75 citations · 321 across the 31 of their papers we have counts for
9 papers · 1 filter
Spectral Microlensing of Extragalactic H II Regions by Stellar-Mass Black Holes
Dezi Liu
Most of the Milky Way's predicted stellar-mass black holes remain hidden, especially at high Galactic latitudes or in the Galactic halo, where traditional dense-field stellar micro…
Comparative analysis of missing data imputation methods for CSST survey: Impact on photometric redshift estimation performance
Ling Wang, Zhu Chen, Zhijian Luo +42
Improving the accuracy of photometric redshifts (photo-) is essential for reliable statistical studies of cosmology and galaxy evolution. However, missing photometric bands are…
CFHT MegaCam Two Deep Fields Imaging Survey (2DFIS) II: Decoding the Lensing Profile of a "Rotating" Cluster with Deep CFHT Imaging
Yicheng Li, Liping Fu, Wentao Luo +15
We present a multi-wavelength analysis of the galaxy cluster RXCJ0110.0+1358 (), a rotating cluster candidate, combining deep CFHT imaging, SDSS photometry, spectroscopic…
Large Scale Overdensity of Lyman Break Galaxies Around the z=6.3 Ultraluminous Quasar J0100+2802
Maria Pudoka, Feige Wang, Xiaohui Fan +8
We study the environment of the z=6.33 ultraluminous quasar SDSS J010013.02+280225.8 (J0100) to understand its association with large-scale structure. Theoretical models propose hi…
Galaxy Light profile neural Networks (GaLNets). II. Bulge-Disc decomposition in optical space-based observations
Chen Qiu, Nicola R. Napolitano, Rui Li +12
Bulge-disk (B-D) decomposition is an effective diagnostic to characterize the galaxy morphology and understand its evolution across time. So far, high-quality data have allowed det…
Identification of new M31 star cluster candidates from PAndAS images using convolutional neural networks
Shoucheng Wang, Bingqiu Chen, Jun Ma +7
Context.Identification of new star cluster candidates in M31 is fundamental for the study of the M31 stellar cluster system. The machine-learning method convolutional neural networ…
Lenses In VoicE (LIVE): Searching for strong gravitational lenses in the VOICE@VST survey using Convolutional Neural Networks
Fabrizio Gentile, Crescenzo Tortora, Giovanni Covone +8
We present a sample of 16 likely strong gravitational lenses identified in the VST Optical Imaging of the CDFS and ES1 fields (VOICE survey) using Convolutional Neural Networks (CN…
Deep CFHT Y-band Imaging of VVDS-F22 Field: II. Quasar Selection and Quasar Luminosity Function
Jinyi Yang, Xue-Bing Wu, Dezi Liu +7
We report the result of a faint quasar survey in a one square degree field. The aim is to test the Y-K/g-z and J-K/i-Y color selection criteria for quasars at faint magnitude, to o…
Deep CFHT Y-band imaging of VVDS-F22 field: I. data products and photometric redshifts
Dezi Liu, Jinyi Yang, Shuo Yuan +5
We present our deep -band imaging data of a two square degree field within the F22 region of the VIMOS VLT Deep Survey. The observations were conducted using the WIRCam instrume…