62 citations · 259 across the 17 of their papers we have counts for
15 papers · 1 filter
Growth from KiDS: Stellar mass assembly of galaxies since z=2 in the light of Kilo-Degree Survey
Qingshan Wang, Antonios Katsianis, Nicola R. Napolitano +10
We measure the galaxy stellar mass function at using 28M galaxies from the KiDS DR4 which spans an effective survey area of 676.9 deg. Combining nine-band photometry…
DenseLens -- Using DenseNet ensembles and information criteria for finding and rank-ordering strong gravitational lenses,
Bharath Chowdhary Nagam, Léon V. E. Koopmans, Edwin A. Valentijn +5
Convolutional neural networks (CNNs) are the state-of-the-art technique for identifying strong gravitational lenses. Although they are highly successful in recovering genuine lens…
Toward a stellar population catalog in the Kilo Degree Survey: the impact of stellar recipes on stellar masses and star formation rates
Linghua Xie, Nicola R. Napolitano, Xiaotong Guo +11
The Kilo Degree Survey (KiDS) is currently the only sky survey providing optical () plus near-infrared (NIR, ) seeing matched photometry over an area larger than 100…
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…
Velocity-resolved Reverberation Mapping of Changing-look Active Galactic Nucleus NGC~4151 During Outburst Stage: Evidence for Kinematics Evolution of Broad-line Region
Sha-Sha Li, Hai-Cheng Feng, H. T. Liu +6
Changing-look active galactic nucleus NGC~4151, which has attracted a lot of attention, is undergoing the second dramatic outburst stage in its evolutionary history. To investigate…
Galaxy morphoto-Z with neural Networks (GaZNets). I. Optimized accuracy and outlier fraction from Imaging and Photometry
Rui Li, Nicola R. Napolitano, Haicheng Feng +8
In the era of large sky surveys, photometric redshifts (photo-z) represent crucial information for galaxy evolution and cosmology studies. In this work, we propose a new Machine Le…
Galaxy Spectra neural Networks (GaSNets). I. Searching for strong lens candidates in eBOSS spectra using Deep Learning
Fucheng Zhong, Rui Li, Nicola R. Napolitano
With the advent of new spectroscopic surveys from ground and space, observing up to hundreds of millions of galaxies, spectra classification will become overwhelming for standard a…
Inferring galaxy dark halo properties from visible matter with Machine Learning
Rodrigo von Marttens, Luciano Casarini, Nicola R. Napolitano +6
Next-generation surveys will provide photometric and spectroscopic data of millions to billions of galaxies with unprecedented precision. This offers a unique chance to improve our…
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…
Central velocity dispersion catalog of LAMOST-DR7 galaxies
Nicola R. Napolitano, Giuseppe D'Ago, Crescenzo Tortora +6
The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) is a major facility to carry out spectroscopic surveys for cosmology and galaxy evolution studies. The sevent…
Constraining the Rastall parameters in static spacetimes with galaxy-scale strong gravitational lensing
Rui Li, Jiancheng Wang, Zhaoyi Xu +1
Recently, Rastall gravity is undergoing a significant surge in popularity. We obtain a power-law total mass-density profile for the inner region (within several effective radius) o…
Using deep Residual Networks to search for galaxy-Lyα emitter lens candidates based on spectroscopic-selection
Rui Li, Yiping Shu, Jianlin Su +4
More than one hundred galaxy-scale strong gravitational lens systems have been found by searching for the emission lines coming from galaxies with redshifts higher than the lens ga…
A scenario on the power-law total mass-density profile of the inner regions of early-type-galaxies
Rui Li, Zhaoyi Xu, Jiancheng Wang +1
We naturally obtain a power-law total mass-density profile for the inner regions (within several effective radius) of early-type galaxies(ETGs) from space-time structures, which ar…
Strong-lensing Measurement of the Mass-density Profile out to 3 Effective Radii for Early-type Galaxies
Rui Li, Yiping Shu, Jiangcheng Wang
We measure the total mass-density profiles out to three effective radii for a sample of 63 , massive early-type galaxies (ETGs) acting as strong gravitational lenses th…
The discrepancy between Einstein mass and dynamical mass for SIS and power-law mass models
Rui Li, Jiancheng Wang, Yiping Shu +1
We investigate the discrepancy between the two-dimensional projected lensing mass and the dynam- ical mass for an ensemble of 97 strong gravitational lensing systems discovered by…