Selection and Mid-infrared Spectroscopy of Ultraluminous Star-Forming Galaxies at z~2

Starting from a sample of 24 \micron\ sources in the Extended Groth Strip, we use 3.6 to 8 \micron\ color criteria to select ultraluminous infrared galaxies (ULIRGs) at $z\sim2$. Spectroscopy from 20-38 \micron\ of 14 objects verifies their nature and gives their redshifts. Multi-wavelength data for these objects imply stellar masses ${>}10^{11}$ \Msun\ and star formation rates $\ge$410 \Msun yr$^{-1}$. Four objects of this sample observed at 1.6 \micron\ (rest-frame visible) with {\it HST}/WFC3 show diverse morphologies, suggesting that multiple formation processes create ULIRGs. Four of the 14 objects show signs of active galactic nuclei, but the luminosity appears to be dominated by star formation in all cases.Comment: 33 pages, 13 figures, accepted by Ap

Structure and morphology of X-ray selected AGN hosts at 1<z<3 in CANDELS-COSMOS field

We analyze morphologies of the host galaxies of 35 X-ray selected active galactic nucleus (AGNs) at $z\sim2$ in the Cosmic Evolution Survey (COSMOS) field using Hubble Space Telescope/WFC3 imaging taken from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS). We build a control sample of 350 galaxies in total, by selecting ten non-active galaxies drawn from the same field with the similar stellar mass and redshift for each AGN host. By performing two dimensional fitting with GALFIT on the surface brightness profile, we find that the distribution of S$\`e$rsic index (n) of AGN hosts does not show a statistical difference from that of the control sample. We measure the nonparametric morphological parameters (the asymmetry index A, the Gini coefficient G, the concentration index C and the M20 index) based on point source subtracted images. All the distributions of these morphological parameters of AGN hosts are consistent with those of the control sample. We finally investigate the fraction of distorted morphologies in both samples by visual classification. Only $\sim$15% of the AGN hosts have highly distorted morphologies, possibly due to a major merger or interaction. We find there is no significant difference in the distortion fractions between the AGN host sample and control sample. We conclude that the morphologies of X-ray selected AGN hosts are similar to those of nonactive galaxies and most AGN activity is not triggered by major merger.Comment: 5 pages, 3 figures, accepted for publication in The Astrophysical Journal Letter

An Open Unified Addressing System for 6G Communication Networks

With the rapid and continuous development of the Internet, it is foreseeable that current addressing schemes and fixed-length IP addresses would create further bottlenecks and limitations in realizing future 6G networking requirements, such as massive connections, resource-constrained communication, and heterogeneous hyper interconnections and guaranteeing agreement-based services and KPIs. Moreover, the locator-based addressing semantic is unsuitable for mobile and content-oriented networks. Thus, this paper proposes the Open Unified Addressing (OUA) system, a novel, flexible, multi-semantic and hierarchical addressing architecture that better supports the flexibility and extensibility of the Internet protocol framework in the context of 6G Communications. The OUA addresses several limitations in the current IP protocol and improves communication efficiency. According to the evaluation with two typical forwarding models, the results show that the OUA system has almost no impact on forwarding delay. Moreover, it can provide scalable addressing spaces and shorten the route convergence time

Progressive Text-to-Image Diffusion with Soft Latent Direction

In spite of the rapidly evolving landscape of text-to-image generation, the synthesis and manipulation of multiple entities while adhering to specific relational constraints pose enduring challenges. This paper introduces an innovative progressive synthesis and editing operation that systematically incorporates entities into the target image, ensuring their adherence to spatial and relational constraints at each sequential step. Our key insight stems from the observation that while a pre-trained text-to-image diffusion model adeptly handles one or two entities, it often falters when dealing with a greater number. To address this limitation, we propose harnessing the capabilities of a Large Language Model (LLM) to decompose intricate and protracted text descriptions into coherent directives adhering to stringent formats. To facilitate the execution of directives involving distinct semantic operations-namely insertion, editing, and erasing-we formulate the Stimulus, Response, and Fusion (SRF) framework. Within this framework, latent regions are gently stimulated in alignment with each operation, followed by the fusion of the responsive latent components to achieve cohesive entity manipulation. Our proposed framework yields notable advancements in object synthesis, particularly when confronted with intricate and lengthy textual inputs. Consequently, it establishes a new benchmark for text-to-image generation tasks, further elevating the field's performance standards.Comment: 14 pages, 15 figure

Fine-grained Appearance Transfer with Diffusion Models

Image-to-image translation (I2I), and particularly its subfield of appearance transfer, which seeks to alter the visual appearance between images while maintaining structural coherence, presents formidable challenges. Despite significant advancements brought by diffusion models, achieving fine-grained transfer remains complex, particularly in terms of retaining detailed structural elements and ensuring information fidelity. This paper proposes an innovative framework designed to surmount these challenges by integrating various aspects of semantic matching, appearance transfer, and latent deviation. A pivotal aspect of our approach is the strategic use of the predicted $x_0$ space by diffusion models within the latent space of diffusion processes. This is identified as a crucial element for the precise and natural transfer of fine-grained details. Our framework exploits this space to accomplish semantic alignment between source and target images, facilitating mask-wise appearance transfer for improved feature acquisition. A significant advancement of our method is the seamless integration of these features into the latent space, enabling more nuanced latent deviations without necessitating extensive model retraining or fine-tuning. The effectiveness of our approach is demonstrated through extensive experiments, which showcase its ability to adeptly handle fine-grained appearance transfers across a wide range of categories and domains. We provide our code at https://github.com/babahui/Fine-grained-Appearance-TransferComment: 14 pages, 15 figure

Piercing through Highly Obscured and Compton-thick AGNs in the Chandra Deep Fields. II. Are Highly Obscured AGNs the Missing Link in the Merger-Triggered AGN-Galaxy Coevolution Models?

By using a large highly obscured ($N_{\rm H} > 10^{23}\ \rm cm^{-2}$) AGN sample (294 sources at $z \sim 0-5$) selected from detailed X-ray spectral analyses in the deepest Chandra surveys, we explore distributions of these X-ray sources in various optical/IR/X-ray color-color diagrams and their host-galaxy properties, aiming at characterizing the nuclear obscuration environment and the triggering mechanism of highly obscured AGNs. We find that the refined IRAC color-color diagram fails to identify the majority of X-ray selected highly obscured AGNs, even for the most luminous sources with ${\rm log}\,L_{\rm X}\, \rm (erg\ s^{-1}) > 44$. Over 80% of our sources will not be selected as heavily obscured candidates using the flux ratio of $f_{\rm 24 \mu m}\, /\,f_R > 1000$ and $R - K > 4.5$ criteria, implying complex origins and conditions for the obscuring materials that are responsible for the heavy X-ray obscuration. The average star formation rate of highly obscured AGNs is similar to that of stellar mass- ($M_*$-) and $z$-controlled normal galaxies, while the lack of quiescent hosts is observed for the former. Partial correlation analyses imply that highly obscured AGN activity (traced by $L_{\rm X}$) appears to be more fundamentally related to $M_*$, and no dependence of $N_{\rm H}$ on either $M_*$ or SFR is detected. Morphology analyses reveal that 61% of our sources have a significant disk component, while only 27% of them exhibit irregular morphological signatures. These findings together point toward a scenario where secular processes (e.g., galactic-disk instabilities), instead of mergers, are most probable to be the leading mechanism that triggers accretion activities of X-ray-selected highly obscured AGNs.Comment: 23 pages, 12 figures, 3 tables, resubmitted to ApJ after addressing referee's comment

Precision Space Observation Technique for Geological Hazard Monitoring and Early Warning

Since the 21st century, with the deterioration of the world environment and the intense human activities, geological disasters have been occurred more frequently. Precision space observation technology is an important means for geological disasters monitoring and early warning. In this paper, the characteristics and monitoring methods of common geological disasters are introduced. The technical characteristics and application of InSAR, LiDAR, high resolution remote sensing and GNSS are discussed. The integration of high precision spatial monitoring technology are reviewed and prospected. Finally, the future trends of the geological disaster monitoring and early warning technology are summarized