Astrophysics and Space Science最新文献

This research investigates cosmic dynamics within the context of (f(mathcal{R},mathcal{L}_{m})) gravity, concentrating on a binary mixing of perfect fluid and dark energy in a Plane Symmetric space-time. By incorporating the non-linear form of (f(mathcal{R},mathcal{L}_{m})) as (f(mathcal{R},mathcal{L}_{m})=frac{mathcal{R}}{2}+mathcal{L}_{m}^{alpha }), it investigates late-time cosmic acceleration and the transition from matter-dominated to dark energy-dominated epochs. The analysis includes the quintessence and Chaplygin gas models, demonstrating their role in the dynamics of energy density, effective pressure, and anisotropy. The model is validated through parameterization using observational data, such as Hubble parameter datasets, which result in an excellent level of agreement with empirical findings. Advanced diagnostics, like the jerk, statefinder, and (Om) diagnostics, show that (f(mathcal{R},mathcal{L}_{m})) gravity is different from previous cosmological models. This lets us explain the expansion of the universe in terms of geometry. This study provides a strong basis for future research on modified gravity, anisotropic cosmological models, and the role of dark energy in the evolution of the universe.

In this paper, I discuss the macroscopic properties of the ultracompact object XTE J1814-338, whose inferred mass and radius read (M = 1.21 pm ) 0.05 (M_{odot }) and R = 7.0 ± 0.4 km as a dark matter-admixed strange star. By using the neutralino as WIMP dark matter with a fixed Fermi momentum, I calculated the moment of inertia, the gravitational redshift, the dimensionless tidal parameter, and the total amount of dark matter for a 1.2(M_{odot }) star. At the end, I study the role of the neutralino’s mass.

The properties of kinetic Alfvén waves (KAWs) are investigated in the negative positive ion electron (NPIE) plasma of Titan’s ionosphere. The concentrations of positive and negative ions in dayside and nightside regions of this ionosphere are different, whereas the magnitude of the ambient magnetic field also varies. The plasma data indicate the possibility for the existence of very low frequency and long wavelength kinetic Alfvén waves (KAWs) in this environment. The frequencies and wavelengths of these waves are estimated considering only the two kinds of positive (HCNH^{+}) and negative (CN^{-}) ions, which have dominant concentrations. Extremely small magnetic field (mid B_{0} mid simeq 0.0002) (G) can sustain KAWs with extremely small frequencies of the order of (simeq 0.004text{ rad}/text{s}) and very long wavelengths of the order of a thousand kilometres along field lines while the Titan is about a million kilometres away from Saturn’s surface. It is pointed out that the weakly nonlinear KAWs can also give rise to electromagnetic solitary waves similar to the Earth’s upper ionosphere. The formation of solitary structures by the nonlinear KAWs is also investigated using the appropriate normalization of spatial coordinates in parallel and perpendicular directions with respect to the ambient magnetic field. The almost stationary electromagnetic pulses may appear in Titan’s ionosphere moving at very small speeds.

This paper investigates the application of knot theory to the classification of orbit families in the Circular Restricted Three-Body Problem (CR3BP). Motivated by the infinite variety of possible orbits—many of which remain unnamed and uncataloged—this paper applies polynomial knot invariants, primarily the Alexander polynomial, to establish a relation between knot structures and orbital trajectories. An algorithm is developed to extract knot types from three-dimensional trajectories enabling the identification and differentiation of complex orbit families. Knot theory topics explored and correlated to CR3BP trajectories include the torus knot and unknot. The findings provide a novel topological framework for understanding CR3BP dynamics, offering both theoretical understanding and practical modeling in astrodynamics for multi-body gravitational systems.

We explore the possibility of retrieving cosmological information along with its inherent uncertainty from 21-cm tomographic data at intermediate redshift. The first step in our approach consists of training an encoder, composed of several three dimensional convolutional layers, to cast the neutral hydrogen 3D data into a lower dimension latent space. Once pre-trained, the featurizer is able to generate 3D grid representations which, in turn, will be mapped onto cosmology ((Omega _{mathrm{m}}), (sigma _{8})) via likelihood-free inference. For the latter, which is framed as a density estimation problem, we consider a Bayesian approximation method which exploits the capacity of Masked Autoregressive Flow to estimate the posterior. It is found that the representations learned by the deep encoder are separable in latent space. Results show that the neural density estimator, trained on the latent codes, is able to constrain cosmology with a precision of (R^{2} ge 0.91) on all parameters and that most of the ground truth of the instances in the test set fall within (1sigma ) uncertainty. It is established that the posterior uncertainty from the density estimator is reasonably calibrated. We also investigate the robustness of the feature extractor by using it to compress out-of-distribution dataset, that is either from a different simulation or from the same simulation but at different redshift. We find that, while trained on the latent codes corresponding to different types of out-of-distribution dataset, the probabilistic model is still reasonably capable of constraining cosmology, with (R^{2} ge 0.80) in general. This highlights both the predictive power of the density estimator considered in this work and the meaningfulness of the latent codes retrieved by the encoder. We believe that the approach prescribed in this proof of concept will be of great use when analyzing 21-cm data from various surveys in the near future.

The intrinsic nature of the magnetosphere is important in understanding the role of different drivers in its dynamics. In this study, an attempt was made to characterize and quantify the complexity in the magnetosphere during Solar Cycle 24 using the Dst index as a measure. Two approaches were considered: chaos and multifractal analysis. The chaotic analysis using the Lyapunov exponent, correlation dimension, and entropy measures revealed that the magnetosphere is chaotic for every year of Solar Cycle 24. Furthermore, there was no significant difference between the complexity in Solar Cycle 24 and the previous 4 solar cycles (20-23). Chaotic parameters (sample entropy, Lyapunov exponent, and correlation dimension) showed strong correlations with annual mean Dst values throughout Solar Cycle 24. Multifractal detrended fluctuation analysis parameters showed weak relationships with annual means but revealed underlying structures in Dst values.

Pulsars, the cosmic lighthouses, are strongly self-gravitating objects with core densities significantly exceeding nuclear density. Since the discovery of the Hulse–Taylor pulsar 50 years ago, binary pulsar studies have delivered numerous stringent tests of General Relativity (GR) in the strong-field regime as well as its radiative properties—gravitational waves (GWs). These systems also enable high-precision neutron star mass measurements, placing tight constraints on the behaviour of matter at extreme densities. In addition, pulsars act as natural detectors for nanohertz GWs, primarily from supermassive black hole binaries, culminating in the first reported evidence of a stochastic GW background in 2023. In this article, I review key milestones in pulsar research and highlight some of contributions from my own work. After a brief overview of the gravity experiments in §1, I review the discovery of pulsars—particularly those in binaries—and their critical role in gravity experiments (§2) that laid the foundation for recent advances. In §3, I present the latest efforts on GR tests using the Double Pulsar and a pioneer technique to constrain the dense matter equation of state. §4 demonstrates the potential of binary pulsars on testing alternative theories to GR. Advances in nanohertz GW detection with pulsar timing arrays are discussed in §5. I outline some of the current challenges in §6 and conclude with final remarks in §7.

Solar flares represent a significant element in the broader context of space weather phenomena, exerting a direct influence on the Earth’s ionosphere. The ionosphere is a region of the Earth’s atmosphere that is ionized by solar radiation, which also undergoes seasonal changes. The present study is concerned with elucidating the seasonal fluctuations in differential vertical total electron content (DVTEC) of the ionosphere during solar flare events of solar cycle 24. The present study examines M and C solar flares during the ascending (2013), peak (2014), and descending phases (2015) of solar cycle 24. A total of 207 solar flare events were observed over a three-year period. The IISC is the low-latitude GNSS site in Bangalore, India (geographic latitude 13.02°N, geographic longitude 77.57°E) was utilized for this study. The results indicate the presence of an anomalous winter phenomenon in 2014, as well as a peak in DVTEC during the winter season. The recombination process, which involves the O/N₂ ratio, is responsible for the higher (Delta )DVTEC observed during the winter season. Additionally, modifications to dissociation-recombination during the summer season and vertical advection in the F layer contributed to the 2014 winter anomaly. Among the solar indices examined, a correlation of 0.45, between d(EUV flux)/dt and (Delta )DVTEC, indicating EUV flux as the primary source of ionization in the ionosphere.

The detections (Abbott et al. in Astrophys. J. Suppl. Ser. 267(2):29, 2023; Abbott et al. in SoftwareX 13:100658, 2021) and analysis of gravitational waves (GWs) have introduced us in a new era of our understanding of the cosmos, providing new insights into astrophysical systems involving massive objects as black holes and neutron stars. Normally the precise sky localization of a GW source needs data from three or more observatories (Abbott et al. in Phys. Rev. Lett. 116(22):221101, 2016c; Abbott et al. in Phys. Rev. Lett. 119(14):141101, 2017c). However, the results presented in this article demonstrate that it is in fact possible to obtain the position of a GW source in a small region of the celestial sphere using data from just two GW observatories, in this case LIGO Hanford and LIGO Livingston. Furthermore, we are also able to reconstruct the gravitational-wave polarization (Poisson and Will in Gravity: Newtonian, Post-Newtonian, Relativistic, Cambridge University Press, Cambridge, 2014) modes (PMs) for the GW170104 (Abbott et al. in GW170104: observation of a 50-solar-mass binary black hole coalescence at redshift 0.2. Phys. Rev. Lett. 118(22):221101, 2017b) and GW150914 (Abbott et al. in Phys. Rev. D 93(12):122003, 2016a) events, with data from only these two detectors. The procedure only uses the spin 2 properties of the GW, so that it does not rely on specific assumptions on the nature of the source. Our findings are possible through careful data filtering methods (Moreschi in J. Cosmol. Astropart. Phys. 1904:032, 2019), the use of refined signal processing algorithms (Moreschi in Astrophys. Space Sci. 369(1):12, 2024), and the application of dedicated denoising (Mallat in A Wavelet Tour of Signal Processing: The Sparse Way, Elsevier, Amsterdam, 2009) techniques. This progress in the GW studies represents the first instance of a direct measurement of PMs using such a limited observational data. We provide detailed validation through the reconstruction of PMs for different polarization angles, and calculations of residuals for the GW170104 event. We also test the procedure with synthetic data with ten different source locations and polarization angles.

Large-scale photometric surveys are revolutionizing astronomy by delivering unprecedented amounts of data. The rich data sets from missions such as the NASA Kepler and TESS satellites, and the upcoming ESA PLATO mission, are a treasure trove for stellar variability, asteroseismology and exoplanet studies. In order to unlock the full scientific potential of these massive data sets, automated data-driven methods are needed. In this review, I illustrate how machine learning is bringing asteroseismology toward an era of automated scientific discovery, covering the full cycle from data cleaning to variability classification and parameter inference, while highlighting the recent advances in representation learning, multimodal datasets and foundation models. This invited review offers a guide to the challenges and opportunities machine learning brings for stellar variability research and how it could help unlock new frontiers in time-domain astronomy.