Modelling the dusty universe - I. Introducing the artificial neural network and first applications to luminosity and colour distributions
文献类型：期刊论文
| 作者 | Almeida, C.1,2; Baugh, C. M.1; Lacey, C. G.1; Frenk, C. S.1; Granato, G. L.3; Silva, L.4; Bressan, A.3,4,5 |
| 刊名 | MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
 |
| 出版日期 | 2010-02-11 |
| 卷号 | 402期号:1页码:544-564 |
| 关键词 | methods: numerical galaxies: evolution large-scale structure of Universe submillimetre |
| 英文摘要 | We introduce a new technique based on artificial neural networks which enable us to make accurate predictions for the spectral energy distributions (SEDs) of large samples of galaxies, at wavelengths ranging from the far-ultraviolet (UV) to the submillimetre (sub-mm) and radio. The neural net is trained to reproduce the SEDs predicted by a hybrid code comprised of the galform semi-analytical model of galaxy formation, which predicts the full star formation and galaxy merger histories, and the grasil spectro-photometric code, which carries out a self-consistent calculation of the SED, including absorption and emission of radiation by dust. Using a small number of galaxy properties predicted by galform, the method reproduces the luminosities of galaxies in the majority of cases to within 10 per cent of those computed directly using grasil. The method performs best in the sub-mm and reasonably well in the mid-infrared (IR) and far-UV. The luminosity error introduced by the method has negligible impact on predicted statistical distributions, such as luminosity functions or colour distributions of galaxies. We use the neural net to predict the overlap between galaxies selected in the rest-frame UV and in the observer-frame sub-mm at z = 2. We find that around half of the galaxies with a 850 mu m flux above 5 mJy should have optical magnitudes brighter than R(AB) < 25 mag. However, only 1 per cent of the galaxies selected in the rest-frame UV down to R(AB) < 25 mag should have 850 mu m fluxes brighter than 5 mJy. Our technique will allow the generation of wide-angle mock catalogues of galaxies selected at rest-frame UV or mid- and far-IR wavelengths. |
| WOS标题词 | Science & Technology ; Physical Sciences |
| 类目[WOS] | Astronomy & Astrophysics |
| 研究领域[WOS] | Astronomy & Astrophysics |
| 关键词[WOS] | HIERARCHICAL GALAXY FORMATION ; STAR-FORMING GALAXIES ; LYMAN-BREAK GALAXIES ; HIGH-REDSHIFT ; SUBMILLIMETER GALAXIES ; EVOLUTION ; ULTRAVIOLET ; POPULATION ; RESOLUTION ; EMISSION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000274453500047 |
| 源URL | [http://119.78.226.72/handle/331011/26299]  |
| 专题 | 上海天文台_星系宇宙学重点实验室 |
| 作者单位 | 1.Univ Durham, Inst Computat Cosmol, Dept Phys, Durham DH1 3LE, England 2.Chinese Acad Sci, Key Lab Res Galaxies & Cosmol, Shanghai Astron Observ, Shanghai 200030, Peoples R China 3.Osserv Astron Padova, INAF, I-35122 Padua, Italy 4.Osserv Astron Trieste, INAF, I-34131 Trieste, Italy 5.INOE, Puebla, Mexico |
| 推荐引用方式 GB/T 7714 | Almeida, C.,Baugh, C. M.,Lacey, C. G.,et al. Modelling the dusty universe - I. Introducing the artificial neural network and first applications to luminosity and colour distributions[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2010,402(1):544-564. |
| APA | Almeida, C..,Baugh, C. M..,Lacey, C. G..,Frenk, C. S..,Granato, G. L..,...&Bressan, A..(2010).Modelling the dusty universe - I. Introducing the artificial neural network and first applications to luminosity and colour distributions.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,402(1),544-564. |
| MLA | Almeida, C.,et al."Modelling the dusty universe - I. Introducing the artificial neural network and first applications to luminosity and colour distributions".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 402.1(2010):544-564. |
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来源：上海天文台
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