scholarly journals Bayesian discrimination of the panchromatic spectral energy distribution modelings of galaxies

2019 ◽  
Vol 15 (S341) ◽  
pp. 143-146
Author(s):  
Yunkun Han ◽  
Zhanwen Han ◽  
Lulu Fan
Keyword(s):  
Bayesian Model ◽  
Model Comparison ◽  
Spectral Energy Distribution ◽  
Estimation Method ◽  
Comparison Method ◽  
Spectral Energy ◽  
Energy Distributions ◽  
Bayesian Model Comparison ◽  
Multi Wavelength ◽  
Almost All

AbstractFitting the multi-wavelength spectral energy distributions (SEDs) of galaxies is a widely used technique to extract information about the physical properties of galaxies. However, a major difficulty lies in the numerous uncertainties regarding almost all ingredients of the SED modeling of galaxies. The Bayesian methods provide a consistent conceptual basis for dealing with the problem of inference with many uncertainties. While the Bayesian parameter estimation method have become quite popular in the field of SED fitting of galaxies, the Bayesian model comparison method, which is based on the same Bayes’ rule, is still not widely used in this field. With the application of Bayesian model comparison method in a series of papers, we show that the results obtained with Bayesian model comparison are understandable in the context of stellar/galaxy physics. These results indicate that Bayesian model comparison is a reliable and very powerful method for the SED fitting of galaxies.

scholarly journals Bayesian analysis of galaxy spectral energy distributions with BayeSED

2012 ◽  
Vol 8 (S295) ◽  
pp. 312-312
Author(s):  
Yunkun Han ◽  
Zhanwen Han
Keyword(s):  
Parameter Estimation ◽  
Complex Systems ◽  
Bayesian Analysis ◽  
Bayesian Model ◽  
Model Comparison ◽  
Spectral Energy ◽  
Infrared Galaxies ◽  
Energy Distributions ◽  
Bayesian Model Comparison ◽  
Rigorous Test

AbstractIn Han & Han (2012), we have preliminarily built BayeSED and applied it to a sample of hyperluminous infrared galaxies. The physically reasonable results obtained from Bayesian model comparison and parameter estimation show that BayeSED could be a useful tool for understanding the nature of complex systems, such as dust obscured starburst-AGN composite galaxies, from decoding their complex SEDs. In this contribution, we present a more rigorous test of BayeSED by making a mock catalog from model SEDs with the value of all parameters to be known in advance.

scholarly journals Spectral energy distribution similarity of the local galaxies and the 3.6 μm selected galaxies from the Spitzer Extended Deep Survey

2021 ◽  
Vol 21 (10) ◽  
pp. 260
Author(s):  
Cheng Cheng ◽  
Jia-Sheng Huang ◽  
Hai Xu ◽  
Gao-Xiang Jin ◽  
Chuan He ◽  
...  
Keyword(s):  
High Redshift ◽  
Spectral Energy Distribution ◽  
Mass Function ◽  
Spectral Energy ◽  
Energy Distributions ◽  
Mid Infrared ◽  
Redshift Galaxy ◽  
The Galaxy ◽  
Deep Survey ◽  
Multi Wavelength

Abstract The Spitzer Extended Deep Survey (SEDS) as a deep and wide mid-infrared (MIR) survey project provides a sample of 500 000+ sources spreading 1.46 square degree and a depth of 26 AB mag (3σ). Combining with the previous available data, we build a PSF-matched multi-wavelength photometry catalog from u band to 8 μm. We fit the SEDS galaxies spectral energy distributions by the local galaxy templates. The results show that the SEDS galaxy can be fitted well, indicating the high redshift galaxy (z ∼ 1) shares the same templates with the local galaxies. This study would facilitate the further study of the galaxy luminosity and high redshift mass function.

scholarly journals Spectral Energy Distributions of a set of H ii regions in M33 (HerM33es)

2011 ◽  
Vol 7 (S284) ◽  
pp. 122-124
Author(s):  
Monica Relaño ◽  
Simon Verley ◽  
Isabel Pérez ◽  
Carsten Kramer ◽  
Manolis Xilouris ◽  
...  
Keyword(s):  
Spectral Energy Distribution ◽  
Morphological Type ◽  
Spectral Energy ◽  
H Ii Regions ◽  
Energy Distributions ◽  
Stellar Cluster ◽  
Multi Wavelength ◽  
Hα Emission ◽  
Group Galaxy

AbstractWithin the framework of the HerM33es Key Project for Herschel and in combination with multi-wavelength data, we study the Spectral Energy Distribution (SED) of a set of H ii regions in the Local Group Galaxy M33. Using the Hα emission, we perform a classification of a selected H ii region sample in terms of morphology, separating the objects in filled, mixed, shell and clear shell objects. We obtain the SED for each H ii region as well as a representative SED for each class of objects. We also study the emission distribution of each band within the regions. We find different trends in the SEDs for each morphological type that are related to properties of the dust and their associated stellar cluster. The emission distribution of each band within the region is different for each morphological type of object.

Science with the VO: Spectroscopic Studies of Herbig Ae/Be Stars

2012 ◽  
Vol 21 (3) ◽  
Author(s):  
D. Baines ◽  
J. Gonzalez ◽  
C. Arviset ◽  
I. Barbarisi ◽  
A. Laruelo ◽  
...  
Keyword(s):  
Spectral Energy Distribution ◽  
Spectroscopic Studies ◽  
Spectral Energy ◽  
Analysis Tool ◽  
Be Stars ◽  
Energy Distributions ◽  
New Developments ◽  
Multi Wavelength ◽  
Opening Up ◽  
Comprehensive Study

AbstractThe Virtual Observatory (VO) is opening up new ways of exploiting the huge amount of data provided by the ever growing number of ground-based and space facilities. Using VOSpec, a multi-wavelength spectral analysis tool developed by the ESA-VO Team at ESAC, and new developments on scripting with VOSpec (VOScript), we have started to undertake a comprehensive study of spectroscopic and photometric data in the VO on Herbig Ae/Be stars. By studying line strengths, variabilities and spectral energy distributions, from the X-ray to sub-millimeter ranges, we aim to gain insights into processes and disk properties of a large sample of these objects. This paper presents initial findings of the spectroscopic analysis and initial spectral energy distribution classifications.

scholarly journals Detecting episodes of star formation using Bayesian model selection

2021 ◽  
Vol 502 (3) ◽  
pp. 3993-4008
Author(s):  
Andrew J Lawler ◽  
Viviana Acquaviva
Keyword(s):  
Star Formation ◽  
Bayesian Model ◽  
Model Comparison ◽  
Density Ratio ◽  
Model Complexity ◽  
Spectral Energy ◽  
Analytic Approximation ◽  
Nested Models ◽  
Bayesian Model Comparison ◽  
Correct Model

ABSTRACT Bayesian model comparison frameworks can be used when fitting models to data in order to infer the appropriate model complexity in a data-driven manner. We aim to use them to detect the correct number of major episodes of star formation from the analysis of the spectral energy distributions (SEDs) of galaxies, modelled after 3D-HST galaxies at z ∼ 1. Starting from the published stellar population properties of these galaxies, we use kernel density estimates to build multivariate input parameter distributions to obtain realistic simulations. We create simulated sets of spectra of varying degrees of complexity (identified by the number of parameters), and derive SED fitting results and pieces of evidence for pairs of nested models, including the correct model as well as more simplistic ones, using the bagpipes codebase with nested sampling algorithm multinest. We then ask the question: is it true – as expected in Bayesian model comparison frameworks – that the correct model has larger evidence? Our results indicate that the ratio of pieces of evidence (the Bayes factor) is able to identify the correct underlying model in the vast majority of cases. The quality of the results improves primarily as a function of the total S/N in the SED. We also compare the Bayes factors obtained using the evidence to those obtained via the Savage–Dickey density ratio (SDDR), an analytic approximation that can be calculated using samples from regular Markov Chain Monte Carlo methods. We show that the SDDR ratio can satisfactorily replace a full evidence calculation provided that the sampling density is sufficient.

Bayesian model comparison

2014 ◽  
pp. 101-117
Author(s):  
Michael D. Lee ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Bayesian Model ◽  
Model Comparison ◽  
Bayesian Model Comparison

scholarly journals A Bayesian model comparison approach to test the specificity of visual integration impairment in schizophrenia or psychosis

2018 ◽  
Vol 265 ◽  
pp. 271-278 ◽  
Author(s):  
Tyler B. Grove ◽  
Beier Yao ◽  
Savanna A. Mueller ◽  
Merranda McLaughlin ◽  
Vicki L. Ellingrod ◽  
...  
Keyword(s):  
Bayesian Model ◽  
Model Comparison ◽  
Visual Integration ◽  
Bayesian Model Comparison ◽  
Comparison Approach

Uncertainty of prior and posterior model probability: Implications for interpreting Bayes factors

2021 ◽  
Author(s):  
John K. Kruschke
Keyword(s):  
Posterior Distribution ◽  
Bayesian Model ◽  
Model Comparison ◽  
Bayes Factor ◽  
Bayes Factors ◽  
Prior Model ◽  
Bayesian Hypothesis Testing ◽  
Bayesian Model Comparison ◽  
Posterior Model Probability ◽  
Model Probability

In most applications of Bayesian model comparison or Bayesian hypothesis testing, the results are reported in terms of the Bayes factor only, not in terms of the posterior probabilities of the models. Posterior model probabilities are not reported because researchers are reluctant to declare prior model probabilities, which in turn stems from uncertainty in the prior. Fortunately, Bayesian formalisms are designed to embrace prior uncertainty, not ignore it. This article provides a novel derivation of the posterior distribution of model probability, and shows many examples. The posterior distribution is useful for making decisions taking into account the uncertainty of the posterior model probability. Benchmark Bayes factors are provided for a spectrum of priors on model probability. R code is posted at https://osf.io/36527/. This framework and tools will improve interpretation and usefulness of Bayes factors in all their applications.

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