Chinese Astronomy and Astrophysics最新文献

Karoonda-like (CK) carbonaceous chondrites are highly oxidized meteorites, with metal-to-magnetite ratio close to zero. Unlike other carbonaceous chondrites (petrologic type: 1–3), most CK chondrites have undergone thermal metamorphism (550–1270 K) on their parent body with a petrologic type 4 or above. Lines of evidence suggest a genetic relationship between CK chondrites and Vigarano-like (CV) carbonaceous chondrites, which are predominantly type 3. However, observable petrographic distinctions persist between the two groups. Thus, a thorough reevaluation of their geochemical discrepancies is critical to test the CK-CV single parent body hypothesis. Northwest Africa (NWA) 13943, a newly discovered meteorite subjected to intense modification, was classified using scanning electron microscopy and electron microprobe techniques. High-precision measurements of the mass-independent chromium isotope compositions (${\epsilon }^{53}$Cr and ${\epsilon }^{54}$Cr) and the mass-dependent oxygen isotope compositions (${\delta }^{17}$O and ${\delta }^{18}$O) of NWA 13943 were reported for the first time. Integrating petrological, mineralogical, oxygen, and chromium isotopic data, it is legitimated to infer that CK and CV chondrites may originate from two proximal but distinct isotopic reservoirs within the protoplanetary disk.

The features of upper atmospheric midnight density maximum (MDM) around low geographic latitudes are studied based on neutral mass densities data at altitudes 360–480 km, derived from the accelerometer measurements aboard on the three polar orbiting satellites CHAMP (CHAllenging Minisatellite Payload), GRACE-A (Gravity Recovery and Climate Experiment-A), and SWARM-C (The Earth's Magnetic Field and Environment Explorers-C). The MDM appears during the local times from 23:00 to 02:00 LT (Local Time), whose peak locates at the low latitudes within ${15}^{\circ }$ and two valleys locate at the middle latitudes between ${35}^{\circ }$ and ${45}^{\circ }$ on both hemispheres separately. The structure of MDM drifts toward the southern hemisphere overall. The MDM's amplitude decreases with increases in altitude and solar radiation level. The seasonal effect weakens the MDM's amplitudes around the summer and winter solstices, while the amplitudes around the spring and autumn equinoxes are extremely significant due to the slight seasonal difference between both hemispheres. Three atmospheric density models DTM2000 (Drag Temperature Model 2000), NRLMSISE00 (US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended atmosphere model), and JB2008 (Jacchia-Bowman 2008 model) are used to simulate the MDM along these three satellites' orbits, and compared with the observations. It is found that the JB2008 model is failed to describe the MDM, and the other two models underestimate the MDM's amplitudes at altitudes 360 km and 480 km: the simulated amplitudes by the DTM2000 model are 46% and 53% of the observed amplitudes, respectively, and only 33% and 26% for the NRLMSISE00 model. These three models are also failed to depict the MDM's variation with altitude, solar radiation level, and seasonal effects. In order to correct the model prediction, a 6th-order Legendre polynomial of geographic latitude, coupled with arguments of local time and altitude, is designed to fit the MDM signals from the three satellites' observations. In terms of amplitude and phase of the MDM, the fitting results agree with the observations very well, and the correlation coefficient is 0.923. It indicates that this empirical polynomial could be helpful to the density model correction and high accuracy prediction of spacecrafts in low Earth orbits.

We study the waiting time distribution of giant pulses from the Crab pulsar observed with the Nanshan 26-m radio telescope at a center frequency of 1556 MHz with 512 MHz bandwidth. The observations were performed over a duration of 12.6 hours with 32 μs sampling interval. Our analysis has led to the detection of 2097 giant pulses above a threshold of 10 $\sigma$, with flux density $>$ 100 Jy. The occurrence rate of giant pulses is characterized by a highly intermittent giant pulse productivity in short clusters with high rates, separated by relatively long quiescent intervals with low occurrence rates, especially for the giant pulses associated with the interpulse emission. The distribution of waiting times between two subsequent giant pulses displays a power-law tail that can be modeled with a non-stationary Poisson process, which indicates that giant pulses are independent and random events. Distinct waiting time distributions between giant pulses in the main pulse and interpulse phases are presented, which implies that the giant pulse emission mechanisms maybe different in the opposite magnetic poles. The ramification for our understanding of the radio emission mechanisms is discussed.

We investigate the umbral oscillation at multi-height solar atmospheres above a sunspot in the active region of National Oceanic and Atmospheric Administration 12680 on 2017 September 15. In this study, the extreme ultraviolet images were measured by the Atmospheric Imaging Assembly (AIA), while the ultraviolet spectral lines and images were observed by the Interface Region Imaging Spectrograph. At the sunspot umbra, the AIA 1700 Å intensity curve shows the primary oscillation with a long period of $\sim$(4.2±0.8) minutes, while the intensity curves in AIA 1600 Å, 171 Å, and 193 Å exhibit an apparent oscillation with a short period of $\sim$(2.8±0.3) minutes. Meanwhile, a short period of $\sim$(3.1±0.5) minutes is found in the Mg II h & k lines and the slit-jaw image at 2796 Å, a short period of $\sim$(2.9±0.4) minutes is detected in the Si IV 1393.76 Å line. Our observations suggest that the oscillatory periods at the sunspot umbra decrease with the height of solar outer atmospheres. The short period is roughly equal to 3 minutes, which could be interpreted as the propagating slow magnetoacoustic wave above the sunspot umbra, and it might originate from the temperature minimum region and then propagate up to the corona. While the long period is close to 5 minutes oscillation in the photosphere, which might be regarded as the solar P-mode wave.

The performance of the antennas, which plays an important role in millimeter-wave astronomy and space communication, is often limited by their reflector surface accuracy. Microwave holography is a fast and effective technique for measuring the surface profile of reflector antenna. In this paper, the antenna aperture phase profile is obtained by microwave holography to estimate the deviation between the reflector of the Tianma 65 m radio telescope and the ideal paraboloid. The panels of the Tianma 65 m radio telescope is in radial pattern with 14 rings. Each corner of the panel is fixed on the screw of the actuator to move up and down, and the adjacent corners of the four panels share an actuator. We use the method of plane fitting to calculate the adjustment value of every panels corner. But one actuator, which simultaneously controls the common corner of the adjacent panels, will have different adjustment values according to the plane fitting equation based on adjacent panels. In this paper, an adjustment value at the corner of the adjacent panel is obtained by plane fitting and adjustment calculation method with the antenna illumination function as the weight, that is, the optimal adjustment value of 1104 actuators of the Tianma 65 m radio telescope. Through many adjustments and the application of new algorithms, the surface accuracy of the reflector of the Tianma 65 m radio telescope has gradually improved to the current 0.24 mm.

To quickly search for rare fast radio bursts (FRBs) from massive astronomical observational data, Radio Frequency interference (RFI) mitigation is one of the key and challenging task. RFI will cause search algorithm to output a large number of false positive candidates, and even submerges real astronomical events. Due to the complexity of the sources and types of RFI. there is currently no universal method to solve this problem. In order to reduce the impact of RFI on FRB search, the RFI in L band observational data of the Nanshan 26m radio telescope (NSRT-26m) was analyzed and studied. A three-layer RFI mitigation procedure was established for the main narrowband RFI and broadband RFI, which effectively alleviated the RFI pollution of observational data. Embedding this procedure into the FRB DDSS (Dispersion Dynamic Spectra Search) pipeline, experimental results show that the detection rate and accuracy of the search algorithm have been further improved. This method provides valuable reference for RFI mitigation of FRB observational data.

Quasars are characterized by violent and large amplitude variability in all the observation wavelengths, and the analysis of optical variability is useful for developing theoretical models. Long-term optical variability data of quasar 3C 446 were collected from the University of Michigan Radio Astronomy Observatory database in the 4.8, 8.0, and 14.5 GHz radio bands from 1976 to 2012. Due to the complexity of the variability data, it's hard to study by the linear time series analysis methods. For learning more about non-linear characteristics of the temporal evolution of quasar variability, the Ensemble Empirical Mode Decomposition and nonlinear analysis are used to analyse chaotic dynamics, fractal properties, and periodicity. This paper focuses on whether there is a significant difference between the periodic and non-linear properties of the quasar variability before and after the removal of the periodic or chaotic components. It turns out that the variability of quasar 3C 446 in the radio bands consists of periodic, trend, and chaotic components, and the periodic and trend components are dominant. The periods of the variability after removing the chaotic and trend components are exactly the same as the periods of the original variability data, but the chaotic and fractal characteristics of the two are significantly different. The saturated correlation dimension indicates that the reconstruction of the dynamical system requires more independent parameters than the original optical variables after the removal of the periodic and trend components. The Kolmogorov entropy indicates that the loss of information is greater for the former than the latter, and the system is more chaotic and more complex. The Hurst value indicates that the self-similarity and long-range correlation are slightly stronger for the latter than the former.

311P/PANSTARRS is an active asteroid with characteristics of both asteroids and comets, and it is one of the targets of China's Tianwen-2 mission. Because of its small size of about 400 m, the Yarkovsky effect may have a significant influence on its long-term dynamics. This paper discussed the changes in the long-term motion of 311P/PANSTARRS caused by the Yarkovsky effect. By assuming different surface compositions, this simulation introduced the semi-major axis drift by propagating orbits of orbital clones. It also discusses non-gravitational effects such as close encounters, non-destructive impacts, and the YORP (Yarkovsky-O'Keefe-Radzievskii-Paddack) effect. The study calculates the probabilities of close encounters and impacts with major planets and estimates the timescale for 311P/PANSTARRS to reach its rotational period splitting limit. The results of the simulations show that the Yarkovsky effect may cause 311P/PANSTARRS to exit from the resonance region faster when compared to a purely gravitational model. 311P/PANSTARRS will leave the current resonance region after roughly 10 Myr, and have a chance to become a Mars-crossing asteroid through ${\nu }_6$ secular resonance due to the diurnal Yarkovsky effect if its surface is covered by a regolith layer. It is concluded that 311P/PANSTARRS is stable at least 10 Myr time scale even if taking the Yarkovsky effect and the YORP effect into account. Furthermore, the YORP effect may not significantly affect the semi-major axis drift of 311P/PANSTARRS.

Currently, more than 5 000 exoplanets have been detected, and exoplanetary science is evolving from a focus on exoplanet detection to a focus on comprehensive exoplanetary characterization. Over the past 20 years, through the atmospheric characterization of about 100 exoplanets, a basic framework has been established for atmospheric detection methods, a series of atmospheric spectral forward modeling and retrieval methods, and atmospheric theory for transiting and directly imaged planets. The James Webb Space Telescope (JWST) has unprecedented detection capabilities in the near to mid-infrared spectra, and high-quality data will drive the development of atmospheric theory and models. The early released scientific results of Cycle-1 have shown the ability of JWST to characterize the atmospheres of transiting and directly imaged exoplanets, as well as the initial constraints on the atmospheres of potentially habitable planets around nearby low-mass star. The pursuit of finely detailed exoplanet atmospheric characterization in the era of JWST has already begun, and in conjunction with future missions with atmospheric survey capabilities, such as ARIEL (Atmospheric Remote-sensing Infrared Exoplanet Large-survey) and large-aperture adaptive-optics ground-based telescopes in the next 5 years, will reveal the diversity of exoplanet atmospheres at a much deeper level.

The characteristics of Low Surface Brightness Galaxies (LSBGs) are very important for understanding the overall characteristics of galaxies. It is of great significance to search and expand the samples of Low Surface Brightness Galaxies by modern machine learning, especially deep learning algorithm. LSBGs are difficult to discern automatically and accurately with traditional methods because of their obscure features. However, deep learning does have the advantage of automatically identifying complex and effective features. To solve this problem, an algorithm named You Only Look Once version X-CS (YOLOX-CS) is proposed to search LSBG in large sample sky survey. Firstly, five classical target detection algorithms are compared through experiments and the optimal YOLOX algorithm is selected as the basic algorithm. Then, the YOLOX-CS framework is constructed by combining different attention mechanisms and different optimizers. The data set uses images from the Sloan Digital Sky Survey (SDSS), labelled from LSBG in the $\alpha .40$-SDSS DR7 (the cross coverage area of 40% HI Arecibo Legacy Fast ALFA Survey and SDSS Data Release7) survey. Due to the small number of samples in this data set, Deep Convolutional Generative Adversarial Networks (DCGAN) model is used to expand the experimental test data. After comparing with a series of target detection algorithms, YOLOX-CS has a good test result in searching LSBG recall rate and Average Precision (AP) value in two data sets before and after expansion. The recall rate and AP value in the test set without expansion data set reach 97.75% and 97.83%, respectively. In the expanded data set of DCGAN model, under the same test set, the recall rate reaches 99.10% and the AP value reaches 98.94%, which proves that the algorithm has excellent performance in LSBG search. Finally, the algorithm is applied to SDSS photometric data, and 765 LSBG candidates are obtained.