Astrophysics and Space Science最新文献

We construct equilibrium configurations for neutron stars using a specific (f(R,T)) functional form, recently derived through gaussian process applied to measurements of the Hubble parameter. By construction, this functional form serves as an alternative explanation for cosmic acceleration, circumventing the cosmological constant problem. Here, we aim to examine its applicability within the stellar regime. In doing so, we seek to contribute to the modified gravity literature by applying the same functional form of a given gravity theory across highly distinct regimes. Our results demonstrate that equilibrium configurations of neutron stars can be obtained within this theory, with the energy density and maximum mass slightly exceeding those predicted by General Relativity. Additionally, we show that the value of some parameters in the (f(R,T)) functional form must differ from those obtained in cosmological configurations, suggesting a potential scale-dependence for these parameters. We propose that further studies apply this functional form across different regimes to more thoroughly assess this possible dependence.

Recent findings on retrograde co-orbital mean-motion resonances in the Earth-Moon system, highlight the potential use of spacecraft in retrograde resonances. Based on these discoveries, this study investigates retrograde co-orbital resonances within the Earth-Moon system, focusing on both optimal and sub-optimal orbital transfers to such configurations. The paper provides a comprehensive analysis of retrograde co-orbital resonances, optimization techniques to evaluate and enhance the performance of bi-impulsive transfers to these configurations. The results reveal the feasibility of low-cost transfers, which could support a range of future missions, including space exploration and satellite deployment. Combining advanced optimization processes, we obtained solutions for orbital transfers for different arrival points in retrograde co-orbitals improving mission efficiency and offering a cost-effective approach to interplanetary exploration.

Pulsar Timing Arrays (PTAs) are a powerful tool to trace gravitational waves (GWs) signatures in the nanohertz frequency range by precisely monitoring timing residuals of millisecond pulsars. This study explores advancements in PTA methodologies, emphasizing machine learning (ML) techniques, wavelet analysis, and cross-correlation studies to enhance sensitivity to GW signals. Using data from the Indian Pulsar Timing Array (InPTA), we apply Principal Component Analysis (PCA), clustering algorithms, and wavelet-based time-frequency decomposition to improve the detection of the Stochastic Gravitational Wave Background (SGWB).Our analysis reveals a strong correlation (Pearson r = 0.872) between measured pulsar timing residuals and the Hellings-Downs curve, supporting the presence of an SGWB signal. Wavelet decomposition identifies significant low-frequency power, suggesting persistent timing residual structures consistent with GW signatures. PCA indicates that the first component captures ∼84.3% of the variance, highlighting a dominant common signal among pulsars. Clustering analysis reveals distinct pulsar groups, with some showing enhanced correlated noise features, likely linked to GW-induced fluctuations. Additionally, the estimated GW amplitude and spectral index for individual pulsars further reinforce the presence of a stochastic background. These findings demonstrate the effectiveness of dimensionality reduction and clustering techniques in isolating astrophysical signals, enhancing the reliability of GW detection. Our results provide strong support for the existence of an SGWB and showcase the potential of integrating machine learning with traditional pulsar timing analyses to refine GW detection strategies.

Comets and asteroids have long captured human curiosity, and until recently, all documented examples belonged to our Solar System. That changed with the discovery of the first known interstellar object, 1I/2017 U1 (‘Oumuamua), in 2017. Two years later, on August 30, 2019, Gennady Borisov discovered a second interstellar object, 2019 Q4, which was officially designated 2I/Borisov. From its initial images, the object’s diffuse appearance hinted at its cometary nature. To better understand the photometric evolution of comet 2I/Borisov as it traveled through the inner Solar System, we compiled observations using medium-sized telescopes. This data is crucial for gaining insights into its size and composition, as well as how such objects, after millions of years in interstellar space, behave when exposed to the Sun’s radiation. Given that 2I/Borisov is the first interstellar comet ever observed, constraining its behavior is of great scientific interest. In this paper, we present photometric data gathered from observatories in Crimea and Catalonia, highlighting the importance of systematic photometric studies of interstellar objects using meter-class telescopes. Our observations showed a steady increase in the comet’s brightness as it approached perihelion, likely due to the slow sublimation of ices. Over the five-month pre-perihelion observation period, we did not detect any significant changes in magnitude. The analysis of observations reveals a steady increase in comet 2I/Borisov brightness as it approached perihelion, likely due to the sublimation of ices, with no observable outbursts during the five-month pre-perihelion period. Additionally, we discuss the challenges in ground-based observation of comets posed by light pollution today, particularly in urban areas, where visual observations are severely limited. Using sample surface brightness measurements, we demonstrate the impact of light pollution and outline the importance of systematic photometric studies for interstellar objects.

The Total Electron Content (TEC) is an important parameter that describes the morphology and structure of the ionosphere. Deep learning is an important and effective tool for forecasting TEC, but the role of different solar activity indices and geomagnetic indices in TEC prediction remains unclear. The Long Short-Term Memory (LSTM) network has special structure design and good generalization ability, which is capable of learning the features of long-term sequence data and has been widely applied in the research of ionosphere prediction. Therefore, in this study, the LSTM network is used to achieve short-term forecasting of low, middle, and high latitudes TEC during geomagnetic storms that occurred in 2016. At the same time, the effects of four different index combinations, F10.7, Kp, Dst, and AE indices, on the prediction results at different latitudes were analyzed. The results show that the appropriate combination of index inputs effectively improves the prediction performance of the model. At low latitudes, the model incorporating Kp, Dst and F10.7 indices performed best, with a 51.3% average decrease in RMSE compared to the model without any additional indices. The best model is one that uses Kp and F10.7 indices at middle latitudes, compared to model without any indices, its average RMSE decreased by 57.0%. At high latitudes, the model using Kp, Dst, and AE indices performed best, with a 43.2% average decrease in RMSE compared to the model without any indices. However, more indices do not necessarily improve prediction accuracy.

This paper aims to obtain a new Class-I solution of the field equations in (mathcal{F}(mathcal{R},mathcal{T})) gravitational theory for the charged anisotropic spherically symmetric distribution. For this purpose, a new spacetime metric function is put forth and employed in the Karmarkar condition. The uniform charge distribution in the stellar interior is considered and the Class-I spacetime is seamlessly matched to Bardeen geometry at the boundary. Moreover, a detailed analysis is conducted to study the physical attributes of the stars Vela X-1, SMC X-4, SAX J1808.4-3658, Her X-1 and Cen X-3, all obeying the essential conditions for a solution to be physically acceptable. A comprehensive review of stability criteria involving the energy conditions and adiabatic is provided complying with the requirement. In addition, an in-depth exploration of the Tolman-Oppenheimer-Volkoff’s (TOV) equation leads to the stellar configuration being in an equilibrium state.

A libration-point orbit (LPO) offers low-cost access to space and may be the destination of future manned missions. Usually, a lunar flyby is required for short-term LPO missions, thus the transfer trajectory from the Earth to LPO is composed of an Earth–Moon two-body leg and a Moon–LPO three-body leg. The abort orbit associated with the Earth–Moon two-body leg has been thoroughly studied. In this paper, the abort orbit of the Moon–LPO three-body leg is designed and analyzed. Along the Moon–LPO three-body leg, the abort orbits of direct, lunar-flyby, and low-energy return are designed and discussed separately. For the direct return, the abort orbits are obtained based on an initial Kepler solution with reentry constraint. For the lunar-flyby return, the abort orbits are designed by pseudostate theory. For the low-energy return, the abort orbits are further optimized by introducing nontransit/transit orbits and lunar flyby. In the Earth–Lissajous transfer scenario, three types of abort orbits for the Moon–LPO three-body leg are numerically designed. For the direct or lunar-flyby return case, the total impulse of abort orbits is greater than 0.9 km/s. This is a significant burden for manned mission planning. For the low-energy return, the minimum total impulses are 0.302 km/s and save 20–60% total impulse at the cost of a limited increase in flight time. This abort orbit employs a nontransit/transit orbit to return to the vicinity of the Moon and quickly return to Earth after applying a second maneuver at perilune. Finally, return windows and trajectory types of abort orbits are classified based on a reference trajectory.

Due to the fact that Keplerian orbits are conic sections, projective geometry gives a description of orbits based on projective hyperquadric properties. Using matrix algebra to describe hyperquadrics allows the construction of a new set of orbital elements using the eigenvalues and eigenvectors of the improper hyperquadric matrix and the construction of reference systems associated with the orbit. It is possible to work directly with the orbit in Cartesian coordinates in the three-dimensional space as a 4x4 matrix, constructing the quadric associated with the orbital conic.

The Habitable Worlds Observatory (HWO) will enable a transformative leap in the direct imaging and characterization of Earth-like exoplanets. For this, NASA is focusing on early investment in technology development prior to mission definition and actively seeking international partnerships earlier than for previous missions. The “R&D for Space-Based HCI in Europe” workshop, held in March 2024 at Paris Observatory, convened leading experts in high-contrast imaging (HCI) to discuss European expertise and explore potential strategies for European contributions to HWO. This paper synthesizes the discussions and outcomes of the workshop, highlighting Europe’s critical contributions to past and current HCI efforts, the synergies between ground- and space-based technologies, and the importance of laboratory testbeds and collaborative funding mechanisms. Key conclusions include the need for Europe to invest in technology development for areas such as deformable mirrors and advanced detectors, and establish or enhance laboratory facilities for system-level testing. Putting emphasis on the urgency of aligning with the timeline of HWO, the participants called on an open affirmation by the European Space Agency (ESA) that a European contribution to HWO is clearly anticipated, to signal national agencies and unlock funding opportunities at the national level. Based on the expertise demonstrated through R&D, Europe is poised to play a pivotal role in advancing global HCI capabilities, contributing to the characterization of temperate exoplanets and fostering innovation across domains.