FacetClumps: A Facet-based Molecular Clump Detection Algorithm

A comprehensive understanding of molecular clumps is essential for investigating star formation. We present an algorithm for molecular clump detection, called FacetClumps. This algorithm uses a morphological approach to extract signal regions from the original data. The Gaussian Facet model is employed to fit the signal regions, which enhances the resistance to noise and the stability of the algorithm in diverse overlapping areas. The introduction of the extremum determination theorem of multivariate functions offers theoretical guidance for automatically locating clump centers. To guarantee that each clump is continuous, the signal regions are segmented into local regions based on gradient, and then the local regions are clustered into the clump centers based on connectivity and minimum distance to identify the regional information of each clump. Experiments conducted with both simulated and synthetic data demonstrate that FacetClumps exhibits great recall and precision rates, small location error and flux loss, a high consistency between the region of detected clump and that of simulated clump, and is generally stable in various environments. Notably, the recall rate of FacetClumps in the synthetic data, which comprises $^{13}CO$ ($J = 1-0$) emission line of the MWISP within $11.7^{\circ} \leq l \leq 13.4^{\circ}$, $0.22^{\circ} \leq b \leq 1.05^{\circ}$ and 5 km s$^{-1}$ $\leq v \leq$ 35 km s$^{-1}$ and simulated clumps, reaches 90.2\%. Additionally, FacetClumps demonstrates satisfactory performance when applied to observational data.Comment: 27pages,28figure

Searching for Variable Stars in the Open Cluster NGC 2355 and Its Surrounding Region

We have investigated the variable stars in the field surrounding NGC 2355 based on the time-series photometric observation data. More than 3000 CCD frames were obtained in the V band spread over 13 nights with the Nanshan One-meter Wide-field Telescope. We have detected 88 variable stars, containing 72 new variable stars and 16 known variable stars. By analyzing these light curves, we classified the variable stars as follows: 26 eclipsing binaries, 52 pulsating stars, 4 rotating variables, and 6 unclear type variable stars for which their periods are much longer than the time baseline chosen. Employing Gaia DR2 parallax, kinematics, and photometry, the cluster membership of these variable stars were also analyzed for NGC 2355. In addition to the 11 variable members reported by Cantat-Gaudin et al. (2018), we identify 4 more variable member candidates located at the outer region of NGC 2355 and showed homogeneity in space positions and kinematic properties with the cluster members. The main physical parameters of NGC 2355 estimated from the two-color and color-magnitude diagrams are log(age/yr) = 8.9, E(B - V) = 0.24 mag, and [Fe/H] = - 0.07 dex.Comment: 15 pages, 11 figures. 6 tables,Accepted for publication in A

Implications for the Explosion Mechanism of Type Ia Supernovae from their Late-time Spectra

Late-time spectra of Type Ia supernovae (SNe Ia) are important in clarifying the physics of their explosions, as they provide key clues to the inner structure of the exploding white dwarfs. We examined late-time optical spectra of 36 SNe Ia, including five from our own project (SNe 2019np, 2019ein, 2021hpr, 2021wuf, and 2022hrs), with phase coverage of $\sim 200$ to $\sim 400$ days after maximum light. At this late phase, the outer ejecta have become transparent and the features of inner iron-group elements emerge in the spectra. Based on multicomponent Gaussian fits and reasonable choices for the pseudocontinuum around Ni and Fe emission features, we get reliable estimates of the Ni to Fe ratio, which is sensitive to the explosion models of SNe Ia. Our results show that the majority (about 67%) of our SNe Ia are more consistent with the sub-Chandrasekhar-mass (i.e., double-detonation) model, although they could be affected by evolutionary or ionisation effects. Moreover, we find that the Si II $\lambda$6355 velocity measured around the time of maximum light tends to increase with the Ni to Fe ratio for the subsample with either redshifted or blueshifted nebular velocities, suggesting that progenitor metallicity might play an important role in accounting for the observed velocity diversity of SNe Ia.Comment: 20 pages, 10 figures, accepted for publication in MNRA