Hasil untuk "Astronomy"

B. Reipurth, D. Jewitt, K. Keil

M. Evans, R. Adhikari, Chaitanya Afle et al.

This Horizon Study describes a next-generation ground-based gravitational-wave observatory: Cosmic Explorer. With ten times the sensitivity of Advanced LIGO, Cosmic Explorer will push gravitational-wave astronomy towards the edge of the observable universe ($z \sim 100$). The goals of this Horizon Study are to describe and evaluate design concepts for Cosmic Explorer; to plan for the United States' leadership in gravitational-wave astronomy; and to envisage the role of Cosmic Explorer in the international effort to build a"Third-Generation"(3G) observatory network that will make discoveries transformative across astronomy, physics, and cosmology.

K. Collins, J. Kielkopf, K. Stassun et al.

ImageJ is a graphical user interface (GUI) driven, public domain, Java-based, software package for general image processing traditionally used mainly in life sciences fields. The image processing capabilities of ImageJ are useful and extendable to other scientific fields. Here we present AstroImageJ (AIJ), which provides an astronomy specific image display environment and tools for astronomy specific image calibration and data reduction. Although AIJ maintains the general purpose image processing capabilities of ImageJ, AIJ is streamlined for time-series differential photometry, light curve detrending and fitting, and light curve plotting, especially for applications requiring ultra-precise light curves (e.g., exoplanet transits). AIJ reads and writes standard Flexible Image Transport System (FITS) files, as well as other common image formats, provides FITS header viewing and editing, and is World Coordinate System aware, including an automated interface to the astrometry.net web portal for plate solving images. AIJ provides research grade image calibration and analysis tools with a GUI driven approach, and easily installed cross-platform compatibility. It enables new users, even at the level of undergraduate student, high school student, or amateur astronomer, to quickly start processing, modeling, and plotting astronomical image data with one tightly integrated software package.

Weitao Zhang, Han He, Jun Zhang

Based on the Ca ii H and K lines observed by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, we employ the photospheric ( ${R}_{{\rm{HK}}}^{{\prime} }$ ) and basal ( ${R}_{{\rm{HK}},L}^{+}$ ) flux-calibrated chromospheric activity indices to examine the relationship between chromospheric activity and the stellar rotation rate. We identify the rotation periods of 11,108 stars observed by Kepler and the Transiting Exoplanet Survey Satellite by crossmatching our chromospheric activity catalog with previous studies. Our statistical results show that chromospheric activity increases with the rotation rate until it reaches a saturation level. As the stellar effective temperature increases from 4950 to 5850 K, the saturation values of the rotation period ( P _rot ) vary correspondingly from 4.38 to 1.23 days for ${R}_{{\rm{HK}}}^{{\prime} }$ and from 9.88 to 1.33 days for ${R}_{{\rm{HK}},L}^{+}$ . Similarly, the corresponding saturation Rossby number (Ro) ranges from 0.200 to 0.032 for ${R}_{{\rm{HK}}}^{{\prime} }$ and from 0.302 to 0.107 for ${R}_{{\rm{HK}},L}^{+}$ . The saturation is also found to be significant in stars with thick convective zones, whereas it is less apparent in stars with higher effective temperatures. For solar-like stars in the T _eff range of 4800–6000 K, the values of chromospheric activity indicators are saturated when P _rot  < 1.45 days (Ro < 0.100) and P _rot  < 2.85 days (Ro < 0.097) for ${R}_{{\rm{HK}}}^{{\prime} }$ and ${R}_{{\rm{HK}},L}^{+}$ , respectively.

Stephane Le Corre

Several solutions have been proposed to explain the dark matter (DM) component, but two explanations stand out. The most widely accepted is the assumption of the existence of exotic matter, and the second is the assumption of a modification of gravitation called MOND. We show in this article that the solutions of exotic matter and MOND are particular cases of a more general solution of pure general relativity that explains DM with only baryonic matter and without modifying gravity. Within the framework of general relativity linearization (GRL), we first demonstrate that these two explanations (exotic matter and GRL solution) are so close that all explanations within the framework of the exotic matter assumption can be translated within the GRL solution. Conversely, certain effects appear in this alternative that should not be observed in the hypothesis of exotic matter. Different types of alignments (about axes of rotation or planar trajectories) should appear on different types of objects (dwarf satellite galaxies, galaxies, or clusters of galaxies). Observational monitoring of the dynamics of S-2 stars close to our Galactic Center in the future should reveal (due to greater precision) discrepancies from the theory, explainable by the lower mass of SgrA* compensated by a stronger-than-expected GRL field (instead of exotic matter). The implementation of simulations to explain the structuring of the universe on a large scale should be able to reveal filaments or walls and large voids, thanks to a stronger-than-expected GRL field (explaining the DM component instead of exotic matter). The size of these structures would be correlated with the intensity of this GRL field. We show that this solution responds to the points addressed to all alternatives to exotic matter. Conversely, we propose points challenging the exotic matter assumption that are naturally explained in this DM component alternative explanation.

Junyao He, Junyao He, Hao Luo et al.

Astronomical imaging data frequently exhibit low signal-to-noise ratios (SNRs), especially for observations obtained from small-aperture, wide-field survey instruments, in which the detected signals are inherently faint and dominated by noise. Such characteristics pose a substantial technical challenge for subsequent target detection and quantitative measurement tasks. This challenge is particularly pronounced for faint astronomical targets with SNRs ranging from 1 to 10. When the SNR decreases below approximately 5, the useful signal approaches or falls beneath the detection threshold imposed by background noise, leading to a pronounced degradation in the performance of traditional threshold-based detection algorithms, such as Sextractor. Furthermore, astronomical imaging data are typically characterized by a high 16-bit dynamic range. This wide dynamic range results in the intensities of faint targets being compressed into a narrow interval of low pixel values. Standard global normalization strategies employed in deep learning models further compress this narrow intensity band, thereby suppressing and obscuring discriminative target features. To address these challenges, we propose ATD-DL, a deep learning–based framework specifically designed for faint astronomical target detection. The core of the proposed framework is an enhanced U-Net–based segmentation architecture. This architecture is integrated with a multi-stage image preprocessing pipeline, target separation, and centroid extraction modules to enable efficient and robust detection of astronomical objects. Experimental results demonstrate that the proposed method achieves excellent performance in detecting extremely faint targets with SNRs in the range 2 ≤ SNR &lt; 5. Compared with traditional approaches, including SExtractor and DAOPHOT, the proposed framework exhibits a markedly superior detection capability under low-SNR conditions near the detection limit. In future applications, ATD-DL may be extended to space object detection tasks, where it has the potential to substantially improve the identification of extremely faint targets.

Yanrong Chen, Zhiwen Shi, Anwar Eziz et al.

High-accuracy Digital Elevation Models (DEMs) are critical for hydrological and ecological applications in low-relief arid basins, yet Interferometric Synthetic Aperture Radar (InSAR)-derived DEMs suffer from significant altitudinal errors due to temporal decorrelation and phase unwrapping artifacts, particularly in flat terrains. To address these limitations, we developed a novel machine learning framework that synergizes Sentinel-1 InSAR, UAV photogrammetry, Sentinel-2 spectral indices, and ALOS topographic features to enhance DEM accuracy. The approach was validated in Northwest China’s Taitema Lake basin across 13 sample plots covering diverse arid surface types (dunes, wetlands, playas). Four algorithms – Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Polynomial Regression (PR) – were rigorously evaluated. Without topographic data, SVM achieved the highest accuracy (test-set R2 = 0.8564). Integrating terrain features with RF further improved performance (R2 = 0.8634, MAE = 1.0683 m), reducing errors from approximately [−10, 27] m to predominantly ±6 m. The RF-corrected DEM exhibited a 42.8% decrease in standard deviation (2.60 m → 1.49 m) and a substantial R2 increase (16.4% → 89.1%). Shapley Additive exPlanations (SHAP) interpretability analysis identified slope and near-infrared reflectance as dominant error-correction features. The corrected DEMs demonstrate enhanced terrain continuity, minimized elevation noise, and offer a scalable, efficient solution for InSAR post-processing in ecologically sensitive arid regions.

J. Rho, S.-H. Park, R. Arendt et al.

We present JWST NIRCam (F356W and F444W filters) and MIRI (F770W) images and NIRSpec Integral Field Unit (IFU) spectroscopy of the young Galactic supernova remnant Cassiopeia A (Cas A) to probe the physical conditions for molecular CO formation and destruction in supernova ejecta. We obtained the data as part of a JWST survey of Cas A. The NIRCam and MIRI images map the spatial distributions of synchrotron radiation, Ar-rich ejecta, and CO on both large and small scales, revealing remarkably complex structures. The CO emission is stronger at the outer layers than the Ar ejecta, which indicates the re-formation of CO molecules behind the reverse shock. NIRSpec-IFU spectra (3–5.5 μ m) were obtained toward two representative knots in the NE and S fields that show very different nucleosynthesis characteristics. Both regions are dominated by the bright fundamental rovibrational band of CO in the two R and P branches, with strong [Ar vi ] and relatively weaker, variable strength ejecta lines of [Si ix ], [Ca iv ], [Ca v ], and [Mg iv ]. The NIRSpec-IFU data resolve individual ejecta knots and filaments spatially and in velocity space. The fundamental CO band in the JWST spectra reveals unique shapes of CO, showing a few tens of sinusoidal patterns of rovibrational lines with pseudocontinuum underneath, which is attributed to the high-velocity widths of CO lines. Our results with LTE modeling of CO emission indicate a temperature of ∼1080 K and provide unique insight into the correlations between dust, molecules, and highly ionized ejecta in supernovae and have strong ramifications for modeling dust formation that is led by CO cooling in the early Universe.

Yanan Feng, Xiaohu Li, Xiaofeng Yang et al.

S-type asymptotic giant branch (AGB) stars are defined by their carbon-to-oxygen (C/O) ratio approaching unity. However, observations of circumstellar molecules in these stars are limited and challenging. In this study, we used the James Clerk Maxwell Telescope to search for cyanide (CN) in 12 selected S-type AGB stars, with only 4 of these stars displaying CN spectral line signals. The column density and fractional abundance of CN were calculated assuming local thermodynamic equilibrium, and the average CN-to-hydrogen-cyanide (HCN) abundance ratio of the four sources is about 0.036. We investigate, for the first time, the relationship between CN and HCN fractional abundances in all types of AGB stars, finding that the ratio is similar in O-rich and S-type stars, while those in C-rich stars are quite different. This result supports the idea that the level of HCN photodissociation plays a crucial role in determining the CN abundance in the circumstellar envelopes of AGB stars at various stages of their evolution.

Kaidan Shi, Yanan Su, Jinhao Xu et al.

Reservoirs play a critical role in terrestrial hydrological systems, but the contribution of small and medium-sized ones is rarely considered and recorded. Particularly in developing countries, there is a rapid increase of such reservoirs due to their quick construction. Accurately identifying these reservoirs is important for understanding social and economic development, but distinguishing them from other natural water bodies poses a significant challenge. Thus, we propose a method to identify reservoirs using high-resolution satellite images and deep learning algorithms. We trained models with various parameters and network structures, and You Only Look Once version 7 (YOLOv7) outperformed other algorithms and was selected to build the final model. The method was applied to a region in northwestern Iran, characterized by an abundance of reservoirs of various sizes. Evaluation results indicated that our method was highly accurate (mAP: 0.79, Recall: 0.76, Precision: 0.82). The YOLOv7 model was able to automatically identify 650 reservoirs in the entire study region, indicating that the proposed method can accurately detect reservoirs and has the potential for broader-scale surveys, even global applications.

Qian Zeng, Ran Li, Jin Wang

We investigated the impact of nonequilibrium conditions on the transmission and recovery of information through noisy channels. By measuring the recoverability of messages from an information source, we demonstrate that the ability to recover information is connected to the nonequilibrium behavior of the information flow, particularly in terms of sequential information transfer. We discovered that the mathematical equivalence of information recoverability and entropy production characterizes the dissipative nature of information transfer. Our findings show that both entropy production (or recoverability) and mutual information increase monotonically with the nonequilibrium strength of information dynamics. These results suggest that the nonequilibrium dissipation cost can enhance the recoverability of noise messages and improve the quality of information transfer. Finally, we propose a simple model to test our conclusions and found that the numerical results support our findings.

Melvyn Tyloo

Networks are widely used to model the interaction between individual dynamic systems. In many instances, the total number of units and interaction coupling are not fixed in time, and instead constantly evolve. In networks, this means that the number of nodes and edges both change over time. Various properties of coupled dynamic systems, such as their robustness against noise, essentially depend on the structure of the interaction network. Therefore, it is of considerable interest to predict how these properties are affected when the network grows as well as their relationship to the growth mechanism. Here, we focus on the time evolution of a network’s Kirchhoff index. We derive closed-form expressions for its variation in various scenarios, including the addition of both edges and nodes. For the latter case, we investigate the evolution where single nodes with one or two edges connecting to existing nodes are added recursively to a network. In both cases, we derive the relations between the properties of the nodes to which the new node connects along with the global evolution of network robustness. In particular, we show how different scalings of the Kirchhoff index can be obtained as a function of the number of nodes. We illustrate and confirm this theory via numerical simulations of randomly growing networks.

Zhenzhong Shi, Sachith Dissanayake, Philippe Corboz et al.

SrCu2(BO3)2 is a 2D quantum antiferromagnet on a particular frustrated lattice showing multiple magnetization plateaus and quantum phase transitions under high pressure. Here the authors uncover novel magnetic phases in this material under combined effects of extreme magnetic field and pressure.

Abdul W. Khanday, Sudhaker Upadhyay, Prince A. Ganai

Abstract We study the clustering of galaxies in generalized uncertainty principle (GUP) modified Newtonian potential. We compute the corrected N-particle partition function which leads to the modified equations of state. The GUP corrected clustering parameter is compared with the original clustering parameter. An investigation of the distribution function for the system of galaxies is also made. Moreover, we analyze the effect of GUP on the two-point correlation function of the system. In order to find the optimal value of the clustering parameter we perform data analysis and compare our model with the data.

The ATLAS collaboration, G. Aad, B. Abbott et al.

Abstract A direct search for Higgs bosons produced via vector-boson fusion and subsequently decaying into invisible particles is reported. The analysis uses 139 fb −1 of pp collision data at a centre-of-mass energy of s $$ \sqrt{s} $$ = 13 TeV recorded by the ATLAS detector at the LHC. The observed numbers of events are found to be in agreement with the background expectation from Standard Model processes. For a scalar Higgs boson with a mass of 125 GeV and a Standard Model production cross section, an observed upper limit of 0.145 is placed on the branching fraction of its decay into invisible particles at 95% confidence level, with an expected limit of 0.103. These results are interpreted in the context of models where the Higgs boson acts as a portal to dark matter, and limits are set on the scattering cross section of weakly interacting massive particles and nucleons. Invisible decays of additional scalar bosons with masses from 50 GeV to 2 TeV are also studied, and the derived upper limits on the cross section times branching fraction decrease with increasing mass from 1.0 pb for a scalar boson mass of 50 GeV to 0.1 pb at a mass of 2 TeV.

Chen Yu, Zhenhong Li, Geoffrey Blewitt

Abstract Precipitable water vapor (PWV) from numerical weather models, such as the latest generation of European Centre for Medium‐Range Weather Forecasts (ECMWF) reanalysis (ERA5) and the ECMWF High RESolution (HRES) models, are important to meteorological studies and to error mitigation of geodetic observations such as Interferometric Synthetic Aperture Radar. In this study, we provide global validations of these new weather models with respect to Global Positioning System (GPS, ∼13,000 stations) and Moderate Resolution Imaging Spectrometer (MODIS, ∼1 km resolution) using data from January 2016 to December 2018 of every 1 h. The global standard deviations of the Zenith Tropospheric Delay (ZTD) differences (DSTDs) between weather models and GPS are 1.69 cm for ERA5 and 1.54 cm for HRES. The global PWV DSTDs between weather models and MODIS are 0.34 cm for ERA5 and 0.32 cm for HRES. The two weather models generally perform better in western North America, Europe, and Arctic by having low ZTD DSTDs (<1.3 cm) or PWV DSTDs (<0.3 cm). HRES also has a low ZTD DSTD of less than 1.3 cm in Antarctic, Japan, New Zealand, and Africa and outperforms ERA5 in most regions of the world, despite the fact that 83% of the HRES PWV values are temporally interpolated (from 6 to 1‐h). However, under extreme weather conditions, ERA5 performs better owing to its high temporal resolution (1 h). Our results can be used as a global reference for evaluating uncertainties when utilizing these weather models.

Qianheng Du, Lijun Wu, Huibo Cao et al.

Abstract Iron diantimonide is a material with the highest known thermoelectric power. By combining scanning transmission electron microscopic study with electronic transport neutron, X-ray scattering, and first principle calculation, we identify atomic defects that control colossal thermopower magnitude and nanoprecipitate clusters with Sb vacancy ordering, which induce additional phonon scattering and substantially reduce thermal conductivity. Defects are found to cause rather weak but important monoclinic distortion of the unit cell P n n m → P m. The absence of Sb along [010] for high defect concentration forms conducting path due to Fe d orbital overlap. The connection between atomic defect anisotropy and colossal thermopower in FeSb2 paves the way for the understanding and tailoring of giant thermopower in related materials.

M. Bruno, M. T. Hansen

Abstract We discuss a method to construct hadronic scattering and decay amplitudes from Euclidean correlators, by combining the approach of a regulated inverse Laplace transform with the work of Maiani and Testa [1]. Revisiting the original result of ref. [1], we observe that the key observation, i.e. that only threshold scattering information can be extracted at large separations, can be understood by interpreting the correlator as a spectral function, ρ(ω), convoluted with the Euclidean kernel, e −ωt , which is sharply peaked at threshold. We therefore consider a modification in which a smooth step function, equal to one above a target energy, is inserted in the spectral decomposition. This can be achieved either through Backus-Gilbert-like methods or more directly using the variational approach. The result is a shifted resolution function, such that the large t limit projects onto scattering or decay amplitudes above threshold. The utility of this method is highlighted through large t expansions of both three- and four-point functions that include leading terms proportional to the real and imaginary parts (separately) of the target observable. This work also presents new results relevant for the un-modified correlator at threshold, including expressions for extracting the Nπ scattering length from four-point functions and a new strategy to organize the large t expansion that exhibits better convergence than the expansion in powers of 1/t.

Peter Athron, Csaba Balazs, Andrew Fowlie et al.

Abstract Motivated by the fact that the Next-to-Minimal Supersymmetric Standard Model is one of the most plausible models that can accommodate electroweak baryogenesis, we analyze its phase structure by tracing the temperature dependence of the minima of the effective potential. Our results reveal rich patterns of phase structure that end in the observed electroweak symmetry breaking vacuum. We classify these patterns according to the first transition in their history and show the strong first-order phase transitions that may be possible in each type of pattern. These could allow for the generation of the matter-antimatter asymmetry or potentially observable gravitational waves. For a selection of benchmark points, we checked that the phase transitions completed and calculated the nucleation temperatures. We furthermore present samples that feature strong first-order phase transitions from an extensive scan of the whole parameter space. We highlight common features of our samples, including the fact that the Standard Model like Higgs is often not the lightest Higgs in the model.

Gladys Villegas, Wenzhi Liao, Ronald Criollo et al.

Close-range hyperspectral images are a promising source of information in plant biology, in particular, for in vivo study of physiological changes. In this study, we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological information. The detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation, disease infections, and environmental conditions have in plants. We tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote sensing. Experimental results demonstrate the efficiency of our fusion approach, with significant improvements over some conventional methods.