4 citations · 6 across the 22 of their papers we have counts for
22 papers
Indirect evidence of the extinction bump within the dusty torus of SDSS J141945.50+524648.0
Ze Li, Gaoyang Chen, Qifan Cui +7
We present a multi-wavelength study of the quasar SDSS J141945.50524648.0 (), a member of the newly identified population of quasar-associated $2175\,\mathring{\mathrm…
Enhancing Photometric Redshift Estimation for LSST with a Hybrid LSTM-Mixture Density Network
Zhijian Luo, Yangyang Li, Xinyu Luo +4
Accurate photometric redshift (photo-) estimation and robust uncertainty quantification are essential for the LSST to achieve its precision cosmology goals. Traditional machine…
Tracing the kinematic perturbations of the Milky Way spiral arms with APOGEE DR17 and Gaia DR3
Xi-Can Tang, Zhi Li, Iulia T. Simion +4
Aims. We constrain the dynamical perturbations of the spiral arms in the Milky Way disk, based on the non-axisymmetric streaming motions of RGB stars revealed by APOGEE and \textit…
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…
Chasing the neutrino blazar candidates II: SED modeling with hadronic model
Hubing Xiao, Zhihao Ouyang, Lili Yang +6
Blazars are promising candidates for high energy neutrino sources, yet the physical origin of their neutrino emission remains uncertain. In this work, we extend our previous study…
Beyond Colors: Probing Redshifts from Galaxy Morphology in Single-band Images with ViT-MDNz
Zhijian Luo, Yangyang Li, Jianzhen Chen +5
To address the challenge of estimating redshifts when only single-band images are available, this study introduces a deep learning model named ViT-MDNz. Leveraging robust statistic…
LSTM-MDNz: Estimating Quasar Photometric Redshifts with an LSTM-Augmented Mixture Density Network
Jianzhen Chen, Zhijian Luo, Liping Fu +4
Quasar photometric redshifts are essential for studying cosmology and large-scale structures. However, their complex spectral energy distributions cause significant redshift-color…
BALNet: Deep Learning-Based Detection and Measurement of Broad Absorption Lines in Quasar Spectra
Yangyang Li, Zhijian Luo, Shaohua Zhang +5
Broad absorption line (BAL) quasars serve as critical probes for understanding active galactic nucleus (AGN) outflows, black hole accretion, and cosmic evolution. To address the li…
Identifying Dust-lane Spheroidal Galaxies in DESI Legacy Imaging Surveys Using Semi-Supervised Methods
Zhijian Luo, Jianzhen Chen, Wenxiang Pei +4
Dust-lane spheroidal galaxies (DLSGs) are unique astrophysical systems that exhibit the morphology of early-type galaxies (ETGs) but are distinguished by prominent dust lanes. Rece…
The averaged broadband spectral energy distribution study of Fermi bright BL Lac objects
Hubing Xiao, Haitao Cao, Rui Xue +6
The physics-determined broadband spectral energy distributions (SEDs) of blazars have been widely used to study the property during their flaring/outburst states, while the non-fla…
Detecting Galactic Rings in the DESI Legacy Imaging Surveys with Semi-Supervised Deep Learning
Jianzhen Chen, Zhijian Luo, Cheng Cheng +3
The ring structures of disk galaxies are vital for understanding galaxy evolution and dynamics. However, due to the scarcity of ringed galaxies and challenges in their identificati…
Galaxy Morphology Classification via Deep Semi-Supervised Learning with Limited Labeled Data
Zhijian Luo, Jianzhen Chen, Zhu Chen +4
Galaxy morphology classification plays a crucial role in understanding the structure and evolution of the universe. With galaxy observation data growing exponentially, machine lear…
The Quasar-associated 2175 Å Dust Absorbers in the SDSS DR16 Quasar Catalog
Shaohua Zhang, Yuchong Luo, Shangchun Xie +4
We present, for the first time, a systematic study of quasar-associated 2175 Å dust absorbers using spectroscopic data from the Sloan Digital Sky Survey (SDSS) Data Release 16 (DR1…
A random walk model for the evolution of the halo spin vector
Jun Hou, Zhijian Luo, Cedric G. Lacey
We follow the spin vector evolutions of well resolved dark matter haloes (containing more than 300 particles) in merger tree main branches from the Millennium and Millennium-II N-b…
Improving Photometric Redshift Estimation for CSST Mock Catalog Using SED Templates Calibrated with Perturbation Algorithm
Yicheng Li, Liping Fu, Zhu Chen +11
Photometric redshifts of galaxies obtained by multi-wavelength data are widely used in photometric surveys because of its high efficiency. Although various methods have been develo…
The Study of Jet Formation Mechanism in Fermi Blazars
Shangchun Xie, Zhihao Ouyang, Jingyu Wu +5
The origin of jet launching mainly comes from two mechanisms: the BZ mechanism and the BP mechanism. However, it is in debate which one is dominating in blazars. In this work, we u…
Photometric Redshift Estimation for CSST Survey with LSTM Neural Networks
Zhijian Luo, Yicheng Li, Junhao Lu +11
Accurate estimation of photometric redshifts (photo-s) is crucial for cosmological surveys. Various methods have been developed for this purpose, such as template fitting method…
Cross-Survey Image Transformation: Enhancing SDSS and DECaLS Images to Near-HSC Quality for Advanced Astronomical Analysis
Zhijian Luo, Shaohua Zhang, Jianzhen Chen +5
This study focuses on transforming galaxy images between astronomical surveys, specifically enhancing images from the Sloan Digital Sky Survey (SDSS) and the Dark Energy Camera Leg…
A comparative study of ultraluminous infrared galaxies in the IRAS and SDSS Surveys
Shaohua Zhang, Zhijian Luo, Xiheng Shi +3
We present a comprehensive study of Ultraluminous Infrared Galaxies (ULIRGs), leveraging data from the IRAS Faint Source Catalogue (FSC) and the spectroscopic catalog in the Sloan…
Imputation of Missing Photometric Data and Photometric Redshift Estimation for CSST
Zhijian Luo, Zhirui Tang, Zhu Chen +10
Accurate photometric redshift (photo-) estimation requires support from multi-band observational data. However, in the actual process of astronomical observations and data proce…
Identification of 4FGL uncertain sources at Higher Resolutions with Inverse Discrete Wavelet Transform
Haitao Cao, Hubing Xiao, Zhijian Luo +2
In the forthcoming era of big astronomical data, it is a burden to find out target sources from ground-based and space-based telescopes. Although Machine Learning (ML) methods have…
Estimating Photometric Redshift from Mock Flux for CSST Survey by using Weighted Random Forest
Junhao Lu, Zhijian Luo, Zhu Chen +10
Accurate estimation of photometric redshifts (photo-) is crucial in studies of both galaxy evolution and cosmology using current and future large sky surveys. In this study, we…