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Star cluster studies hold the key to understanding star formation, stellar evolution, and origin of galaxies. The detection and characterization of clusters depend on the underlying background density and the cluster richness. We examine…

Astrophysics of Galaxies · Physics 2018-11-07 Srirag Nambiar , Soumyadeep Das , Sarita Vig , Gorthi R. K. S. S. Manyam

The mass, or binding energy, is the basis property of the atomic nucleus. It determines its stability, and reaction and decay rates. Quantifying the nuclear binding is important for understanding the origin of elements in the universe. The…

Nuclear Theory · Physics 2018-10-03 Léo Neufcourt , Yuchen Cao , Witold Nazarewicz , Frederi Viens

Current analysis of astronomical data are confronted with the daunting task of modeling the awkward features of astronomical data, among which heteroscedastic (point-dependent) errors, intrinsic scatter, non-ignorable data collection…

Instrumentation and Methods for Astrophysics · Physics 2011-12-19 S. Andreon

A Bayesian probability based approach is applied to the problem of detecting and parameterizing oscillations in the upper solar atmosphere for the first time. Due to its statistical origin, this method provides a mechanism for determining…

Astrophysics · Physics 2008-12-18 M. S. Marsh , J. Ireland , T. Kucera

We present SPISEA (Stellar Population Interface for Stellar Evolution and Atmospheres), an open-source Python package that simulates simple stellar populations. The strength of SPISEA is its modular interface which offers the user control…

Solar and Stellar Astrophysics · Physics 2020-09-09 M. W. Hosek , J. R. Lu , C. Y. Lam , A. K. Gautam , K. E. Lockhart , D. Kim , S. Jia

I compare the mass values obtained with data taken from the Arcminute Microkelvin Imager (AMI) radio interferometer system and from the Planck satellite. The former of these uses a Bayesian analysis pipeline that parameterises a cluster in…

Cosmology and Nongalactic Astrophysics · Physics 2020-02-13 Kamran Javid

A software library for constructing and learning probabilistic models is presented. The library offers a set of building blocks from which a large variety of static and dynamic models can be built. These include hierarchical models for…

Mathematical Software · Computer Science 2012-07-09 Markus Harva , Tapani Raiko , Antti Honkela , Harri Valpola , Juha Karhunen

Astronomy is in an era where all-sky surveys are mapping the Galaxy. The plethora of photometric, spectroscopic, asteroseismic and astrometric data allows us to characterise the comprising stars in detail. Here we quantify to what extent…

Solar and Stellar Astrophysics · Physics 2017-05-03 George C. Angelou , Earl P. Bellinger , Saskia Hekker , Sarbani Basu

Context: Star-forming regions, stellar associations, and open clusters are fundamental stellar systems where predictions from star-formation theories can be robustly contrasted with observations. Aims: We aim to provide the astrophysical…

Astrophysics of Galaxies · Physics 2024-11-26 J. Olivares , H. Bouy , Trevor Z. Dorn-Wallenstein , A. Berihuete

NGC 346 is a young cluster with numerous hot OB stars. It is part of the Small Magellanic Cloud (SMC), and has an average metallicity that is one-seventh of the Milky Way's. A detailed study of its stellar content provides a unique…

Constraints on cosmological parameters are often distilled from sky surveys by fitting templates to summary statistics of the data that are motivated by a fiducial cosmological model. However, recent work has shown how to estimate the…

Cosmology and Nongalactic Astrophysics · Physics 2022-11-16 Aseem Paranjape , Ravi K. Sheth

We present a Bayesian method for the identification and classification of objects from sets of astronomical catalogs, given a predefined classification scheme. Identification refers here to the association of entries in different catalogs…

Instrumentation and Methods for Astrophysics · Physics 2015-06-15 Jörg P. Rachen

In analysis of X-ray diffraction data, identifying the crystalline phase is important for interpreting the material. The typical method is identifying the crystalline phase from the coincidence of the main diffraction peaks. This method…

Materials Science · Physics 2025-01-17 Ryo Murakami , Kenji Nagata , Yoshitaka Matsushita , Masahiko Demura

Asteroseismology has become an indispensable method for measuring stellar ages and radii, while binary systems remain the most prevalent tool for determining stellar masses. The synergy of the two, namely pulsating stars in binary systems,…

Solar and Stellar Astrophysics · Physics 2024-11-12 Simon J. Murphy

Space-based projects are providing a wealth of high-quality asteroseismic data, including frequencies for a large number of stars showing solar-like oscillations. These data open the prospect for precise determinations of key stellar…

Solar and Stellar Astrophysics · Physics 2015-05-20 P. -O. Quirion , J. Christensen-Dalsgaard , T. Arentoft

This Chapter, "A Guide to General-Purpose ABC Software", is to appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). We present general-purpose software to perform Approximate Bayesian Computation (ABC) as…

Computation · Statistics 2018-06-22 Athanasios Kousathanas , Pablo Duchen , Daniel Wegmann

The binary fractions of open and globular clusters yield powerful constraints on their dynamical state and evolutionary history. We apply publicly available Bayesian analysis code to a $UBVRIJHK_{S}$ photometric catalog of the old open…

Solar and Stellar Astrophysics · Physics 2020-01-08 Roger E. Cohen , Aaron M. Geller , Ted von Hippel

Blue supergiants (BSGs) are important objects to study the intermediate phases of massive star evolution, helping to constrain evolutionary models. However, the lack of a holistic study of a statistically significant and unbiased sample of…

Solar and Stellar Astrophysics · Physics 2023-06-28 Abel de Burgos , Sergio Simón-Díaz , Miguel A. Urbaneja , Ignacio Negueruela

The application of Bayesian methods in cosmology and astrophysics has flourished over the past decade, spurred by data sets of increasing size and complexity. In many respects, Bayesian methods have proven to be vastly superior to more…

Astrophysics · Physics 2009-06-23 Roberto Trotta

Bayesian model selection provides a powerful framework for objectively comparing models directly from observed data, without reference to ground truth data. However, Bayesian model selection requires the computation of the marginal…

Methodology · Statistics 2024-01-17 Xiaohao Cai , Jason D. McEwen , Marcelo Pereyra
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