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天文和天体物理学研究
天文和天体物理学研究

汪景琇 景益鹏

月刊

1674-4527

wenyy@bao.ac.cn

010-64853746

100717

北京朝阳区大屯路甲20号国家天文台 RAA编辑部

天文和天体物理学研究/Journal Research in Astronomy and AstrophysicsCSCD北大核心CSTPCDSCI
查看更多>>本刊1981年创刊至2000年已出版20卷。创刊时为中文期刊，2001年改为《中国天文和天体物理学报》（英文版）。主要刊登天文学和天体物理学领域的原创性研究论文。主要栏目和报道范围：“研究快报”用来报道天文观测的新结果及新理论；“特约综述”聘请国际知名天文学家就某些热点问题进行专题评述。“研究论文”具有原创性。2009年更名为《天文和天体物理学研究》（英文版），由双月刊变为月刊。
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    Possible Habitats for NH3,NH2D,H13CN,HC15N,SO,and C18O in the Initial Conditions of High-mass Star Formation

    Quan-Ling CuiChuan-Peng ZhangJun-Jie Wang
    237-252页
    查看更多>>摘要：The initial condition of high-mass star formation is a complex area of study because of the high densities(nH2＞106 cm-3)and low temperatures(Tdust＜18 K)involved.Under such conditions,many molecules become depleted from the gas phase by freezing out onto dust grains.However,the N-bearing and deuterated species could remain gaseous under these extreme conditions,suggesting that they may serve as ideal tracers.In this paper,using the Plateau de Bure Interferometer and Very Large Array observations at 1.3 mm,3.5 mm,and l.3 cm,we investigate the possible habitats for NH3,NH2D,H13CN,HC15N,SO,and C18O in eight massive precluster and protocluster clumps G18.17,G18.21,G23.97N,G23.98,G23.44,G23.97S,G25.38,and G25.71.We found that the NH3 cores are in good agreement with the 3.5 mm peak emission,but the NH3 is much more extended than the 3.5 mm emission structure.The SO distributions agree well with the 3.5 mm peaks for the evolved star formation stage,but we did not detect any SO emission in the four earliest star formation sources.C18O is a poor tracer in conditions of the cold((≲)18K)and dense((≲)104cm-3)cores,e.g.,the prestellar cores.We also found that the NH2D cores are mainly located in the temperature range of 13.0-20.0 K,and the NH2D lines may be strongly depleted above 20 K.
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    The Bright Single Pulse Emission from PSR B1 133+16

    Jun TanZhi-Gang WenZhen WangXue-Feng Duan...
    253-261页
    查看更多>>摘要：We have conducted a comprehensive investigation into the bright single pulse emission from PSR B1133+16 using the Giant Metrewave Radio Telescope.High time resolution data(61 μs)were obtained at a center frequency of 322 MHz with a bandwidth of 32 MHz over a continuous observation period of 7.45 hr.A total of 1082 bright pulses were sporadically detected with peak flux densities ranging from 10 to 23 times stronger than the average pulse profile.However,no giant pulse-like emission with a relative pulse energy larger than 10 and extremely short duration was detected,indicating that these bright pulses cannot be categorized as giant pulse emission.The majority of these bright pulses are concentrated in pulse phases at both the leading and trailing windows of the average pulse profile,with an occurrence ratio of approximately 2.74.The pulse energy distribution for all individual pulses can be described by a combination of two Gaussian components and a cutoff power-law with an index of α=-3.2.An updated nulling fraction of 15.35％±0.45％ was determined from the energy distribution.The emission of individual pulses follows a log-normal distribution in peak flux density ratio.It is imperative that regular phase drifting in bright pulse sequence is identified in both the leading and trailing components for the first time.Possible physical mechanisms are discussed in detail to provide insights into these observations.
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    Multiwavelength Observations of the Infrared Dust Bubble N75 and its Surroundings

    Quan-Ling CuiChuan-Peng ZhangJun-Jie Wang
    262-270页
    查看更多>>摘要：Infrared dust bubbles play an important role in the study of star formation and the evolution of the interstellar medium.In this work,we study the infrared dust bubble N75 and the infrared dark cloud G38.93 mainly using the tracers C18O,HCO+,HNC and N2H+observed by the 30 m IRAM telescope.We also study the targets using data from large-scale surveys:GLIMPSE,MIPSGAL,GRS,NRAO VLA Sky Survey and Bolocam Galactic Plane Survey.We found that the C18O emission is morphologically similar to the Spitzer IRAC 8.0 μm emission.The 1.1 mm cold dust emission of G38.93 shows an elongated structure from southwest to northeast.The ionized gas from G38.93 is surrounded by polycyclic aromatic hydrocarbon emission,which may be excited by radiation from G38.93.We found that the identified young stellar objects tend to cluster around G38.93 and are mostly in class Ⅱ,with several class I cases distributed around N75,but no class Ⅱ examples.We also found evidence of expanding feedback,which could have triggered star formation.
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    Accelerating Asteroidal Period and Pole Inversion from Multiple Lightcurves Using Parallel Differential Evolution and Cellinoid Shape Model

    Yong-Xiong ZhangWen-Xiu GuoXiao-Ping LuHua Zheng...
    271-286页
    查看更多>>摘要：Determining asteroid properties provides valuable physical insights but inverting them from photometric lightcurves remains computationally intensive.This paper presents a new approach that combines a simplified Cellinoid shape model with the Parallel Differential Evolution(PDE)algorithm to accelerate inversion.The PDE algorithm is more efficient than the Differential Evolution algorithm,achieving an extraordinary speedup of 37.983 with 64 workers on multicore CPUs.The PDE algorithm accurately derives period and pole values from simulated data.The analysis of real asteroid lightcurves validates the method's reliability:in comparison with results published elsewhere,the PDE algorithm accurately recovers the rotational periods and,given adequate viewing geometries,closely matches the pole orentations.The PDE approach converges to solutions within 20,000 iterations and under one hour,demonstrating its potential for large-scale data analysis.This work provides a promising new tool for unveiling asteroid physical properties by overcoming key computational bottlenecks.
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    Machine Learning-based Identification of Contaminated Images in Light Curve Data Preprocessing

    Hui LiRong-Wang LiPeng ShuYu-Qiang Li...
    287-295页
    查看更多>>摘要：Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as"stellar contamination,"and second,the brightness markedly decreases due to cloudy cover,referred to as"cloudy contamination."The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.
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