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      • KCI등재후보

        GALAXY SED FITTING

        Burgarella Denis,Boquien Mederic,Buat Veronique,Ciesla Laure,Rhoelly Yannick 한국천문학회 2017 天文學論叢 Vol.32 No.1

        Modelling and fitting the spectral energy distribution (SED) of galaxies or regions of galaxies is one of the most useful methods available to the astronomer nowadays. By modelling the SEDs and comparing the models to the observations, we can collect important information on the physical processes at play in the formation and evolution of galaxies. The models allow to follow the evolution of the galaxies from their formation on. The versatility of code is crucial because of the diversity of galaxies. The analysis is only relevant and useful if the models can correctly reproduce this diversity now and across (as best as possible) all redshifts. On the other hand, the code needs to run fast to compare several million or tens of millions of models and to select the best (on a probabilistic basis) one that best resembles the observations. With this important point in mind, it seems logical that we should efficiently make use of the computer power available to the average astronomer. For instance, it seems difficult, today, to model and fit SEDs without a parallelized code. We present the new Python version of CIGALE SED fitting code and its characteristics. CIGALE comes in two main flavours: {\it CIGALE Classic} to fit SEDs and {\it CIGALE Model} to create spectra and SEDs of galaxies at all redshifts. The latest can potentially be used in conjunction with galaxy evolution models of galaxy formation and evolution such as semi-analytic ones.

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        PROPERTIES OF DUST OBSCURED GALAXIES IN THE NEP-DEEP FIELD

        Nagisa Oi,Hideo Matsuhara,CHRIS PEARSON,Veronique Buat,Denis Burgarella,Matt Malkan,Takamitsu Miyaji 한국천문학회 2017 天文學論叢 Vol.32 No.1

        We selected 47 DOGs at z ~ 1.5 using optical $R$ (or $r^{'}$), AKARI 18 $\mu$m, and 24 $\mu$m color in the AKARI North Ecliptic Pole (NEP) Deep survey field. Using the colors among 3, 4, 7, and $9\mu$m, we classified them into 3 groups; bump DOGs (23 sources), power-law DOGs (16 sources), and unknown DOGs (8 sources). We built spectral energy distributions (SEDs) with optical to far-infrared photometric data and investigated their properties using SED fitting method. We found that AGN activity such as a AGN contribution to the infrared luminosity and a Chandra detection rate for bump and power-law DOGs are significantly different, while stellar component properties like a stellar mass and a star-formation rate are similar to each other. A specific star-formation rate range of power-law DOGs is slightly higher than that of bump DOGs with wide overlap. Herschel/PACS detection rates are almost the same between bump and power-law DOGs. On the other hand SPIRE detection rates show large differences between bump and power-law DOGs. These results might be explained by differences in dust temperatures. Both groups of DOGs host hot and/or warm dust (~ 50 Kelvin), and many bump DOGs contain cooler dust ($\hspace{0.3em}\raisebox{0.4ex}{$<$}\hspace{-0.75em}\raisebox{-.7ex}{$\sim$}\hspace{0.3em}$ 30 Kelvin).

      • KCI등재후보

        HERSCHEL OBSERVATIONS IN THE AKARI NEP FIELD: INITIAL SOURCE COUNTS

        Chris Pearson,Ryan Cheale,STEPHEN SERJEANT,Hideo Matsuhara,Glenn J. White,Denis Burgarella,Ivan Valtchanov,Bruno Altieri,David L. Clements,Ros Hopwood 한국천문학회 2017 天文學論叢 Vol.32 No.1

        The preliminary data reduction, analysis and first results from the Herschel survey of the AKARI NEP field are presented. Herschel SPIRE observations of the NEP-Wide region and PACS observations of the NEP-Deep region have yielded galaxy catalogues of 4000 and 900 sources respectively down to flux density levels of approximately 15 mJy at 100-250 microns. Source counts produced from these catalogues reach cosmologically significant depths tracing the evolutionary upturn and turnover in the source counts. The source counts are in agreement with other large area surveys carried out with Herschel bridging the gap between the shallow and deep Herschel surveys.

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