Search Publications

Simultaneous NICER and NuSTAR Observations of the Neutron Star Low-mass X-Ray Binary Serpens X-1

Fabian, A. C.; Miller, J. M.; Tomsick, J. A. +5 more

We present the first contemporaneous NICER and NuSTAR analysis of the low-mass X-ray binary Serpens X-1 obtained in 2023 June, performing broadband X-ray spectral analysis modeling of the reprocessed emission with RELXILLNS from 0.4 to 30 keV. We test various continuum and background estimation models to ensure that our results do not hinge on the…

The reason for the widespread energetic storm particle event of 13 March 2023

Palmerio, E.; Jebaraj, I. C.; Riihonen, E. +20 more

Context. On 13 March 2023, when the Parker Solar Probe spacecraft (S/C) was situated on the far side of the Sun as seen from Earth, a large solar eruption took place, which created a strong solar energetic particle (SEP) event observed by multiple S/C all around the Sun. The energetic event was observed at six well-separated locations in the helio…

Correction to: Constraints on light decaying dark matter candidates from 16 yr of INTEGRAL/SPI observations

Calore, F.; Dekker, A.; Serpico, P. D. +1 more

A critical evaluation of the elemental abundances and evolutionary status of 15 Vul (HD 189849): the first identification of an evolved A_m star

Çay, M. Taşkın; Çay, İpek H.; Civelekler, Betül

Understanding the evolution of metallic-line (${\rm A}_{\rm m}$) stars requires well-determined atmospheric parameters and abundance patterns of the selected candidates. In this study, we present a detailed abundance analysis of 15 Vul (HD 189849), identified as a m…

Search for hot subdwarf stars from SDSS images using a deep learning method: SwinBayesNet

Yi, Zhenping; Lei, Zhenxin; Kong, Xiaoming +5 more

Hot subdwarfs are essential for understanding the structure and evolution of low-mass stars, binary systems, astroseismology, and atmospheric diffusion processes. In recent years, deep learning has driven significant progress in hot subdwarf searches. However, most approaches tend to focus on modelling with spectral data, which are inherently more…

Molecular inventory of the environment of a young eruptive star: Case study of the classical FU Orionis star V1057 Cyg

Menten, K. M.; Ábrahám, P.; Kóspál, Á. +6 more

Context. Studying accretion-driven episodic outbursts in young stellar objects (YSOs) is crucial for understanding the later stages of star and planet formation. FU Orionis-type objects (briefly, FUors) represent a small but rather central class of YSOs, whose outbursts are characterized by a rapid multi-magnitude increase in brightness at optical…

Photometric Stellar Parameters for 195,478 Kepler Input Catalog Stars

Huang, Yang; Liu, Jifeng; Beers, Timothy C. +9 more

The stellar atmospheric parameters and physical properties of stars in the Kepler Input Catalog (KIC) are of great significance for the study of exoplanets, stellar activity, and asteroseismology. However, despite extensive effort over the past decades, accurate spectroscopic estimates of these parameters are available for only about half of the s…

New red supergiant stars in the other side of our Galaxy

Gao, Jian; Ren, Yi; Jiang, Biwei +3 more

Red supergiant stars (RSGs) are massive stars in a late stage of evolution, crucial for understanding stellar life cycles and Galactic structure. However, RSGs on the far side of our Galaxy have been underexplored due to observational challenges. In this study, we introduce a novel method and present a new catalogue comprising 474 RSGs situated on…

Night O₂ (a¹Δ_g) airglow spatial distribution and temporal behavior on Venus based on SPICAV IR/VEx nadir dataset

Montmessin, F.; Fedorova, A.; Korablev, O. +6 more

The infrared O₂ (a¹Δ_g) airglow driven by the subsolar to antisolar circulation occurs between two global circulation regimes on Venus: the zonal super-rotation below 90 km and the subsolar to antisolar circulation over 120 km. Here we report the complete global results of SPICAV IR/Venus Express observations of O

Half a Million Binary Stars Identified from the Low-resolution Spectra of LAMOST

Liu, Chao; Chen, Xiaodian; Wang, Jie +2 more

Binary stars are prevalent yet challenging to detect. We present a novel approach using convolutional neural networks (CNNs) to identify binary stars from low-resolution spectra obtained by the LAMOST survey. The CNN is trained on a data set that distinguishes binaries from single main-sequence stars based on their positions on the Hertzsprung–Rus…