Telescope （LAMOST）. The results were compared with the SDSS/SEGUE Stellar Parameter Pipeline （SSPP）, and we derived precisions of 167 K, 0.34dex, and 0.16dex for Teff, logg and [Fe/H] respectively. Furthermore, 120 of these stars are selected to construct the primary stellar spectral template library （Version 1.0） of LAMOST, and will be deployed as basic ingredients for the LAMOST automated parametrization pipeline.

An object correlation and maneuver detection approach for space surveillance

Object correlation and maneuver detection are persistent problems in space surveillance and maintenance of a space object catalog. We integrate these two prob- lems into one interrelated problem, and consider them simultaneously under a sce- nario where space objects only perform a single in-track orbital maneuver during the time intervals between observations. We mathematically formulate this integrated sce- nario as a maximum a posteriori （MAP） estimation. In this work, we propose a novel approach to solve the MAP estimation. More precisely, the corresponding posterior probability of an orbital maneuver and a joint association event can be approximated by the Joint Probabilistic Data Association （JPDA） algorithm. Subsequently, the ma- neuvering parameters are estimated by optimally solving the constrained non-linear least squares iterative process based on the second-order cone programming （SOCP） algorithm. The desired solution is derived according to the MAP criterions. The per- formance and advantages of the proposed approach have been shown by both theoret- ical analysis and simulation results. We hope that our work will stimulate future work on space surveillance and maintenance of a space object catalog.

Estimating stellar atmospheric parameters based on Lasso features

With the rapid development of large scale sky surveys like the Sloan Digital Sky Survey （SDSS）, GAIA and LAMOST （Guoshoujing telescope）, stellar spectra can be obtained on an ever-increasing scale. Therefore, it is necessary to estimate stel- lar atmospheric parameters such as Teff, log g and [Fe/H] automatically to achieve the scientific goals and make full use of the potential value of these observations. Feature selection plays a key role in the automatic measurement of atmospheric parameters. We propose to use the least absolute shrinkage selection operator （Lasso） algorithm to select features from stellar spectra. Feature selection can reduce redundancy in spectra, alleviate the influence of noise, improve calculation speed and enhance the robustness of the estimation system. Based on the extracted features, stellar atmospheric param- eters are estimated by the support vector regression model. Three typical schemes are evaluated on spectral data from both the ELODIE library and SDSS. Experimental results show the potential performance to a certain degree. In addition, results show that our method is stable when applied to different spectra.

An algorithm for preferential selection of spectroscopic targets in LEGUE

We describe a general target selection algorithm that is applicable to any survey in which the number of available candidates is much larger than the number of objects to be observed. This routine aims to achieve a balance between a smoothly- varying, well-understood selection function and the desire to preferentially select cer- tain types of targets. Some target-selection examples are shown that illustrate differentpossibilities of emphasis functions. Although it is generally applicable, the algorithm was developed specifically for the LAMOST Experiment for Galactic Understanding and Exploration （LEGUE） survey that will be carried out using the Chinese Guo Shou Jing Telescope. In particular, this algorithm was designed for the portion of LEGUE targeting the Galactic halo, in which we attempt to balance a variety of science goals that require stars at fainter magnitudes than can be completely sampled by LAMOST. This algorithm has been implemented for the halo portion of the LAMOST pilot sur- vey, which began in October 2011.