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  • Stellar Population and Energy Feedback in the Supergiant Shell LMC 1
    Supergiant shells (SGSs) are the largest interstellar structures in galaxies and inject hot enriched gas into galactic halos. We have studied SGS LMC 1 to determine quantitatively whether stellar energy feedback is adequate to power the formation of an SGS. The Gaia EDR3 photometric data of the OB association LH15 inside SGS LMC 1 are used to construct color–magnitude diagrams, and stellar evolutionary tracks and isochrones are used to assess stellar masses and ages. The observed present-day mass function is compared with the Salpter initial mass function to estimate the number of massive stars that have exploded as supernovae. Their total stellar wind mechanical energy and supernova explosion energy input amounts to (57 ± 12) × 1051 erg. For the gas components of SGS LMC 1, ATCA+Parkes H i data are used to determine the total mass and kinetic energy in the H i shell, MCELS Hα image is used to determine the ionized gas mass and kinetic energy, adopting the H i expansion velocity, and ROSAT X-ray observations are used to estimate the thermal energy in the SGS interior. The sum of the kinetic and thermal energies in the three layers is estimated to be (59 ± 5) × 1051 erg. Thus, the stellar energy feedback from LH15 appears adequate to power the formation of SGS LMC 1. The radial age gradient in LH15 and the young stellar objects along the outer periphery indicate a progression of star formation, which might be a crucial factor for an SGS to grow to its large size.

  • Evolution of Massive Red Galaxies in Clusters from z = 1.0 to z = 0.3
    A critical issue in studying the evolution of galaxy clusters is to find ways that enable meaningful comparisons of clusters observed at different redshifts, as well as in various stages of their growth. Studies in the past have typically suffered from uncertainties in cluster mass estimates due to the scatter between cluster observables and mass. Here we propose a novel and general approach that uses the probability distribution function of an observable–cluster mass relation, together with dark matter halo merger trees extracted from numerical simulations, such that one can trace the evolution in a self-contained fashion, for clusters chosen to lie in a specified range in mass and redshift. This method, when applied to clusters of different mass ranges, further allows one to examine the evolution of various observable-cluster mass scaling relations. We illustrate the potential of this method by studying the stellar mass content of red cluster member galaxies, as well as the growth of brightest cluster galaxies, from z = 1.0 to z = 0.3, using a large optically detected cluster sample from the Subaru Hyper Suprime-Cam Survey, finding good agreement with previous studies.

  • A Neutral Hydrogen Absorption Study of Cold Gas in the Outskirts of the Magellanic Clouds Using the GASKAP-H i Survey
    Cold neutral hydrogen (H i) is a crucial precursor for molecular gas formation and can be studied via H i absorption. This study investigates H i absorption in low column density regions of the Small and Large Magellanic Clouds (SMC and LMC) using the Galactic-ASKAP H i (GASKAP-H i) survey, conducted by the Australian Square Kilometer Array Pathfinder (ASKAP). We select 10 SMC directions in the outer regions and 18 LMC directions, with four in the outskirts and 14 within the main disk. Using the radiative transfer method, we decompose the emission and absorption spectra into individual cold neutral medium (CNM) and warm neutral medium (WNM) components. In the SMC, we find H i peak optical depths of 0.09–1.16, spin temperatures of ∼20–50 K, and CNM fractions of 1%–11%. In the LMC, optical depths range from 0.03–3.55, spin temperatures from ∼10–100 K, and CNM fractions from 1%–100%. The SMC’s low CNM fractions likely result from its low metallicity and large LOS depth. Additionally, the SMC’s outskirts show lower CNM fractions than the main body, potentially due to increased CNM evaporation influenced by the hot Magellanic Corona. Shell motions dominate the kinematics of the majority of CNM clouds in this study and likely supply cold H i to the Magellanic Stream. In the LMC, high CNM fraction clouds are found near supergiant shells, where thermal instability induced by stellar feedback promotes WNM-to-CNM transition. Although no carbon monoxide has been detected, enhanced dust shielding in these areas helps maintain the cold H i.

  • Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
    Fast-moving celestial objects are characterized by velocities across the celestial sphere that significantly differ from the motions of background stars. In observational images, these objects exhibit distinct shapes, contrasting with the typical appearances of stars. Depending on the observational method employed, these celestial entities may be designated as near-Earth objects or asteroids. Historically, fast-moving celestial objects have been observed using ground-based telescopes, where the relative stability of stars and Earth facilitated effective image differencing techniques alongside traditional fast-moving celestial object detection and classification algorithms. However, the growing prevalence of space-based telescopes, along with their diverse observational modes, produces images with different properties, rendering conventional methods less effective. This paper presents a novel algorithm for detecting fast-moving celestial objects within star fields. Our approach enhances state-of-the-art fast-moving celestial object detection neural networks by transforming them into physical-inspired neural networks. These neural networks leverage the point-spread function of the telescope and the specific observational mode as prior information; they can directly identify fast-moving celestial objects within star fields without requiring additional training, thereby addressing the limitations of traditional techniques. Additionally, all neural networks are integrated using the mixture-of-experts technique, forming a comprehensive fast-moving celestial object detection algorithm. We have evaluated our algorithm using simulated observational data that mimic various observations carried out by space-based telescope scenarios and real observation images. Results demonstrate that our method effectively detects fast-moving celestial objects across different observational modes and telescope configurations.

  • Landscape of Coronal X-Ray Variability and Cycles
    Coronal (1–10 MK) X-rays display dramatic variability over the Sun’s iconic 11 yr magnetic dynamo cycle: already a factor of 4 in the soft 0.1–2.4 keV “ROSAT band,” soaring to more than 100 at harder energies (>10 keV). The high-energy variations impact heliospheric space weather (SW); presumably likewise for host-star analogs. In an effort to better document long-term coronal variability and X-ray cycles of other stars, measurements of 19 late-type F–M dwarfs and subgiants were obtained from archives of the three contemporary long-lived X-ray observatories: Chandra, XMM-Newton, and Swift. The X-ray event lists were time-filtered to suppress transients like flares and telemetry dropouts. A novel scheme, based on empirical coronal models, harmonized flux conversions across the different instruments. The Sun was included based on high-energy irradiance time series. Results generally confirmed previous findings: high-contrast, decadal-class X-ray modulations were found exclusively at low-to-medium LX/LBOL; higher X-ray intensity stars displayed lower-amplitude, faster variations, if cycling at all; whereas the highest activity classes showed stable (“saturated”) long-term X-ray trends, but punctuated by persistent flaring. In addition, several variants of “dynamo diagrams” are presented to illustrate possible correlations among key parameters, such as rotation period and cycle duration. Early versions of such diagrams had displayed what appeared to be clear trends, although additional observations in recent years have tended to downplay the previous relationships. The diverse X-ray behaviors hold implications for stellar SW, as well as posing tough challenges for dynamo theory.