Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>A new, more comprehensive model of gas–grain chemistry in hot molecular cores is presented, in which nondiffusive reaction processes on dust-grain surfaces and in ice mantles are implemented alongside traditional diffusive surface/bulk-ice chemistry. We build on our nondiffusive treatments used for chemistry in cold sources, adopting a standard collapse/warm-up physical model for hot cores. A number of other new chemical model inputs and treatments are also explored in depth, culminating in a final model that demonstrates excellent agreement with gas-phase observational abundances for many molecules, including some (e.g., methoxymethanol) that could not be reproduced by conventional diffusive mechanisms. The observed ratios of structural isomers methyl formate, glycolaldehyde, and acetic acid are well reproduced by the models. The main temperature regimes in which various complex organic molecules (COMs) are formed are identified. Nondiffusive chemistry advances the production of many COMs to much earlier times and lower temperatures than in previous model implementations. Those species may form either as by-products of simple-ice production, or via early photochemistry within the ices while external UV photons can still penetrate. Cosmic ray-induced photochemistry is less important than in past models, although it affects some species strongly over long timescales. Another production regime occurs during the high-temperature desorption of solid water, whereby radicals trapped in the ice are released onto the grain/ice surface, where they rapidly react. Several recently proposed gas-phase COM-production mechanisms are also introduced, but they rarely dominate. New surface/ice reactions involving CH and CH<jats:sub>2</jats:sub> are found to contribute substantially to the formation of certain COMs.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The solar wind (SW) is an outflow of the solar coronal plasma, which expands supersonically throughout the heliosphere. SW particles interact by charge exchange with interstellar neutral atoms; on the one hand, they modify the distribution of this gas in interplanetary space, and, on the other hand, they are the seed populations for heliospheric pickup ions and energetic neutral atoms (ENAs). The heliolatitudinal profiles of the SW’s speed and density evolve during the solar activity cycle. A model of the evolution of the SW’s speed and density is needed to interpret observations of ENAs, pickup ions, the heliospheric backscatter glow, etc. We derive the Warsaw Heliospheric Ionization Model 3DSW—WawHelIon 3DSW—based on interplanetary scintillation (IPS) tomography maps of the SW speed. We use the IPS tomography data from 1985 to 2020, compiled by Tokumaru et al. We derive a novel statistical method of filtering these data against outliers; we present a flexible analytic formula for the latitudinal profiles of the SW speed, based on Legendre polynomials of varying order with additional restraining conditions at the poles; fit this formula to the yearly filtered data; and calculate yearly SW density profiles using the latitudinally invariant SW energy flux observed in the ecliptic plane. Despite the application of a refined IPS data set, a more sophisticated data filtering method, and a more flexible analytic model, the present results mostly agree with those obtained previously, demonstrating the robustness of IPS studies of the SW’s structure.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Ly<jats:italic>α-</jats:italic>emitting galaxies and giant Ly<jats:italic>α</jats:italic> blobs (LABs) have been extensively observed to study the formation history of galaxies. However, the origin of their extended Ly<jats:italic>α</jats:italic> emission, especially of LABs, remains controversial. Polarization signals from some LABs have been discovered, and this is commonly interpreted as strong evidence supporting that the extended Ly<jats:italic>α</jats:italic> emission originates from the resonance scattering. The Monte Carlo Ly<jats:italic>α</jats:italic> radiative transfer code LaRT is updated to investigate the polarization of Ly<jats:italic>α</jats:italic> using the Stokes vector formalism. We apply LaRT to a few models to explore the fundamental polarization properties of Ly<jats:italic>α</jats:italic>. Interestingly, individual Ly<jats:italic>α</jats:italic> photon packets are found to be almost completely polarized by a sufficient number of scatterings (<jats:italic>N</jats:italic> <jats:sub>scatt</jats:sub> ≳ 10<jats:sup>4</jats:sup>–10<jats:sup>5</jats:sup> in a static medium) or Doppler shifts induced by gas motion, even starting from unpolarized light. It is also found that the polarization pattern can exhibit a nonmonotonically increasing pattern in some cases, other than the commonly known trend that the polarization monotonically increases with radius. The polarization properties are primarily determined by the degree of polarization of individual photon packets and the anisotropy of the Ly<jats:italic>α</jats:italic> radiation field, which are eventually controlled by the medium’s optical depth and velocity field. Once Ly<jats:italic>α</jats:italic> photon packets achieve ∼100% polarization, the radial profile of polarization appears to correlate with the surface brightness profile. A steep surface brightness profile tends to yield a rapid increase of the linear polarization near the Ly<jats:italic>α</jats:italic> source location. In contrast, a shallow surface brightness profile gives rise to a slowly increasing polarization pattern.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Wide-field telescopes with long exposure times have stronger space target detection capabilities. However, complex background sky conditions will still cause a series of difficulties in detecting space debris, such as a large number of star points, a large amount of noise, and the discontinuity and nonlinearity of the target. We propose a space debris automatic extraction channel with a high detection rate and low computational cost to solve these difficulties. We apply an improved median filter for noise elimination and then the double-structure morphological filter algorithm used to suppress the background of the star image to eliminate star points and noise. Then, the guided filter was used to eliminate residual noise, and star points were used to reduce the impact on the target. Finally, the improved Hough transform was also applied to detect the target in the image. Our automatic extraction algorithm is used in real astronomical star maps, including different orbiting satellites (star-tracking mode). These images were obtained by using a 280 mm diameter telescope, which was located in Changchun Observatory. The experimental results demonstrated the effectiveness of the extraction algorithm in this study. It can effectively detect and track space targets in a long-exposure wide-field surveillance system and has high positioning accuracy and low computational complexity, which solves the problem of space debris extraction under a complex background.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Hot subdwarf stars are a particular type of star that is crucial for studying binary evolution and atmospheric diffusion processes. In recent years, identifying hot subdwarfs by machine-learning methods has become a hot topic, but there are still limitations in automation and accuracy. In this paper, we proposed a robust identification method based on a convolutional neural network. We first constructed the data set using the spectral data of LAMOST DR7-V1. We then constructed a hybrid recognition model including an eight-class classification model and a binary classification model. The model achieved an accuracy of 96.17% on the testing set. To further validate the accuracy of the model, we selected 835 hot subdwarfs that were not involved in the training process from the identified LAMOST catalog (2428, including repeated observations) as the validation set. An accuracy of 96.05% was achieved. On this basis, we used the model to filter and classify all 10,640,255 spectra of LAMOST DR7-V1, and obtained a catalog of 2393 hot subdwarf candidates, of which 2067 have been confirmed. We found 25 new hot subdwarfs among the remaining candidates by manual validation. The overall accuracy of the model is 87.42%. Overall, the model presented in this study can effectively identify specific spectra with robust results and high accuracy, and can be further applied to the classification of large-scale spectra and the search for specific targets.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We have surveyed the complete extent of Leo A, which is an apparently isolated Local Group dwarf irregular galaxy, in <jats:italic>B</jats:italic>, <jats:italic>V</jats:italic>, <jats:italic>R</jats:italic>, <jats:italic>I</jats:italic> (the Johnson–Cousins system), and <jats:italic>NA</jats:italic>656 (centered on H<jats:italic>α</jats:italic>) passbands with the Subaru Telescope equipped with the Suprime-Cam mosaic camera. <jats:italic>B</jats:italic>, <jats:italic>V</jats:italic>, and <jats:italic>I</jats:italic> photometry results were published earlier by Stonkutė et al. The recently published Stetson’s high-quality photometric standards in the <jats:italic>R</jats:italic> passband encouraged us to calibrate and make available to the community deep (<jats:italic>R</jats:italic> ∼ 25 mag) <jats:italic>R</jats:italic> and <jats:italic>NA</jats:italic>656 photometry results in the field of Leo A (<jats:inline-formula> <jats:tex-math> <?CDATA $20^{\prime} \times 24^{\prime} $?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>20</mml:mn> <mml:mo accent="false">′</mml:mo> <mml:mo>×</mml:mo> <mml:mn>24</mml:mn> <mml:mo accent="false">′</mml:mo> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjsac5119ieqn1.gif" xlink:type="simple" /> </jats:inline-formula>). We present the photometry catalog of 28,224 objects in <jats:italic>R</jats:italic> and 25,800 objects in <jats:italic>NA</jats:italic>656 passbands. This catalog could serve for future imaging and spectroscopic observation programs of Leo A, especially targeted to study emission-line objects. Also, we demonstrate the capability of the <jats:italic>B</jats:italic>, <jats:italic>V</jats:italic>, <jats:italic>R</jats:italic>, and <jats:italic>NA</jats:italic>656 passband system to separate Milky Way M-type dwarfs and late-type evolved stars in external galaxies, as well as to recognize early-type (Be, B[e]) emission-line stars.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Using the high-cadence lightcurves collected from the FOSSIL survey, rotation periods of 17 small (diameter 1 km &lt; <jats:italic>D</jats:italic> &lt; 3 km) Hilda asteroids (hereinafter Hildas) were obtained. Combined with the previously measured rotation periods of Hildas, a spin-rate limit appears at around 3 hr. Assuming rubble-pile structures for the Hildas, a bulk density of ∼1.5 g cm<jats:sup>−3</jats:sup> is required to withstand this spin-rate limit. This value is similar to that of the C-type asteroids (1.33 g cm<jats:sup>−3</jats:sup>) and higher than the ∼1 g cm<jats:sup>−3</jats:sup> bulk density of the Jupiter Trojans. This suggests that the Hildas population may contain more C-type asteroids than expected, and the limit at 3 hr simply reflects the spin-rate limit for C-type asteroids. In addition, a Hilda superfast rotator was found, which has a rotation period of 1.633 hr and an estimated diameter of 0.7 km. This object is unlikely to be explained by a rubble-pile or monolithic structure.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Detection methods for interplanetary coronal mass ejections (ICMEs) from in situ spacecraft measurements are mostly manual, which are labor-intensive and time-consuming, being prone to the inconsistencies of identification criteria and the incompleteness of the existing catalogs. Therefore, the automatic detection of ICMEs has aroused the interest of the astrophysical community. Of these automatic methods, the convolutional neural network–based methods show the advantages of fast speed and high precision. To further improve the computing feasibility and detection performance, this paper proposes a method called residual U-net (RU-net), from the perspective of time-series segmentation. With the help of U-net architecture, we design an encoder–decoder network with skip connection to capture multiscale information, where the end-to-end architecture with an embedded residual element is formulated to accelerate the algorithmic convergence. For the in situ data from 1997 October 1 to 2016 January 1 collected by the Wind spacecraft, the results of our experiments demonstrate the competitive performance of the proposed RU-net in terms of accuracy and efficiency (178 of 230 ICMEs are detected in the test set, and the <jats:italic>F</jats:italic>1 score is 80.18%).</jats:p>

<jats:title>Abstract</jats:title> <jats:p>To understand structure formation in the universe and impose stronger constraints on the cluster mass function and cosmological models, it is important to have large galaxy cluster catalogs. The Swift AGN and Cluster Survey is a serendipitous X-ray survey aimed at building a large statistically selected X-ray cluster catalog with 442 cluster candidates in its first release. Our initial SDSS follow-up study confirmed 50% of clusters in the Sloan Digital Sky Survey footprint as <jats:italic>z</jats:italic> &lt; 0.5 clusters. Here we present further optical follow-up analysis of 248 (out of 442) cluster candidates from the Swift cluster catalog using multiband imaging from the MDM 2.4 m telescope and the Pan-STARRS survey. We report the optical confirmation of 55 clusters with &gt;3<jats:italic>σ</jats:italic> galaxy overdensities and detectable red sequences in the color–magnitude space. The majority of these confirmed clusters have redshifts <jats:italic>z</jats:italic> &lt; 0.6. The remaining candidates are potentially higher-redshift clusters that are excellent targets for infrared observations. We report the X-ray luminosity and the optical richness for these confirmed clusters. We also discuss the distinction between X-ray and optical observables for the detected and nondetected cluster candidates.</jats:p>