Astrophysics and Space Science最新文献

Field-aligned irregularities (FAI) are a persistent feature of the equatorial ionosphere and can significantly impact satellite-based communication and navigation systems. Despite extensive documentation of their large-scale occurrence patterns, there is still a lack of understanding regarding their short-term temporal variability and detection uncertainty. To address this, a statistical framework based on Kernel Density Estimation (KDE) was developed to investigate the temporal characteristics of FAI events with higher resolution. Data from the Equatorial Atmosphere Radar (EAR) in West Sumatra, Indonesia, were analyzed, focusing on two years: 2016 (a leap year) and 2017 (a non-leap year). KDE was applied to generate smoothed daily probability estimates of FAI occurrence, along with associated confidence intervals, allowing the temporal evolution of FAI activity to be visualized more clearly. To examine short-term variability, FAI events are grouped into 1-day, 2-day, and 3-day sequential patterns. Results show consistent seasonal signatures across both years, suggesting stable ionospheric behaviours despite differences in calendar structure. The KDE approach captures fluctuations more clearly than standard methods and highlights subtle patterns in event occurrences. This method offers a reproducible way to study FAI dynamics and can be extended to multi-year or multi-site analyses. It supports a more complex conception of equatorial ionospheric variability and its relevance to space weather monitoring and forecasting, where precise characterization of ionospheric disturbances is essential.

Hot stars born as rapid rotators are expected to induce meridional currents that mix hydrogen from the envelope into the core and return CNO-cycle processed material to the envelope, which should enhance the N at the surface at the expense of C and possibly also O depending on the ambient conditions. But the photospheric C and N abundances could also be influenced by mass transfer in a close binary system which spins up the mass gainer and deposits either processed or unprocessed material to its surface depending on just how much material has been peeled off the mass donor. We focus on the chemical composition of Be star photospheres to infer the present and past evolution of rapidly rotating early B stars. To mitigate the effects of gravity darkening and photospheric line blending on the abundances, we chose 8 Be stars with low (vsin i) that have good high-resolution FUV spectra in the IUE archive. We carried out a conventional NLTE abundance analysis of selected N iii, N i, and C iii lines in the FUV spectral region. We find clear evidence that the C iii 1176 Å multiplet is weak in the core region in most program stars, suggesting CNO processing. However, in all cases we infer a N abundance that is solar or less, raising a conundrum as to what happened to the “missing C.” Since a similar pattern of weak C yet normal N is also found in the mass gainer in some Algol binaries, there appears to be an emerging challenge to explain this apparent abundance anomaly. We speculate that the excess N from CNO processing might be converted into O (and perhaps on to Ne) by fusion with He in the hot but low-density regions either in the trail of ashes just outside the receding carbon-fusing core, or in He-shell flash regions, of a highly evolved mass loser in its final stage of mass transfer.

We used CORSIKA to simulate extensive air showers initiated by primary protons and iron nuclei at an energy of 30 TeV and a zenith angle of 0^∘. By analyzing secondary particles within 0-600 m from the shower axis, we extracted statistical-moment features for the electromagnetic and muonic components, and fitted the radial distributions of both components with the NKG function to obtain the age parameters and particle-number parameters (Georgios in EPJ Web Conf. 137:13001, 2017). We first constructed a stacking ensemble model (with XGBoost, Random Forest (RF), and Support Vector Machines (SVMs) as base learners, and Logistic Regression as the meta-learner) for proton-iron classification, and then introduced single classifiers (SVM, XGBoost, and Random Forest) as benchmarks to validate the reliability of the stacking framework. The area under the ROC curve (AUC) and the Q-factor were used as evaluation metrics for composition discrimination. The results show that, under this idealized proton-iron setting, the single classifiers already reach near-saturated performance (AUC close to 1). The stacking model achieves an AUC of 0.995 on an independent test set, with a maximum Q ≈1 × 10(mathtt{^{4}}) in the threshold scan. The comparable performance between stacking and the single models indicates that the stacking framework is stable and reliable for this task; the lack of a significant performance gain is mainly due to the idealized physical setup and the strong class separability, which leave limited room for improvement beyond the single-model ceiling. This workflow can serve as a baseline for future composition-discrimination studies that incorporate detector response, noise/systematic uncertainties, and broader energy and zenith-angle ranges.

We present an autonomous model to simulate the daytime variation of sub-ionospheric Very Low Frequency (VLF) signal amplitude, beginning with the computation of the D-region electron density by numerically solving the electron continuity equation (ECE). From the resulting altitude-dependent electron density profile ((N_{e})), we extract Wait’s ionospheric parameters ((h^{prime }) and (beta )) using a log-linear fitting method. The study focuses on two VLF propagation paths (one short and one medium in length) in India, originating from the VTX / 18.2 kHz transmitter. The model effectively employs the Long Wave Propagation Capability (LWPC) framework to reproduce the daytime VLF signal amplitude profile. It accurately captures the daytime variations observed at the Bengaluru (BAN) station, where the ground wave component is dominant, as well as at Khukurdaha, WB (KHK). A quantitative comparison between the simulated ((A_{sim})) and ((A_{obs})) observed amplitudes shows justified agreement, validating the physical consistency and possible predictive capability of the proposed approach.

Type I superluminous supernovae (SLSNe) are a diverse class of exceptionally bright massive star explosions, which typically exhibit absorption from ionised oxygen in their early spectra. While their photometric properties (luminosity and duration) both span an order of magnitude, population studies suggest that these distributions are continuous. However, spectroscopic samples have shown some indications of distinct sub-types, either through similarity to certain prototype objects, or in terms of their velocity evolution. Here we show that a well-observed SLSN, PTF12dam, completely changes its O II absorption profile as it rises to maximum light, moving from one proposed sub-type to another. This supports an interpretation where spectroscopic diversity is driven by the ejecta temperature at maximum light, rather than fundamental differences in the explosion or progenitor. Motivated by this, we develop a new diagnostic, the Brightness-Timescale-Temperature-Radius diagram, and a simple toy model for the evolution of the photospheric velocity, to show that diversity in the light curve rise time (likely due to differences in ejected mass) naturally explains why SLSNe with broader light curves generally have weaker O II lines, lower photospheric velocities after maximum, and slower changes in photospheric velocity over time. We show that the velocity distribution of the known SLSN population favours a relatively flat ejecta density profile, consistent with a hot bubble inflated by a central engine.

Astrophysical plasma environments and quantum-gravity-inspired spacetime regularization collectively modify photon dynamics near compact objects, yet their coupled impact on photon sphere structure remains unquantified. This study examines the photon sphere radius ((r_{mathrm{ph}})) for static Hayward regular black holes immersed in a cold, non-magnetized plasma with a power-law density profile ((omega _{p}^{2} propto r^{-k})). The modified condition for circular photon orbits, incorporating the regularization parameter (l) and plasma strength (K), was numerically solved across physical parameter ranges. Results demonstrate a consistent inward shift of (r_{mathrm{ph}}) relative to the Schwarzschild vacuum case, with individual increases in (l) (to (1.0M)) or (K) (to 0.5) reducing (r_{mathrm{ph}}) by up to (12.7%) and over (18%), respectively. Crucially, combined effects exhibit nonlinear synergy: the contraction exceeds additive expectations, peaking at (l approx 0.8M) and (K approx 0.3) with a residual shift (Delta r_{mathrm{ph}}/M approx -0.32) and a total shift (delta r_{mathrm{ph}}^{mathrm{total}}/M approx -0.32) for typical accretion parameters ((k = 1.5)). This synergy, arising from the combined amplification by plasma gradients and quantum-corrected curvature, enhances sensitivity to plasma strength by (60%) compared to singular geometries. The corresponding 4–(12%) reduction in black hole shadow diameter underscores the significance of these interactions for interpreting next-generation interferometric observations of strong-gravity lensing features.

In this paper we explore a unified cosmological framework combining variable generalized Chaplygin gas (VGCG) and gravitationally–induced adiabatic matter creation cosmology within the context of (f(Q)) gravity. Theoretical and statistical analyses are performed with two functional forms, (f(Q)=n_{1} Q^{k}) and (f(Q)=n_{0}+n_{1}Q^{k}), where (n_{0}), (n_{1}) and (k) are dimensionless free parameters. Using the latest observational data sets we perform a robust statistical analysis to constrain the model’s parameters. A statistical comparison, including goodness-of-fit with standard (Lambda )CDM model is performed. The results show that the Bayesian inference favors the complex models while the model selection criterion, like Akaike information criteria (AIC) and Bayesian information criteria (BIC) favor the simpler (Lambda )CDM model. The results also show a smooth transition from deceleration to acceleration around the redshift (z approx 0.6) with effective equation of state parameter remains in the quintessence regime. The present value of Hubble parameter align closely with Planck 2018 measurements.

We investigate late–time cosmology in the Finsler–Barthel–Kropina framework, where anisotropic effects are introduced into the FLRW background through a time–dependent function (eta (t)) constructed via the osculating Riemannian approach. The resulting modified Friedmann equations generate direction–dependent corrections to the expansion history. Using Cosmic Chronometers (CC), DESI BAO, and Pantheon+ supernova observations, we reconstruct the Hubble rate, energy density, and key cosmographic quantities. The model yields (H_{0}) values consistent with late–time observations and negative value of deceleration parameter at present indicates ongoing acceleration phase of universe, while the reconstructed jerk and (Om(z)) diagnostics show clear departures from constant–(Lambda ) evolution, indicating effective dark-energy like dynamics sourced by Finslerian anisotropy. The predicted cosmic age is slightly higher than (Lambda )CDM. A model selection analysis based on information criteria shows that the Finsler–Kropina model performs competitively with (Lambda )CDM for the CC+ DESI BAO dataset, whereas the full joint dataset mildly favors (Lambda )CDM due to its lower parameter complexity. This demonstrates that Finsler–Kropina geometry offers a viable anisotropic extension of late–time cosmology.

This study uses the k-nearest neighbor (KNN) algorithm, Pearson correlation coefficient to predict sudden storm commencement (SSC), main, and recovery phases of ten intense storms (occurred during 2012-2018), and solar wind coupling with Earth’s magnetosphere. Probability distribution functions (pdfs) for solar wind interplanetary magnetic field (IMF), its Bz component and solar wind speed are also studied. IMF-Bz pdfs included single peak with and without bumps in front and on tail, double peak, and triple peak but highest positive correlation coefficients for double peak dominated those for triple peak distributions. Similar results are found for IMF pdfs. Contrarily, highest positive correlation coefficient occurred for single peak solar wind probability distribution. It is also found that storm phase prediction accuracy reduced when number of nearest neighbors is increased. The accuracy of prediction changed by replacing elements of data vectors. The highest accuracy occurred for data vectors including SYMH index and Bz component of an interplanetary magnetic field. The findings of this study can play a critical role in future space weather.

We present a singularity-free relativistic interior solution for constructing stable quark stellar models in the framework of a linear (f(Q)) gravity ((f(Q) = alpha Q + phi )) satisfying the pseudo-spheroidal geometry. The physical features and the stability of the stellar model is explored with strange star (SS) candidate EXO 1745-248 ((M = 1.7, M_{odot }) and (R = 9, km)). The Durgapal-Banerjee transformation is employed to obtain the relativistic interior solution using the MIT Bag model equation of state (EoS): (P = frac{1}{3}(rho - 4 mathcal{B}_{g})). For a linear form of (f(Q)) gravity, we obtain the exterior vacuum solution, which reduces to the Schwarzschild-de Sitter (SdS) solution with the cosmological constant term, (Lambda = frac{phi }{2alpha }). The stellar model is analyzed for the different values of the spheroidicity parameter ((mu )). The value of (alpha ) is constrained using a viable physical limit on the Bag parameter ((mathcal{B}_{g} in [57.55,95.11],MeV,fm^{-3})). The constraints on Mass-Radius relation indicates that physically acceptable SS models are permitted for (mu geq 7). The contribution of (mu ) to the energy density, pressure profiles, and other physical features is studied for the SS candidate EXO 1745-248. The stability of the stellar model obtained here is also analyzed through causality condition, adiabatic index and other stability criteria. We also investigate the stellar model for other SS candidates to test its viability. The relativistic interior solution obtained here can be used to construct viable and physically acceptable strange star models with very high compactness ratio in the framework of linear (f(Q)) gravity.