arXiv subjects

Shuanghao Shu

Publications and source records attributed to Shuanghao Shu.

9 recordsLinked to original sources

arXiv2026

A Statistical Study of HI Gas in AGN-Hosting and Satellite Galaxies from ALFALFA and FASHI

We investigate the relative importance of Active Galactic Nucleus (AGN) feedback and environmental processes using a large sample of HI galaxies from the ALFALFA and FASHI surveys. By applying the optical spectroscopy from SDSS DR7/DR8 and the DESI survey, we analyse the gas content and physical properties of AGN-hosting galaxies in group environments. Our results show that AGN-hosting galaxies exhibit significantly suppressed star formation rates and HI gas fraction, approximately one order of magnitude lower than star-forming counterparts, regardless of their group-centric position. AGN-hosting satellites exhibit a significant and persistent deficit in both gas fraction and SFR relative to normal satellites without AGN, even at the halo virial radius (R/R180 approx 1). This suggests that cold gas depletion is primarily driven by internal AGN feedback before these galaxies experience intense environmental interactions. The relatively flat radial profiles of gas fraction and sSFR further indicate that the evolution of AGN-hosting satellites is governed by internal physical processes rather than environmental interactions. Moreover, the apparent increase in HI gas at R/R180 < 0.3 is identified as an artifact of beam confusion. We conclude that for the AGN-hosting population, internal feedback is likely the prior quenching mechanism, while environmental effects act as a secondary, subsequent process.

astro-ph.GA↗

arXiv2026

Cross-Comparison of Galaxies Detected in the CSST Spectroscopic Survey and the SKA HI Survey

We present a forward-modeling framework to forecast the galaxies detected in the Chinese Space Station Survey Telescope (CSST) spectroscopic survey and the Square Kilometre Array (SKA) HI survey. Starting from the L-Galaxies 2020 semi-analytic model run on the Millennium-II N-body simulation (MS-II), the cold gas in galaxies is partitioned into atomic and molecular components self-consistently within the model. We further model the emission-lines (H $α$, H $β$, O III) relevant for the slitless spectrograph of the CSST in a post-processing step. We construct mock lightcones using the Mock Map Facility (MoMaF) approach, simulating the neutral hydrogen (HI) data cubes representing a 2000 hour SKA-Mid spectral line observation from redshifts 0.25--0.5, and employ the Source Finding Application 2(SOFIA-2) source-finding package to generate an HI galaxy catalog. In parallel, we apply the CSST selection function and noise model to obtain a realistic catalog of emission-line galaxies; the emission-line signal is proportional to the star formation rate. These products allow us to cross compare the galaxy samples and assess the synergy between CSST and SKA. We study the correlations of the HI and the emission-line signal with the halo mass, HI mass, and the stellar mass, and the baryonic Tully-Fisher relation (BTFR). We also perform stacking analysis of the HI signal from the CSST-selected sample, which probes the HI content in galaxies with low HI mass. Finally, we derive the optical-HI cross-correlation power spectrum of the galaxies, and measure the bias of these galaxies. These results can provide useful insight on the cold gas and stellar content of the galaxies.

astro-ph.GA↗

arXiv2026

FATHOMER survey: III. Preliminary HI galaxy identification results

We present the HI galaxy observation results of the FATHOMER (FAst neuTral HydrOgen intensity Mapping ExpeRiment), a pilot drift scan survey by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The survey comprises 28 hours of observations over 7 nights in 2021, covering a $60\, °^2$ sky area in the frequency range 1.05-1.45 GHz. The HI galaxies are identified using both a matched-filtering algorithm and the SoFiA source-finding pipeline, which yield consistent detections. We derive the velocity width ($W_{50}$), flux density, and HI mass for detected galaxies. A total of 702 galaxies are identified with HI mass above $10^{6.2}\,{M_\odot}$, signal-to-noise ratio greater than 5, and redshift $z < 0.09$. Among these, 331 are previously known from the ALFALFA survey. Of the newly detected sources, 9 have spectroscopic confirmation from SDSS, 285 are matched to SDSS or DESI photometric data, and 77 lack optical counterparts--possible candidates for dark or faint galaxies. Comparison with ALFALFA shows that FAST enables detection of galaxies at higher redshifts and with lower HI fluxes, despite the radio frequency interference (RFI) and partial data masking. A preliminary HI mass function analysis reveals a higher characteristic mass and steeper low-mass slope than ALFALFA, indicating FAST's enhanced sensitivity to massive and distant HI systems. These results demonstrate FAST's strong potential for future deep HI surveys and highlight the importance of improved RFI mitigation and completeness correction.

astro-ph.GA↗

arXiv2025

AI Agent for Source Finding by SoFiA-2 for SKA-SDC2

Source extraction is crucial in analyzing data from next-generation, large-scale sky surveys in radio bands, such as the Square Kilometre Array (SKA). Several source extraction programs, including SoFiA and Aegean, have been developed to address this challenge. However, finding optimal parameter configurations when applying these programs to real observations is non-trivial. For example, the outcomes of SoFiA intensely depend on several key parameters across its preconditioning, source-finding, and reliability-filtering modules. To address this issue, we propose a framework to automatically optimize these parameters using an AI agent based on a state-of-the-art reinforcement learning (RL) algorithm, i.e., Soft Actor-Critic (SAC). The SKA Science Data Challenge 2 (SDC2) dataset is utilized to assess the feasibility and reliability of this framework. The AI agent interacts with the environment by adjusting parameters based on the feedback from the SDC2 score defined by the SDC2 Team, progressively learning to select parameter sets that yield improved performance. After sufficient training, the AI agent can automatically identify an optimal parameter configuration that outperform the benchmark set by Team SoFiA within only 100 evaluation steps and with reduced time consumption. Our approach could address similar problems requiring complex parameter tuning, beyond radio band surveys and source extraction. Yet, high-quality training sets containing representative observations and catalogs of ground truth are essential.

cs.LG↗

arXiv2025

CRAFTS for HI cosmology: I. data processing pipeline and validation tests

We present the calibration procedures and validation of source measurement with the data of the Commensal Radio Astronomy FAST Survey (CRAFTS) for \HI intensity mapping by the Five-hundred-meter Aperture Spherical Radio Telescope (FAST). Using 70-hour drift-scan observation with the L-band (1.05-1.45GHz) 19-beam receiver, we obtain the data covering $270\,\rm deg^2$ sky area. We employ both the pulsar backend and the spectrum backend to calibrate the spectral time-ordered-data (TOD) before projecting them onto HEALPix maps. We produce calibrated TOD with frequency resolution of 30kHz and time resolution of 1s and the map data-cube with frequency resolution of 30kHz and spatial resolution of $2.95\,\rm arcmin^2$. We examine the pointing errors, noise overflow, RFI contamination and their effect on the data quality. The resulting noise level is $\sim$ 5.7mJy for the calibrated TOD and 1.6mJy for the map, consistent with the theoretical predictions within 5\% at RFI-free channels. We also validate the data by Principal Components Analysis (PCA) and find the residual map looks thermal noise dominated after removing 30 modes. We identify 447 isolated bright continuum sources in our data matching the NRAO-VLA Sky Survey (NVSS) catalog, with relative flux error of 8.3\% for TOD and 6.6\% for the map-level. We also measure the \HI emission of 90 galaxies with redshift $z<0.07$ and compare with \HI-MaNGA spectra, yielding an overall relative \HI integral flux error of 16.7\%. These results provide an important first step in assessing the feasibility of conducting cosmological \HI detection with CRAFTS.

astro-ph.CO↗

arXiv2025

Searching for axion dark matter gegenschein of the Vela supernova remnant with FAST

Axions are one of the leading dark matter candidates. If we are embedded in a Milky Way dark matter halo comprised of axions, their stimulated decay would enable us to observe a counterimage (``axion gegenschein") with a frequency equal to half the axion mass in the opposite direction of a bright radio source. This spectral line emission will be broadened to $Δν/ν\sim σ_d/c \sim 10^{-3}$ due to the velocity dispersion of dark matter, $σ_d$. In this pilot study, we perform the first search for the expected axion gegenschein image of Vela supernova remnant (SNR) with 26.4 hours of effective ON-OFF data from the Five-hundred-meter Aperture Spherical radio Telescope (FAST) L-band (1.0 - 1.5~GHz) 19-beam receiver. Our null detection limits the axion-photon coupling strength to be $g_{aγγ} \lesssim 2 \times 10^{-10} \mathrm{GeV}^{-1}$ in the mass ranges of $8.7\,μ\mathrm{eV} \leq m_a \leq 9.44\,μ\mathrm{eV}$ and $10.85\,μ\mathrm{eV} \leq m_a \leq 12.01\,μ\mathrm{eV} $. These results provide a stronger constraint on $g_{aγγ}$ in this axion mass range than the current limits obtained by the direct search of axion decay signal from galaxy clusters which uses FAST observations, but is a factor of $\sim 3$ times weaker than the current CAST limit.Based on our observation strategy, data processing methods, and results, the expected sensitivity will reach $\sim 10^{-11}\mathrm{GeV}^{-1}$ with $\sim 2000$ hours of observation in the future.

astro-ph.CO↗

arXiv2023

FAST drift scan survey for HI intensity mapping: I. preliminary data analysis

This work presents the initial results of the drift-scan observation for the neutral hydrogen (HI) intensity mapping survey with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The data analyzed in this work were collected in night observations from 2019 through 2021. The primary findings are based on 28 hours of drift-scan observation carried out over seven nights in 2021, which covers $60\,{\rm deg}^2$ sky area. Our main findings are: (i) Our calibration strategy can successfully correct both the temporal and bandpass gain variation over the $4$-hour drift-scan observation. (ii) The continuum maps of the surveyed region are made with frequency resolution of $28$ kHz and pixel area of $2.95\,{\rm arcmin}^2$. The pixel noise levels of the continuum maps are slightly higher than the forecast assuming $T_{\rm sys}=20\,{\rm K}$, which are $36.0$ mK (for 10.0 s integration time) at the $1050$--$1150$ MHz band, and $25.9$ mK (for 16.7 s integration time) at the $1323$--$1450$ MHz band, respectively. (iii) The flux-weighted differential number count is consistent with the NRAO-VLA Sky Survey (NVSS) catalog down to the confusion limit $\sim7\,{\rm mJy}/{\rm beam}^{-1}$. (iv) The continuum flux measurements of the sources are consistent with that found in the literature. The difference in the flux measurement of $81$ isolated NVSS sources is about $6.3\%$. Our research offers a systematic analysis for the FAST HI intensity mapping drift-scan survey and serves as a helpful resource for further cosmology and associated galaxies sciences with the FAST drift-scan survey.

astro-ph.CO↗

arXiv2023

Detections of 21-cm absorption with a blind FAST survey at z $\leqslant$ 0.09

We present the early science results from a blind search of the extragalactic HI 21-cm absorption lines at z $\leqslant$ 0.09 with the drift-scan observation of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). We carried out the search using the data collected in 643.8 hours by the ongoing Commensal Radio Astronomy FasT Survey (CRAFTS), which spans a sky area of 3155 deg$^{2}$ and covers 44827 radio sources with a flux density greater than 12 mJy. Due to the radio frequency interference (RFI), only the relatively clean data in the frequency range of 1.3-1.45 GHz are used in the present work. Under the assumption of $T_{s}/c_{f}$ = 100 K, the total completeness-corrected comoving absorption path length spanned by our data and sensitive to Damped Lyman $α$ Absorbers (DLAs) are $ΔX^{inv}$ = 8.33$\times10^3$ ($Δz^{inv} = 7.81\times10^{3}$) for intervening absorption. For associated absorption, the corresponding values are $ΔX^{asc}$ = 12.8 ($Δz^{asc} = 11.9$). Three known HI absorbers (UGC 00613, 3C 293 and 4C +27.14) and two new HI absorbers (towards NVSS J231240-052547 and NVSS J053118+315412) are detected blindly. We fit the HI profiles with multi-components Gaussian functions and calculate the redshift (0.063, 0.066), width, flux density, optical depth and HI column densities for each absorption. Our results demonstrate the power of FAST in blindly searching HI absorbers. For absorption towards NVSS J231240-052547, the optical counterparts are faint and currently lack existing spectra. The most likely interpretation is that a radio-loud active galactic nucleus (AGN) is faint in the optical as the background source, with a faint optical absorber in between. NVSS J053118+315412 exhibits an associated absorption with a complex profile, which may suggest unsettled gas structures or gas accretion onto the supermassive black hole (SMBH).

astro-ph.GA↗

arXiv2023

Detecting HI Galaxies with Deep Neural Networks in the Presence of Radio Frequency Interference

In neutral hydrogen (HI) galaxy survey, a significant challenge is to identify and extract the HI galaxy signal from observational data contaminated by radio frequency interference (RFI). For a drift-scan survey, or more generally a survey of a spatially continuous region, in the time-ordered spectral data, the HI galaxies and RFI all appear as regions which extend an area in the time-frequency waterfall plot, so the extraction of the HI galaxies and RFI from such data can be regarded as an image segmentation problem, and machine learning methods can be applied to solve such problems. In this study, we develop a method to effectively detect and extract signals of HI galaxies based on a Mask R-CNN network combined with the PointRend method. By simulating FAST-observed galaxy signals and potential RFI impacts, we created a realistic data set for the training and testing of our neural network. We compared five different architectures and selected the best-performing one. This architecture successfully performs instance segmentation of HI galaxy signals in the RFI-contaminated time-ordered data (TOD), achieving a precision of 98.64% and a recall of 93.59%.

astro-ph.IM↗