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Jianhong Hu

Publications and source records attributed to Jianhong Hu.

5 recordsLinked to original sources

Optically Selected Superthin Galaxies Remain Thin in the Near-infrared

We investigate whether galaxies identified as superthin in optical images remain superthin in the near-infrared (NIR), and how their extreme disk morphology is related to environment. From a nearby volume-limited sample, we select 210 superthin galaxies using two-dimensional bulge/disk decomposition of SDSS $r$-band images, requiring the disk component to have a minor-to-major axis ratio $b/a<1/9$. We measure disk shapes from SDSS $griz$ to UKIDSS $JHK$ bands. Both the major- and minor-axis scales decrease from the optical to the NIR, reaching $\sim0.6$ of their $r$-band values in the $K$ band, but the disk axis ratio remains nearly unchanged. Thus, optically selected superthin galaxies remain superthin in the NIR, suggesting that any NIR-dominant thick component, if present, is not prominent enough to alter the fitted disk shape. Reanalysis of our sample and a previous superthin sample shows that earlier reported NIR thickening is mainly due to a magnitude- and band-dependent bias in one-dimensional fitting. We further compare their environments with matched control samples using projected cross-correlations, reconstructed local overdensities, and large-scale-structure classifications. Superthin galaxies show lower clustering on $\sim0.1$--$1\,h^{-1}\,\mathrm{Mpc}$ scales and lower overdensities at $1\,h^{-1}\,\mathrm{Mpc}$, but similar large-scale clustering and no clear residual dependence on large-scale-structure type. These results are consistent with a higher central-galaxy fraction and lower satellite fraction in the superthin sample, while the similar large-scale clustering points to comparable typical halo masses relative to the controls. This halo-occupation interpretation is qualitatively consistent with simulation-based scenarios in which high host-halo spin helps build extended thin disks, although the present data do not directly measure halo spin.

astro-ph.GA

APOSTLE vs. AURIGA Simulations: How Subgrid Models Shape Milky Way Analogs

Despite significant progress in cosmological simulations of galaxy formation, the role of subgrid physics in shaping the detailed properties of galaxies remains incompletely understood. In this work, we analyze two sets of zoom-in simulations that share identical initial conditions but adopt distinct implementations of baryonic physics, enabling a controlled comparison of their predictions. We examine the stellar properties, morphological structures, and satellite populations of the simulated galaxies at $z=0$. We find that AURIGA galaxies systematically exhibit higher stellar masses and surface densities than their APOSTLE counterparts. These differences are primarily driven by variations in the efficiency of gas cooling from the circumgalactic medium (CGM) into the star-forming gas. Both simulations form well-defined disk galaxies; however, AURIGA systems generally display higher disk-to-total mass ratios, earlier disk formation, and more prominent dynamical structures such as bars and spiral arms. Nevertheless, strongly disk-dominated systems are present in both simulations, although they do not arise in the same host haloes. The vertical disk structure in both simulations is well described by a sech density profile, with scale heights below ~ 1 kpc in the inner regions. The satellite populations also differ, with AURIGA producing systematically more massive satellites, including a ~ 0.3 dex increase in the most massive system, while the number of satellites above $10^6 M_{\odot}$ remains comparable in most halo pairs. Both simulations reproduce similar satellite stellar mass--metallicity relations, albeit ~ 0.25 dex higher than observation. This comparative study therefore provides useful benchmarks for future efforts to better constrain galaxy formation models.

astro-ph.GA

Formation of super-thin galaxies in Illustris-TNG

Superthin galaxies are observed to have stellar disks with extremely small minor-to-major axis ratios. In this work, we investigate the formation of superthin galaxies in the TNG100 simulation. We trace the merger history and investigate the evolution of galaxy properties of a selected sample of superthin galaxies and a control sample of galaxies that share the same joint probability distribution in the stellar-mass and color diagram. Through making comparisons between the two galaxy samples, we find that present-day superthin galaxies had similar morphologies as the control sample counterparts at higher redshifts, but have developed extended flat `superthin' morphologies since $z \sim 1$. During this latter evolution stage, superthin galaxies undergo overwhelmingly higher frequency of prograde mergers (with orbit-spin angle $θ_{\rm orb} \leqslant 40^\circ$). Accordingly the spins of their dark matter halos have grown significantly and become noticeably higher than that of their normal disk counterparts. This further results in the buildup of their stellar disks at larger distances much beyond the regimes of normal disk galaxies. We also discuss the formation scenario of those superthin galaxies that live in larger dark matter halos as satellite galaxies therein.

astro-ph.GA

On the existence, rareness and uniqueness of quenched HI-rich galaxies in the local Universe

Using data from ALFALFA, xGASS, HI-MaNGA and the Sloan Digital Sky Survey (SDSS), we identify a sample of 47 "red but HI-rich"(RR) galaxies with $NUV-r > 5$ and unusually high HI-to-stellar mass ratios. We compare the optical properties and local environments between the RR galaxies and a control sample of "red and HI-normal"(RN) galaxies that are matched in stellar mass and color. The two samples are similar in the optical properties typical of massive red (quenched) galaxies in the local Universe. The RR sample tends to be associated with slightly lower-density environments and has lower clustering amplitudes and smaller neighbor counts at scales from several kiloparsecs to a few Megaparsecs. The results are consistent with the RR galaxies preferentially being located at the center of low-mass halos, with a median halo mass $\sim 10^{12}h^{-1}M_{\odot}$ compared to $\sim 10^{12.5}h^{-1}M_{\odot}$ for the RN sample. This result is confirmed by the SDSS group catalog which reveals a central fraction of 89% for the RR sample, compared to $\sim 60\%$ for the RN sample. If assumed to follow the HI size-mass relation of normal galaxies, the RR galaxies have an average HI-to-optical radius ratio of $R_{HI}/R_{90}\sim 4$, four times the average ratio for the RN sample. We compare our RR sample with similar samples in previous studies, and quantify the population of RR galaxies using the SDSS complete sample. We conclude that the RR galaxies form a unique but rare population, accounting for only a small fraction of the massive quiescent galaxy population. We discuss the formation scenarios of the RR galaxies.

astro-ph.GA

A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization

Cross-view geo-localization is a task of matching the same geographic image from different views, e.g., unmanned aerial vehicle (UAV) and satellite. The most difficult challenges are the position shift and the uncertainty of distance and scale. Existing methods are mainly aimed at digging for more comprehensive fine-grained information. However, it underestimates the importance of extracting robust feature representation and the impact of feature alignment. The CNN-based methods have achieved great success in cross-view geo-localization. However it still has some limitations, e.g., it can only extract part of the information in the neighborhood and some scale reduction operations will make some fine-grained information lost. In particular, we introduce a simple and efficient transformer-based structure called Feature Segmentation and Region Alignment (FSRA) to enhance the model's ability to understand contextual information as well as to understand the distribution of instances. Without using additional supervisory information, FSRA divides regions based on the heat distribution of the transformer's feature map, and then aligns multiple specific regions in different views one on one. Finally, FSRA integrates each region into a set of feature representations. The difference is that FSRA does not divide regions manually, but automatically based on the heat distribution of the feature map. So that specific instances can still be divided and aligned when there are significant shifts and scale changes in the image. In addition, a multiple sampling strategy is proposed to overcome the disparity in the number of satellite images and that of images from other sources. Experiments show that the proposed method has superior performance and achieves the state-of-the-art in both tasks of drone view target localization and drone navigation. Code will be released at https://github.com/Dmmm1997/FSRA

cs.CV