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Star clusters are studied widely both as benchmarks for stellar evolution models and in their own right. Cluster age and mass distributions within galaxies are probes of star formation histories, and of cluster formation and disruption…

Solar and Stellar Astrophysics · Physics 2015-05-18 Morgan Fouesneau , Ariane Lançon

The vast volume of data generated by modern astronomical surveys offers test beds for the application of machine-learning. It is important to evaluate potential existing tools and determine those that are optimal for extracting scientific…

Instrumentation and Methods for Astrophysics · Physics 2019-09-04 Rafael Garcia-Dias , Carlos Allende Prieto , Jorge Sánchez Almeida , Pedro Alonso Palicio

We present a statistical analysis of the properties of a large sample of dynamically hot old stellar systems, from globular clusters to giant ellipticals, which was performed in order to investigate the origin of ultra-compact dwarf…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-04 Tanuka Chattopadhyay , Margarita Sharina , Emmanuel Davoust , Tuli De , Asis Kumar Chattopadhyay

A major goal in the field of galaxy formation is to understand the formation of the Milky Way's disk. The first step toward doing this is to empirically describe its present state. We use the new high-dimensional dataset of 19 abundances…

Astrophysics of Galaxies · Physics 2020-02-19 Bridget L. Ratcliffe , Melissa K. Ness , Kathryn V. Johnston , Bodhisattva Sen

Micro-panel data are collected and analysed in many research and industry areas. Cluster analysis of micro-panel data is an unsupervised learning exploratory method identifying subgroup clusters in a data set which include homogeneous…

Machine Learning · Statistics 2018-07-17 Lukas Sobisek , Maria Stachova , Jan Fojtik

Due to advances in sensors, growing large and complex medical image data have the ability to visualize the pathological change in the cellular or even the molecular level or anatomical changes in tissues and organs. As a consequence, the…

Machine Learning · Statistics 2016-02-17 Nan Lin , Junhai Jiang , Shicheng Guo , Momiao Xiong

Variable stars play a key role in understanding the Milky Way and the universe. The era of astronomical big data presents new challenges for quick identification of interesting and important variable stars. Accurately estimating the periods…

Instrumentation and Methods for Astrophysics · Physics 2022-12-21 Xiao-Hui Xu , Qing-Feng Zhu , Xu-Zhi Li , Bin Li , Hang Zheng , Jin-Sheng Qiu , Hai-Bin Zhao

Eclipsing binaries are vital for directly determining stellar parameters without reliance on models or scaling relations. Spectroscopically derived parameters of detached and semi-detached binaries allow us to determine component masses…

Solar and Stellar Astrophysics · Physics 2017-11-15 Rachel A. Matson , Douglas R. Gies , Zhao Guo , Stephen J. Williams

Data mining techniques must be developed and applied to analyse the large public data bases containing hundreds to thousands of millions entries. The aim of this study is to develop methods for locating previously unknown stellar clusters…

Astrophysics of Galaxies · Physics 2015-06-04 O. Solin , E. Ukkonen , L. Haikala

In this thesis, we propose several modelling strategies to tackle evolving data in different contexts. In the framework of static clustering, we start by introducing a soft kernel spectral clustering (SKSC) algorithm, which can better deal…

Social and Information Networks · Computer Science 2014-11-24 Rocco Langone

Transiting extrasolar planets constitute only a small fraction of the range of stellar systems found to display periodic, shallow dimmings in wide-field surveys employing small-aperture camera arrays. Here we present an efficient selection…

We present a detailed light curve analysis of publicly available V band observations of 62 binary stars, mostly contact binaries, obtained by the All Sky Automated Survey (ASAS)-3 project between 2000 and 2009. Eclipsing binaries are…

Solar and Stellar Astrophysics · Physics 2015-05-20 Sukanta Deb , Harinder P. Singh

Co-clustering is a specific type of clustering that addresses the problem of finding groups of objects without necessarily considering all attributes. This technique has shown to have more consistent results in high-dimensional sparse data…

Machine Learning · Computer Science 2021-10-28 Yuri Santos , Jônata Tyska , Vania Bogorny

Many clustering algorithms when the data are curves or functions have been recently proposed. However, the presence of contamination in the sample of curves can influence the performance of most of them. In this work we propose a robust,…

Functional data clustering is to identify heterogeneous morphological patterns in the continuous functions underlying the discrete measurements/observations. Application of functional data clustering has appeared in many publications across…

Methodology · Statistics 2022-10-04 Mimi Zhang , Andrew Parnell

We present a new automated algorithm to identify, track, and characterize small-scale brightening associated with solar eruptive phenomena observed in H{\alpha}. The temporal spatially-localized changes in chromospheric intensities can be…

Solar and Stellar Astrophysics · Physics 2015-05-30 M. S. Kirk , K. S. Balasubramaniam , J. Jackiewicz , B. J. McNamara , R. T. J. McAteer

Microlensing is one of the most promising tools for discovering stellar-mass black holes (BHs) in the Milky Way because it allows us to probe dark or faint celestial compact objects. While the existence of stellar-mass BHs has been…

High Energy Astrophysical Phenomena · Physics 2024-04-16 Kyungmin Kim , Yeong-Bok Bae , Yoon-Hyun Ryu

We present new measurements of the centers for 65 Milky Way globular clusters. Centers were determined by fitting ellipses to the density distribution within the inner $2\arcmin$ of the cluster center, and averaging the centers of these…

Astrophysics of Galaxies · Physics 2015-05-19 Ryan Goldsbury , Harvey B. Richer , Jay Anderson , Aaron Dotter , Ata Sarajedini , Kristin Woodley

We develop a new method to locally cluster curves and discover functional motifs, i.e.~typical ``shapes'' that may recur several times along and across the curves capturing important local characteristics. In order to identify these shared…

Methodology · Statistics 2023-01-30 Marzia A. Cremona , Francesca Chiaromonte

Clustering is an effective tool for astronomical spectral analysis, to mine clustering patterns among data. With the implementation of large sky surveys, many clustering methods have been applied to tackle spectroscopic and photometric data…

Instrumentation and Methods for Astrophysics · Physics 2022-12-19 Haifeng Yang , Chenhui Shi , Jianghui Cai , Lichan Zhou , Yuqing Yang , Xujun Zhao , Yanting He , Jing Hao