Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Jun Ma is active.

Publication


Featured researches published by Jun Ma.


The Astronomical Journal | 2015

SOUTH GALACTIC CAP u-BAND SKY SURVEY (SCUSS): DATA REDUCTION

Hu Zou; Zhaoji Jiang; Xu Zhou; Zhenyu Wu; Jun Ma; Xiaohui Fan; Zhou Fan; Boliang He; Yipeng Jing; Michael P. Lesser; Cheng Li; Jundan Nie; Shiyin Shen; Jiali Wang; Tianmeng Zhang; Zhimin Zhou

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 2.3 Bok telescope at Kitt Peak. The survey observations started in 2010 and ended in 2013. The final survey area is about 5000 deg(2) with a median 5s point source limiting magnitude of similar to 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 Canada-France-Hawaii Telescope Legacy surveys.


Publications of the Astronomical Society of the Pacific | 2015

Capability of Quasar Selection by Combining SCUSS and SDSS Observations

Hu Zou; Xue-Bing Wu; Xu Zhou; Shu Wang; Linhua Jiang; Xiaohui Fan; Zhou Fan; Zhaoji Jiang; Yipeng Jing; Michael P. Lesser; Cheng Li; Jun Ma; Jundan Nie; Shiyin Shen; Jiali Wang; Zhenyu Wu; Tianmeng Zhang; Zhimin Zhou

The South Galactic Cap u-band Sky Survey (SCUSS) provides a deep u-band imaging of about 5000 deg(2) in south Galactic cap. It is about 1.5 mag deeper than the SDSS u-band. In this article, we evaluate the capability of quasar selection using both SCUSS and SDSS data, based on considerations of the deep SCUSS u-band imaging and two-epoch u-band variability. We find that the combination of the SCUSS u-band and the SDSS griz-band allows us to select more faint quasars and more quasars at redshift around 2.2 than the selection that uses only the SDSS ugriz data. Quasars have significant u-band variabilities. The fraction of quasars with large two-epoch variability is much higher than that of stars. The selection by variability can select both low-redshift quasars with ultraviolet excess and mid-redshift (2 < z < 3.5) quasars where quasar selection by optical colors is inefficient. The above two selections are complementary and make full use of the SCUSS u-band advantages.


The Astrophysical Journal | 2015

AN EXTENDED VIEW OF THE PISCES OVERDENSITY FROM THE SCUSS SURVEY

Jundan Nie; M. Smith; V. Belokurov; X. Fan; Zhou Fan; M. J. Irwin; Zhongyi Jiang; Yipeng Jing; S. E. Koposov; Michael P. Lesser; Jun Ma; Shiyin Shen; J. Wang; Z. Wu; Tao Zhang; Xingtai Zhou; Zhimin Zhou; Hu Zou

SCUSS is a u-band photometric survey covering about 4000 square degree of the South Galactic Cap, reaching depths of up to 23 mag. By extending around 1.5 mag deeper than SDSS single-epoch u data, SCUSS is able to probe much a larger volume of the outer halo, i.e. with SCUSS data blue horizontal branch (BHB) stars can trace the outer halo of the Milky Way as far as 100-150 kpc. Utilizing this advantage we combine SCUSS u band with SDSS DR9 gri photometric bands to identify BHB stars and explore halo substructures. We confirm the existence of the Pisces overdensity, which is a structure in the outer halo (at around 80 kpc) that was discovered using RR Lyrae stars. For the first time we are able to determine its spatial extent, finding that it appears to be part of a stream with a clear distance gradient. The stream, which is ~5 degrees wide and stretches along ~25 degrees, consists of 20-30 BHBs with a total significance of around 6sigma over the background. Assuming we have detected the entire stream and that the progenitor has fully disrupted, then the number of BHBs suggests the original system was similar to smaller classical or a larger ultra-faint dwarf galaxy. On the other hand, if the progenitor still exists, it can be hunted for by reconstructing its orbit from the distance gradient of the stream. This new picture of the Pisces overdensity sheds new light on the origin of this intriguing system.


The Astronomical Journal | 2015

Batc 15 band photometry of the open cluster ngc 188

J.-J. Wang; Jun Ma; Zhenyu Wu; Song Wang; Xu Zhou

This paper presents CCD multicolour photometry for the old open cluster NGC 188. The observations were carried out as a part of the Beijing--Arizona--Taiwan--Connecticut Multicolour Sky Survey from 1995 February to 2008 March, using 15 intermediate-band filters covering 3000--10000 AA. By fitting the Padova theoretical isochrones to our data, the fundamental parameters of this cluster are derived: an age of


Publications of the Astronomical Society of the Pacific | 2015

An Investigation of the Absolute Proper Motions of the SCUSS Catalog

Xiyan Peng; Zhaoxiang Qi; Zhenyu Wu; Jun Ma; Cuihua Du; Xu Zhou; Yong Yu; Zheng-Hong Tang; Zhaoji Jiang; Hu Zou; Zhou Fan; Xiaohui Fan; M. Smith; Linhua Jiang; Yipeng Jing; M. G. Lattanzi; B. J. McLean; Michael P. Lesser; Jundan Nie; Shiyin Shen; Jiali Wang; Tianmeng Zhang; Zhimin Zhou; Songhu Wang

t=7.5pm 0.5


Publications of the Astronomical Society of the Pacific | 2017

Project Overview of the Beijing-Arizona Sky Survey

Hu Zou; Xu Zhou; Xiaohui Fan; Tianmeng Zhang; Zhimin Zhou; Jundan Nie; Xiyan Peng; Ian McGreer; Linhua Jiang; Arjun Dey; Dongwei Fan; Boliang He; Zhaoji Jiang; Dustin Lang; Michael P. Lesser; Jun Ma; Shude Mao; David J. Schlegel; Jiali Wang

Gyr, a distant modulus of


The Astronomical Journal | 2015

STRUCTURAL PARAMETERS FOR 10 HALO GLOBULAR CLUSTERS IN M33

Jun Ma

(m-M)_0=11.17pm0.08


The Astronomical Journal | 2017

The First Data Release of the Beijing-Arizona Sky Survey

Hu Zou; Tianmeng Zhang; Zhimin Zhou; Jundan Nie; Xiyan Peng; Xu Zhou; Linhua Jiang; Zheng Cai; Arjun Dey; Xiaohui Fan; Dongwei Fan; Yucheng Guo; Boliang He; Zhaoji Jiang; Dustin Lang; Michael P. Lesser; Zefeng Li; Jun Ma; Shude Mao; Ian McGreer; David J. Schlegel; Yali Shao; Jiali Wang; Shu-Xiao Wang; Jin Wu; Xiaohan Wu; Qian Yang; Minghao Yue

, and a reddening of


Astrophysics and Space Science | 2016

Spectral identification of the u-band variable sources in two LAMOST fields

Tian-Wen Cao; Ming Yang; Hong Wu; Tianmeng Zhang; J. R. Shi; Haotong Zhang; Fan Yang; Jingkun Zhao; Xu Zhou; Zhou Fan; Zhaoji Jiang; Jun Ma; Jiali Wang; Zhenyu Wu; Hu Zou; Zhimin Zhou; Jundan Nie; A-Li Luo; XueBing Wu; Yong-Heng Zhao

E(B-V)=0.036pm0.010


The Astronomical Journal | 2015

Spectral energy distributions and masses of 304 m31 old star clusters

Jun Ma; Song Wang; Zhenyu Wu; Tianmeng Zhang; Hu Zou; Jundan Nie; Zhiming Zhou; Xu Zhou; Jianghua Wu; Cuihua Du; Qirong Yuan

. The radial surface density profile of NGC 188 is obtained by star count. By fitting the King model, the structural parameters of NGC 188 are derived: a core radius of

Collaboration


Dive into the Jun Ma's collaboration.

Top Co-Authors

Avatar

Hu Zou

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar

Jundan Nie

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar

Xu Zhou

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar

Tianmeng Zhang

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar

Zhaoji Jiang

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar

Zhimin Zhou

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar

Jiali Wang

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Zhou Fan

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge