Article
Astronomy & Astrophysics
C. Aerts, G. Molenberghs, J. De Ridder
Summary: This study evaluates the properties of 15062 newly discovered Gaia DR3 gravity-mode pulsators to increase the sample of optimal targets for future gravito-inertial asteroseismology. The selected gravity-mode pulsators have properties in line with those of their well-known Kepler analogues, revealing the role of Gaia in asteroseismology.
ASTRONOMY & ASTROPHYSICS
(2023)
Article
Astronomy & Astrophysics
B. Biswas, E. E. O. Ishida, J. Peloton, A. Moller, M. V. Pruzhinskaya, R. S. de Souza, D. Muthukrishna
Summary: This paper describes the implementation of a fast transient classification algorithm in the FINK broker and reports the classification results based on simulated catalogues and real data from the ZTF alert stream. The algorithm successfully distinguishes fast transient events from non-fast transient events, and has been widely applied in the field of astronomy.
ASTRONOMY & ASTROPHYSICS
(2023)
Article
Astronomy & Astrophysics
Sergey Karpov, Oleg Yu Malkov, Gang Zhao
Summary: Selection of extreme objects in data from large-scale sky surveys is a powerful tool for detecting new classes of astrophysical objects or rare stages of their evolution. In addition to the traditional approach of cross-matching catalogues and analyzing color indices, attention should also be paid to objects found in only one survey, which may lead to the discovery of transients and objects with extreme color values.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
Zoe Ansari, Adriano Agnello, Christa Gall
Summary: This study aimed to resolve model degeneracies and separate intrinsic physical properties of astrophysical sources from extrinsic systematics using mixture density networks. The method demonstrated competitive performance in producing full probability distributions for photo-z estimates and can be applied to wide-field surveys with varying extinction levels.
ASTRONOMY & ASTROPHYSICS
(2021)
Article
Astronomy & Astrophysics
E. Paunzen
Summary: The Geneva seven-colour photometric system has been successfully applied to the study of various astrophysical objects and a new catalogue containing highly accurate measurements has been generated, providing new data sources for various applications.
ASTRONOMY & ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
M. Kovacevic, M. Pasquato, M. Marelli, A. De Luca, R. Salvaterra, A. Belfiore
Summary: This study used unsupervised machine learning to analyze a large dataset of light-curve parameters, revealing its clustering structure. The results showed that the SOM method can quickly identify groups, speeding up manual characterization and addressing the issue of fitting simple temporal models to light curves.
ASTRONOMY & ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
P. Vermot, J. Palous, B. Barna, S. Ehlerova, M. R. Morris, R. Wunsch
Summary: We characterized the properties of stellar populations in the central regions of nearby galactic nuclei using spatially resolved spectroscopic observations. By simultaneously fitting various observables, including line-of-sight velocity, velocity dispersion, and spectral features, we determined the age, mass, and 3D geometry of the young and old stellar populations in the nuclear star cluster and surrounding disk. Our results are consistent with previous independent measurements.
ASTRONOMY & ASTROPHYSICS
(2023)
Article
Astronomy & Astrophysics
Gy. M. Szabo, Sz. Kalman, L. Borsato, V. Hegedus, Sz. Meszaros, R. Szabo
Summary: This study explores the distribution of giant planets on orbits with P-orb < 3 days and proposes that possible causes for the formation of sub-Jovian or Neptunian desert include multiple scenarios, predicting different relationships between the boundary position and stellar parameters. By analyzing the distribution of exoplanets in various 2D and 3D projections, the study finds that the boundary is influenced by several stellar parameters and provides quantitative formulae for the boundary's dependence on different-sized planets. The findings suggest that the formation of the boundary might be associated with the irradiation-driven loss of atmospheres of moderately massive planets.
ASTRONOMY & ASTROPHYSICS
(2023)
Article
Astronomy & Astrophysics
A. M. Kutkin, T. A. Oosterloo, R. Morganti, E. A. K. Adams, M. Mancini, B. Adebahr, W. J. G. de Blok, H. Denes, K. M. Hess, J. M. van der Hulst, D. M. Lucero, V. A. Moss, A. Berger, R. van den Brink, W. A. van Cappellen, L. Connor, S. Damstra, G. M. Loose, J. van Leeuwen, Y. Maan, A. Mika, M. J. Norden, A. R. Offringa, L. C. Oostrum, D. van der Schuur, D. Vohl, S. J. Wijnholds, J. Ziemke
Summary: The first data release from the Apertif survey includes 3074 radio continuum images, obtained using a new machine-learning method to obtain primary beam models. The dataset also contains a large number of newly detected radio sources, as well as cross-matching results with other catalogs. This is important for studying long-term transient sources and the spectral properties of the sources.
ASTRONOMY & ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
A. Moya, R. J. Lopez-Sastre
Summary: This study aims to use artificial intelligence regression models to estimate stellar masses and radii accurately. By stacking multiple regression models, the most accurate estimates were obtained, improving the accuracy by a factor of two compared to currently used empirical relation-based models. The proposed AI models demonstrated a generalization capability to estimate masses and radii that were not observed during the training step.
ASTRONOMY & ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
K. Lakshmipathaiah, S. Vig, Matthew L. N. Ashby, Joseph L. Hora, Miju Kang, Rama Krishna Sai S. Gorthi
Summary: In this study, machine learning algorithms are applied to classify infrared-selected targets for NASA's SPHEREx mission. The approach differs from previous methods by utilizing photometric colors and magnitudes from multiple infrared bands and employing machine and deep learning algorithms. The results provide probabilistic classification of different types of objects, including young stellar objects, asymptotic giant branch stars, active galactic nuclei, and main-sequence stars.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2023)
Article
Astronomy & Astrophysics
P. F. Wang, J. L. Han, J. Xu, C. Wang, Y. Yan, W. C. Jing, W. Q. Su, D. J. Zhou, T. Wang
Summary: This study presents polarization profiles of 682 pulsars obtained from observations using the FAST radio telescope. Among them, about 460 pulsars exhibit polarization profiles that have not been previously observed. The profiles show diverse features such as S-shaped swings, orthogonal modes, highly linearly polarized or strongly circularly polarized components. Frequency dependencies are found in the linear and circular polarization as well as the widths of pulse profiles.
RESEARCH IN ASTRONOMY AND ASTROPHYSICS
(2023)
Article
Astronomy & Astrophysics
K. R. Sreenivas, V Perdelwitz, L. Tal-Or, T. Trifonov, S. Zucker, T. Mazeh
Summary: Using fifteen years of radial velocity data, this study identified two Jupiter analogs orbiting around F8V star HD 103891 and Solar-like star HD 105779. The study highlights the importance of long-term radial velocity surveys in studying planetary occurrence beyond the snow line of Solar-like stars.
ASTRONOMY & ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
Jie Wang, Hailong Zhang, Na Wang, Xinchen Ye, Wanqiong Wang, Jia Li, Meng Zhang, Yazhou Zhang, Xu Du
Summary: This paper investigates the delay issues faced by the Xinjiang Astronomical Observatory Data Center and proposes a solution using software-defined network technology. By designing a novel reconfiguration method and a traffic load-balancing algorithm, transmission performance and quality can be improved.
RESEARCH IN ASTRONOMY AND ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
F. Stoppa, P. Vreeswijk, S. Bloemen, S. Bhattacharyya, S. Caron, G. Johannesson, R. Ruiz de Austri, C. van den Oetelaar, G. Zaharijas, P. J. Groot, E. Cator, G. Nelemans
Summary: This paper introduces an innovative framework, ASID-L, for rapid localization of sources in optical images using computer vision techniques. Experimental results show that ASID-L outperforms the commonly used SExtractor method in terms of the number and accuracy of detected sources.
ASTRONOMY & ASTROPHYSICS
(2022)
Article
Multidisciplinary Sciences
Mariko Kimura, Keisuke Isogai, Taichi Kato, Yoshihiro Ueda, Satoshi Nakahira, Megumi Shidatsu, Teruaki Enoto, Takafumi Hori, Daisaku Nogami, Colin Littlefield, Ryoko Ishioka, Ying-Tung Chen, Sun-Kun King, Chih-Yi Wen, Shiang-Yu Wang, Matthew J. Lehner, Megan E. Schwamb, Jen-Hung Wang, Zhi-Wei Zhang, Charles Alcock, Tim Axelrod, Federica B. Bianco, Yong-Ik Byun, Wen-Ping Chen, Kem H. Cook, Dae-Won Kim, Typhoon Lee, Stuart L. Marshall, Elena P. Pavlenko, Oksana I. Antonyuk, Kirill A. Antonyuk, Nikolai V. Pit, Aleksei A. Sosnovskij, Julia V. Babina, Aleksei V. Baklanov, Alexei S. Pozanenko, Elena D. Mazaeva, Sergei E. Schmalz, Inna V. Reva, Sergei P. Belan, Raguli Ya. Inasaridze, Namkhai Tungalag, Alina A. Volnova, Igor E. Molotov, Enrique de Miguel, Kiyoshi Kasai, William L. Stein, Pavol A. Dubovsky, Seiichiro Kiyota, Ian Miller, Michael Richmond, William Goff, Maksim V. Andreev, Hiromitsu Takahashi, Naoto Kojiguchi, Yuki Sugiura, Nao Takeda, Eiji Yamada, Katsura Matsumoto, Nick James, Roger D. Pickard, Tamas Tordai, Yutaka Maeda, Javier Ruiz, Atsushi Miyashita, Lewis M. Cook, Akira Imada, Makoto Uemura
Article
Astronomy & Astrophysics
Dae-Won Kim, Coryn A. L. Bailer-Jones
ASTRONOMY & ASTROPHYSICS
(2016)
Article
Multidisciplinary Sciences
Hahn Yi, Jeongeun Hwang, Hyun-Jin Bae, Namkug Kim
SCIENTIFIC REPORTS
(2019)
Article
Medicine, General & Internal
Dong-Woo Seo, Hahn Yi, Beomhee Park, Youn-Jung Kim, Dae Ho Jung, Ilsang Woo, Chang Hwan Sohn, Byuk Sung Ko, Namkug Kim, Won Young Kim
JOURNAL OF CLINICAL MEDICINE
(2020)
Article
Medicine, General & Internal
Dong-Woo Seo, Hahn Yi, Hyun-Jin Bae, Youn-Jung Kim, Chang-Hwan Sohn, Shin Ahn, Kyoung-Soo Lim, Namkug Kim, Won-Young Kim
Summary: The study demonstrated the potential of machine learning models in predicting good neurological outcomes for OHCA patients before ROSC by analyzing different variables and comparing performance metrics to identify the best predictive model.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Astronomy & Astrophysics
Dae-Won Kim, Doyeob Yeo, Coryn A. L. Bailer-Jones, Giyoung Lee
Summary: In new astronomical surveys, a light curve classifier based on deep neural networks and transfer learning has been developed, showing successful knowledge transfer between data sets even with limited labeled data available in the new survey.
ASTRONOMY & ASTROPHYSICS
(2021)
Article
Astronomy & Astrophysics
Joongoo Lee, Min-Su Shin
Summary: In this study, a three-stage training approach for neural networks is proposed, which is capable of both photometric redshift estimation and detection of out-of-distribution objects. The use of unlabeled data for training the networks enables reliable performance in practice. The model demonstrates successful photometric redshift estimation and accurate identification of out-of-distribution objects.
ASTRONOMICAL JOURNAL
(2022)
Article
Astronomy & Astrophysics
Joongoo Lee, Min-Su Shin
Summary: A new machine-learning model has been developed for improving the accuracy of estimating photometric redshifts for galaxies, utilizing neural networks and ensemble learning. The model exhibits high accuracy for densely populated test samples in the input space, but accuracy diminishes for sparse samples and unseen objects.
ASTRONOMICAL JOURNAL
(2021)
Article
Medicine, General & Internal
Chun-Song Youn, Hahn Yi, Youn-Jung Kim, Hwan Song, Namkug Kim, Won-Young Kim
Summary: This study aimed to develop a machine learning model for identifying significant coronary artery disease among out-of-hospital cardiac arrest (OHCA) survivors. The study used data from a Korean registry and found that the voting classifier model showed the highest accuracy in predicting significant lesions. Additionally, eight variables were identified as significant in the machine learning models.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Astronomy & Astrophysics
Sangho Choi, Hong-Kyu Moon, Dong-Goo Roh, Min-Su Shin, Myung-Jin Kim, Young-Jong Sohn
Summary: We present multiband photometry data of 6793 asteroids observed from 2015 to 2017 using the Korea Microlensing Telescope Network telescopes. Taxonomic classifications were applied to classify the objects, both in a 2D color plane and a newly defined 3D color space. The results show a decrease in the number of S types and an increase in the fraction of C types with heliocentric distance in the main belt, while D types dominate in the Jupiter Trojans.
PLANETARY SCIENCE JOURNAL
(2023)
Article
Astronomy & Astrophysics
Min-Su Shin, Seo-Won Chang, Hahn Yi, Dae-Won Kim, Myung-Jin Kim, Yong-Ik Byun
ASTRONOMICAL JOURNAL
(2018)
Article
Astronomy & Astrophysics
Rafael Alves Batista, Min-Su Shin, Julien Devriendt, Dmitri Semikoz, Guenter Sigl
Article
Astronomy & Astrophysics
Sangeeta Malhotra, James E. Rhoads, K. Finkelstein, Huan Yang, Chris Carilli, Francoise Combes, Karine Dassas, Steven Finkelstein, Brenda Frye, Maryvonne Gerin, Pierre Guillard, Nicole Nesvadba, Jane Rigby, Min-Su Shin, Marco Spaans, Michael A. Strauss, Casey Papovich
ASTROPHYSICAL JOURNAL
(2017)