arXiv subjects

Ying Gao

Publications and source records attributed to Ying Gao.

76 records · Page 5Linked to original sources

arXiv2018

The spectral energy distribution of the hyperluminous, hot dust-obscured galaxy W2246$-$0526

Hot dust-obscured galaxies (Hot DOGs) are a luminous, dust-obscured population recently discovered in the WISE All-Sky survey. Multiwavelength follow-up observations suggest that they are mainly powered by accreting supermassive black holes (SMBHs), lying in dense environments, and being in the transition phase between extreme starburst and UV-bright quasars. Therefore, they are good candidates for studying the interplay between SMBHs, star formation and environment. W2246$-$0526 (thereafter, W2246), a Hot DOG at $z\sim4.6$, has been taken as the most luminous galaxy known in the Universe. Revealed by the multiwavelength images, the previous Herschel SPIRE photometry of W2246 is contaminated by a foreground galaxy (W2246f), resulting in an overestimation of its total IR luminosity by a factor of about 2. We perform the rest-frame UV/optical-to-far-IR spectral energy distribution (SED) analysis with SED3FIT and re-estimate its physical properties. The derived stellar mass $M_\star = 4.3\times10^{11}~M_\odot$ makes it be among the most massive galaxies with spectroscopic redshift $z>4.5$. Its structure is extremely compact and requires an effective mechanism to puff-up. Most of ($>95\%$) its IR luminosity is from AGN torus emission, revealing the rapid growth of the central SMBH. We also predict that W2246 may have a significant molecular gas reservoir based on the dust mass estimation.

astro-ph.GA↗

arXiv2017

Perception Driven Texture Generation

This paper investigates a novel task of generating texture images from perceptual descriptions. Previous work on texture generation focused on either synthesis from examples or generation from procedural models. Generating textures from perceptual attributes have not been well studied yet. Meanwhile, perceptual attributes, such as directionality, regularity and roughness are important factors for human observers to describe a texture. In this paper, we propose a joint deep network model that combines adversarial training and perceptual feature regression for texture generation, while only random noise and user-defined perceptual attributes are required as input. In this model, a preliminary trained convolutional neural network is essentially integrated with the adversarial framework, which can drive the generated textures to possess given perceptual attributes. An important aspect of the proposed model is that, if we change one of the input perceptual features, the corresponding appearance of the generated textures will also be changed. We design several experiments to validate the effectiveness of the proposed method. The results show that the proposed method can produce high quality texture images with desired perceptual properties.

cs.CV↗

arXiv2016

The most-luminous heavily-obscured quasars have a high merger fraction: morphological study of WISE-selected hot dust-obscured galaxies

Previous studies have shown that WISE-selected hyperluminous, hot dust-obscured galaxies (Hot DOGs) are powered by highly dust-obscured, possibly Compton-thick AGNs. High obscuration provides us a good chance to study the host morphology of the most luminous AGNs directly. We analyze the host morphology of 18 Hot DOGs at $z\sim3$ using Hubble Space Telescope/WFC3 imaging. We find that Hot DOGs have a high merger fraction ($62\pm 14 \%$). By fitting the surface brightness profiles, we find that the distribution of Sérsic indices in our Hot DOG sample peaks around 2, which suggests that most of Hot DOGs have transforming morphologies. We also derive the AGN bolometric luminosity ($\sim10^{14}L_\odot$) of our Hot DOG sample by using IR SEDs decomposition. The derived merger fraction and AGN bolometric luminosity relation is well consistent with the variability-based model prediction (Hickox et al. 2014). Both the high merger fraction in IR-luminous AGN sample and relatively low merger fraction in UV/optical-selected, unobscured AGN sample can be expected in the merger-driven evolutionary model. Finally, we conclude that Hot DOGs are merger-driven and may represent a transit phase during the evolution of massive galaxies, transforming from the dusty starburst dominated phase to the unobscured QSO phase.

astro-ph.GA↗

arXiv2013

Five Families of Three-Weight Ternary Cyclic Codes and Their Duals

As a subclass of linear codes, cyclic codes have applications in consumer electronics, data storage systems, and communication systems as they have efficient encoding and decoding algorithms. In this paper, five families of three-weight ternary cyclic codes whose duals have two zeros are presented. The weight distributions of the five families of cyclic codes are settled. The duals of two families of the cyclic codes are optimal.

cs.IT↗