Journal of Astrophysics and Astronomy最新文献

In this study, we investigate the global structural properties and fractality of 1,876 open clusters (OCs) in various environments, including 1,145 singles, 392 pairs, and 339 groups. We analyse cluster mass, age, size, concentration, and fractal structure using the Q parameter and the fractal dimension (f_{textrm{dim}}), and examine their correlations with key physical parameters. Our results reveal systematic environmental trends: clusters in groups are generally younger, less massive, slightly larger, and less centrally concentrated than those in pairs or singles. Fractality is more pronounced in clusters within pairs and groups, with 44% of group clusters exhibiting fractal substructure compared to 38.5% for pairs and 33.2% for singles. Similarly, median (f_{textrm{dim}}) values increase from singles (1.13) to pairs (1.16) to groups (1.25), reflecting greater substructure in denser environments. These findings indicate that both intrinsic cluster properties and environmental context significantly influence cluster evolution. More massive clusters tend to evolve toward centrally concentrated, radially symmetric configurations, while less massive clusters retain fractal features for longer periods. Overall, our study demonstrates that OCs do not evolve in isolation: interactions with the environment play a critical role in shaping their structural evolution and dynamical state.

In this paper, a high-fidelity satellite precise orbit propagator (SPOP) is described for the spacecraft orbiting in the halo orbit around the Lagrangian point of the Sun-planet system. The propagator integrates the perturbed two-body differential equations of motion in the heliocentric J2000 inertial reference frame using Cowell’s method and explicit Runge–Kutta integrator with fixed time step size. The dominant perturbing forces are included while modeling the numerical propagator. Further, we describe the computational procedure for calculating the orbit to and from J2000 inertial frame and the Rotating Lagrangian Point (RLP) frame for visualizing the orbit. The SOHO and Aditya-(L_1) missions are used to validate the results obtained from the precise orbit propagator.

Extracting parameters from the global 21cm signal is crucial for understanding the early Universe. However, detecting the 21cm signal is challenging due to the brighter foreground and associated observational difficulties. In this study, we evaluate the performance of various machine-learning regression models to improve parameter extraction and foreground removal. This evaluation is essential for selecting the most suitable machine learning regression model based on computational efficiency and predictive accuracy. We compare four models: random forest regressor (RFR), Gaussian process regressor (GPR), support vector regressor (SVR), and artificial neural networks (ANNs). The comparison is based on metrics, such as the root mean square error (RMSE) and (R^{2}) scores. We examine their effectiveness across different dataset sizes and conditions, including scenarios with foreground contamination. Our results indicate that ANN consistently outperforms the other models, achieving the lowest RMSE and the highest (R^{2}) scores across multiple cases. While GPR also performs well, it is computationally intensive, requiring significant RAM and longer execution times. SVR struggles with large datasets due to its high computational costs, and RFR demonstrates the weakest accuracy among the models tested. We also found that employing principal component analysis (PCA) as a preprocessing step significantly enhances model performance, especially in the presence of foregrounds.

A spectroscopic study was carried out for the double-line A-type eclipsing binary system RR Lyn A(+)B based on the disentangled spectra, with an aim of clarifying the differences in photospheric chemical compositions between the components, where (T_textrm{eff}) (effective temperature) and (v_textrm{t}) (microturbulence) were determined from Fe lines. The resulting abundances of 30 elements revealed the following characteristics. (1) The brighter/hotter A shows metal-rich trends of classical Am stars; i.e., heavier elements generally show overabundances tending to increase towards higher Z (atomic number) with exceptionally large deficit of Sc, while light elements such as CNO show underabundances. (2) Meanwhile, the abundances of fainter/cooler B are closer to the solar composition ([X/H] (sim 0) for intermediate Z elements such as Fe group) though [X/H] does exhibit a slightly increasing tendency with Z, which suggests that B is a kind of marginal Am star with almost normal metallicity. This consequence is in contrast to the results of previous studies, which reported B to be of a metal-deficient nature similar to (lambda ) Boo stars. Such distinctions of chemical abundances between A and B may serve as a key to understanding the conditions for the emergence of the Am phenomenon.

This work studies interference patterns created by simple lens models (point mass, Chang–Refsdal, and binary lens) in the wave optics regime, primarily in the context of lensing of gravitational waves (GWs) in the LIGO band at frequencies around 100 Hz. We study how the interference patterns behave close to the caustic curves, which mark the high-magnification regions in conventional geometric optics. In addition, we also look at the formation of highly de-amplified regions in the amplification maps close to caustics and how they differ under wave and geometric optics. We see that, except for close to caustic regions, the geometric optics track the oscillations of the amplification factor in frequency very well, although the amplitude of these oscillations can differ considerably. Chang–Refsdal and binary lenses with masses ({sim })100–200 (M_odot ) can introduce significant de-amplification at frequencies ({sim })100 Hz when the source is close to caustics, which may help us distinguish such lenses from the point mass lens.

Type II solar radio bursts are commonly associated with shocks generated by coronal mass ejections (CMEs), where plasma waves are excited by magnetohydrodynamic (MHD) processes and converted into radio waves at the local plasma frequency or its harmonics. However, there are instances where type II bursts occur in the absence of whitelight CMEs. We analysed one such metric type II radio burst observed on 2 November 2023, characterized by split band features and fundamental-harmonic lanes. Notably, no CME was detected with space-based coronagraphs during this event. However, an intense M1.6 class flare was observed just before the type II burst and an extreme ultraviolet (EUV) disturbance was observed expanding into surrounding regions. The absence of any whitelight CME seen in any coronagraph field of view, even though the EUV shock had a moderate speed of ({approx }500) km s(^{-1}), which was close to the shock speed derived from radio observations. These observations indicate that the shock in the inner corona was most likely driven by the EUV ejecta seen in the lower corona, but the ejecta did not survive as a CME in the coronagraph field of view.

The paper is an investigation of the motion of a spacecraft around triangular libration points of the restricted five-body problem (R5BP) and its stability. With the assumption that the spacecraft moves in gravitational environments of four primaries, the configuration is such that the first primary is located at the origin of the coordinate system, while the second primary is collinear with the first primary, and the third and fourth are located above and below, on the left of the first primary. The equations of motion are established, and the locations of the libration points, zero velocity curve, stability of the libration points, and the Poincaré surfaces of sections are thoroughly investigated analytically and numerically when the mass of the first primary is varied. It is observed that when the mass of the first primary is increasing, the position of the spacecraft drifts away from the first primary. Further, it is seen that the increasing mass of the first primary reduces the region where motion of the spacecraft is allowed around the triangular points. Finally, the Poincaré Surface of section was explored, and it was seen that as the mass of the first primary is increasing, more clusters were noticed around the primaries, and this shows the presence of stable or quasi-periodic orbits, which correspond to regular motion. Consequently, the orbits are stable. The problem can be applied to study the motion of a spacecraft in the environments of Jupiter and its three Moons.

In this paper, we report the detailed spectral and temporal properties of six non-nuclear X-ray point sources, namely X-1, X-2, X-3, X-4, X-5, and X-6, located in the Seyfert 2 galaxy, NGC 4602, utilising the archival XMM-Newton data. Spectral fitting was performed using two empirical models: an absorbed power-law model and an absorbed disk blackbody model. Based on the estimated bolometric luminosity, all six sources fall in the ultraluminous X-ray sources range, with three out of the six sources (X-1, X-3, and X-6) reaching the extreme-luminosity X-ray luminosity range, exceeding (10^{40}) erg s(^{-1}), even in their lower limits. Detailed spectral analysis reveals distinct states among the sources. The sources, X-1, X-2, and X-4 exhibit hard spectral state with the powerlaw photon indices (Gamma ) ranging from (sim )1.69 to (sim )1.79 and inner disk temperatures (kT_{in}sim 0.65)–1.54 keV, within the error limits, while the sources, X-3, X-5, and X-6 display soft spectra with (Gamma sim 1.97)–2.43 with the cooler disk temperatures lying between (kT_{in} sim 0.28) and 0.44 keV. In this work, the Luminosity–Temperature relation could not be tightly constrained due to limited data availability, but the validity of (textrm{L} sim text {T}^{4}) relation was taken into account for the purpose of mass estimation. The hard spectral state of the sources (X-1, X-2, and X-4) may be attributed either due to the inverse comptonization of soft seed photons from the hot corona or due to the emission from the innermost region of the accretion flow while the soft spectra of the sources (X-3, X-5, and X-6) could be interpreted either as a thermal emission associated with an outflowing wind or emission from the accretion disk itself. The sources exhibit no short-term temporal variability as indicated by the Chi-square probability of constancy values, which is further complemented by the ( 3sigma ) upper limit values of RMS fractional variability. Moreover, the power density spectra created show no sign of pulsations in these sources.

In this work, we examine the dynamic motion of a test particle possessing both electrical charge and magnetic dipole moment in the presence of a Reissner–Nordström (RN) black hole (BH) situated within an externally asymptotically uniform magnetic field. The interaction between the external magnetic field and the motion of the test particle near the black hole was primarily discussed through the Lorentz force. In our study, the peak value of the effective potential of the particles decreases with increasing magnetic coupling parameter, (beta ). Additionally, the effects of the magnetic coupling parameter and the cyclotron frequency (omega _0) on the specific energy and angular momentum of the test particles for stable circular orbits are analyzed. An increase in both (beta ) and (omega _0) is found to cause a decrease in both the specific energy and angular momentum of the test particles. We also derive the expression of magnetic coupling parameters for the black hole, and the correspondence to the external magnetic field is analyzed. Our study also focuses on the center-of-mass energy, (E_{cm}), of colliding particles. An increase in the magnetic coupling parameter leads to a decrease in the center-of-mass energy extracted by the collision of two particles.

Photometric classification of Type Ia supernovae (SNe Ia) is critical for cosmological studies but remains difficult due to class imbalance and observational noise. While deep learning models have been explored, they are often resource-intensive and lack interpretability. We present a computationally efficient and interpretable classification framework that maintains high performance on imbalanced datasets. We emphasize the use of PR-AUC and F1-score as more informative metrics than ROC-AUC in severely imbalanced settings. Using an XGBoost ensemble optimized via Bayesian hyperparameter tuning, we classified light curves from the Supernova Photometric Classification Challenge (SPCC), comprising 21,318 events with a 3.19 imbalance ratio (non-Ia to Ia). Our model achieved a PR-AUC of (0.993^{+0.03}_{-0.02}), an F1-score of (0.923 pm 0.008), and a ROC-AUC of (0.976 pm 0.004), matching or exceeding deep learning performance on precision-recall trade-offs, while using fewer resources. Despite slightly lower overall accuracy, our method balances false positives and false negatives, improving the efficiency of spectroscopic follow-up. We show that optimized ensemble models offer a reproducible and lightweight alternative to complex architectures, particularly for large-scale surveys, such as the Legacy Survey of Space and Time (LSST), where transparency and efficiency are essential.