尘埃遮蔽的Starburst-AGN复合星系的能谱研究
|
摘要
由于激烈的恒星形成活动和超大质量黑洞的吸积活动耦合在一起同时进行,尘埃遮蔽的Starburst-AGN复合星系代表了星系的形成和演化过程中的一个重要阶段,并且是认识Starburst-AGN联系的理想实验室。能谱分布(SEDs)蕴含了关于这类有趣的天体中恒星形成、星族和AGN活动等方面的丰富信息。然而,通过能谱的分析来有效地提取这些物理信息在目前仍然是一个非常困难的问题。
本文首先从星系能谱分布的基本概念、多波段能谱的观测、星系能谱分布的理论模型、星系能谱分布的分析(或拟合)方法等方面对此研究领域做了系统性的介绍。之后,本文重点介绍了我们在这个领域内所做的一些工作。
AGN的光度函数是帮助人们认识AGN活动及其演化的一个重要的可观测量。在实践中,AGN光度函数的测量需要相互独立且各自都存在一定局限性的不同波段的观测。为了准确地测量AGN的光度函数,我们需要结合多波段的观测以得出一个自洽的结果。有鉴于此,基于一个改进的AGN能谱模型,我们给出了AGN的硬X-ray光度函数和IR光度函数的一个详细的比较。我们发现,从硬X-ray光度函数出发而利用AGN能谱得出的相应IR光度函数倾向于低估高IR光度的AGN的数量。这种低估的情况独立于AGN的硬X-ray光度函数的选择,并且对最新的硬X-ray光度函数还更加明显。我们表明,在观测上独立获得的AGN的硬X-ray光度函数和IR光度函数之间的这种不一致可以通过在AGN的能谱模型中适当考虑进UV到X-ray的斜率αox与UV光度LUV之间的反相关而在很大程度上得到解决。另外,我们也讨论了以上的这种不一致的其它可能解释,例如在现有的X-ray观测中遗漏的大量康普顿厚的AGN、寄主星系中恒星形成过程对mid-IR的贡献等。与此同时,我们发现,如果假设Quasars(?)(?)Seyferts这两类不同的AGN周围的遮蔽介质按不同的方式分布和演化,那么AGN的硬X-ray光度函数和IR光度函数之间将更加一致。这个结果与人们普遍接受的认为这两类AGN的机制存在根本的不同的观点相一致。
尘埃遮蔽的Starburst-AGN复合星系比AGN更加复杂,而其多波段能谱也更加复杂、更加难以分析。为了能更好地认识这些复杂的星系,我们组建了BayeSED一套能利用各种能谱模型或者它们的线性叠加来对星系的能谱进行详细的贝叶斯分析的程序。其中,人工神经网络、主成分分析、和多峰嵌套采样等方法的采用使得能谱的贝叶斯分析更加高效。作为一个示范,我们将此程序应用于对一个超高光度红外星系样本进行详细的贝叶斯能谱分析,包括贝叶斯模型比较和参数估计。通过利用贝叶斯证据值来对纯Starburst.纯AGN以及两者的线性叠力(?)Starburst+AGN三种模型进行比较,我们发现,对此样本中的星系而言,Starburst+AGN模型总是具有最高的可能性。根据计算得出的不同模型的贝叶斯证据值以及估计的Starburst成分和AGN成分的红外光度,我们发现此超高光度红外星系样本中的星系因其主导能源的不同而分为A类和B类。另外,通过对这两类星系的其它Starburst参数和AGN参数作的一些简单的统计相关性分析,我们发现,A类星系中AGN周围的尘埃环中尘埃含量要比相应B类中的尘埃含量更高一些,而B类星系中Starburst区的OB型星比例更高并且分布在更大的尺度上。这些结果是与人们当前的星系通过并和而形成和演化的整体图景相一致的。总而言之,初步的应用表明,我们的BayeSED程序给出的结果是合理的。因此,它可以成为一个可靠而又高效的工具,能通过对能谱的详细分析来帮助人们认识像尘埃遮蔽的Starburst-AGN复合星系这样复杂的系统。
Since violent formation of stars (i.e. Starburst) and growth of SMBHs (i.e.active galactic nucleus, AGN) are coupled and ongoing together, dust-obscuredStarburst-AGN composite galaxies represent important phases in the formationand evolution of galaxies, and are ideal laboratories for studying starburst-AGNconnections. The spectral energy distributions (SEDs) are encoded with infor-mation about star formations, stellar populations, interstellar mediums (ISM)and AGN in these interesting objects. However, it is currently still very chal-lenging to efciently extract the basic physical properties of these galaxies fromthe analysis of their SEDs.
In this thesis, we frstly described the feld of the analysis of SEDs (or ft-ting), including the basic concept of SED, the construction of observed multi-wavelength SED of galaxies, and the methods for the analysis of SEDs. Then,we present our work on this feld in detail.
The luminosity function (LF) of AGN is an important observable quantityfor our understanding of AGN activities and their evolution. In practice, the LFsof AGN are measured independently from diferent wavelength bands, all of whichare sufered by diferent limitations. To obtain an accurate determination of theLF of AGN, multi-wavelength observations need to be combined self-consistently.Given these, we present a detailed comparison between the210keV hard X-ray and infrared (IR) LF of AGN, by employing a simple but well tested modelfor the SEDs of AGN. We fnd that the IRLFs predicted from HXLFs tend tounderestimate the number of the most IR-luminous AGN. This is independent ofthe choices of HXLF, and even more obvious for the HXLFs recently measured.We show that the discrepancy between the independently obtained HXLFs andIRLFs of AGN can be largely resolved when the anticorrelation between the UVto X-ray slope αoxand UV luminosity LUVis appropriately considered in themodel for the SEDs of AGN. We also discuss other possible explanations for thediscrepancy, such as the missing population of Compton-thick AGN and possible contribution of star-formation in the host to the mid-IR. Meanwhile, we fndthat the HXLFs and IRLFs of AGN can be more consistent with each other ifthe obscuration mechanisms of Quasars and Seyferts are assumed to be diferent.This is consistent with the widely accepted idea that the mechanisms of the twotypes of AGN are fundamentally diferent.
The dust-obscured Starburst-AGN composite galaxies are more complicatedthan AGN, and the analysis of their multi-wavelength SEDs is more challenging.Given these, we have built BayeSED, a general purpose tool for doing Bayesiananalysis of SEDs by using whatever pre-existing model SED libraries or theirlinear combinations. The artifcial neural networks (ANNs), principal compo-nent analysis (PCA) and multimodal nested sampling (MultiNest) techniquesare employed to allow a highly efcient sampling of posterior distribution andthe calculation of Bayesian evidence. As a demonstration, we apply this toolto a sample of hyperluminous infrared galaxies (HLIRGs). The Bayesian evi-dences obtained for a pure Starburst, a pure AGN, and a linear combination ofStarburst+AGN models show that the Starburst+AGN model have the highestevidence for all galaxies in this sample. The Bayesian evidences for the threemodels and the estimated contributions of starburst and AGN to infrared lumi-nosity show that HLIRGs can be classifed into two groups: one dominated bystarburst and the other dominated by AGN. Other parameters and correspondinguncertainties about starburst and AGN are also estimated by using the modelwith the highest Bayesian evidence. We found that the starburst region of theHLIRGs dominated by starburst tends to be more compact and has a higherfraction of OB star than that of HLIRGs dominated by AGN. Meanwhile, theAGN torus of the HLIRGs dominated by AGN tend to be more dusty than thatof HLIRGs dominated by starburst. Overall, we believe that BayeSED could bea reliable and efcient tool for exploring the nature of complex systems such asdust-obscured Starburst-AGN composite systems from decoding their SEDs.
本文首先从星系能谱分布的基本概念、多波段能谱的观测、星系能谱分布的理论模型、星系能谱分布的分析(或拟合)方法等方面对此研究领域做了系统性的介绍。之后,本文重点介绍了我们在这个领域内所做的一些工作。
AGN的光度函数是帮助人们认识AGN活动及其演化的一个重要的可观测量。在实践中,AGN光度函数的测量需要相互独立且各自都存在一定局限性的不同波段的观测。为了准确地测量AGN的光度函数,我们需要结合多波段的观测以得出一个自洽的结果。有鉴于此,基于一个改进的AGN能谱模型,我们给出了AGN的硬X-ray光度函数和IR光度函数的一个详细的比较。我们发现,从硬X-ray光度函数出发而利用AGN能谱得出的相应IR光度函数倾向于低估高IR光度的AGN的数量。这种低估的情况独立于AGN的硬X-ray光度函数的选择,并且对最新的硬X-ray光度函数还更加明显。我们表明,在观测上独立获得的AGN的硬X-ray光度函数和IR光度函数之间的这种不一致可以通过在AGN的能谱模型中适当考虑进UV到X-ray的斜率αox与UV光度LUV之间的反相关而在很大程度上得到解决。另外,我们也讨论了以上的这种不一致的其它可能解释,例如在现有的X-ray观测中遗漏的大量康普顿厚的AGN、寄主星系中恒星形成过程对mid-IR的贡献等。与此同时,我们发现,如果假设Quasars(?)(?)Seyferts这两类不同的AGN周围的遮蔽介质按不同的方式分布和演化,那么AGN的硬X-ray光度函数和IR光度函数之间将更加一致。这个结果与人们普遍接受的认为这两类AGN的机制存在根本的不同的观点相一致。
尘埃遮蔽的Starburst-AGN复合星系比AGN更加复杂,而其多波段能谱也更加复杂、更加难以分析。为了能更好地认识这些复杂的星系,我们组建了BayeSED一套能利用各种能谱模型或者它们的线性叠加来对星系的能谱进行详细的贝叶斯分析的程序。其中,人工神经网络、主成分分析、和多峰嵌套采样等方法的采用使得能谱的贝叶斯分析更加高效。作为一个示范,我们将此程序应用于对一个超高光度红外星系样本进行详细的贝叶斯能谱分析,包括贝叶斯模型比较和参数估计。通过利用贝叶斯证据值来对纯Starburst.纯AGN以及两者的线性叠力(?)Starburst+AGN三种模型进行比较,我们发现,对此样本中的星系而言,Starburst+AGN模型总是具有最高的可能性。根据计算得出的不同模型的贝叶斯证据值以及估计的Starburst成分和AGN成分的红外光度,我们发现此超高光度红外星系样本中的星系因其主导能源的不同而分为A类和B类。另外,通过对这两类星系的其它Starburst参数和AGN参数作的一些简单的统计相关性分析,我们发现,A类星系中AGN周围的尘埃环中尘埃含量要比相应B类中的尘埃含量更高一些,而B类星系中Starburst区的OB型星比例更高并且分布在更大的尺度上。这些结果是与人们当前的星系通过并和而形成和演化的整体图景相一致的。总而言之,初步的应用表明,我们的BayeSED程序给出的结果是合理的。因此,它可以成为一个可靠而又高效的工具,能通过对能谱的详细分析来帮助人们认识像尘埃遮蔽的Starburst-AGN复合星系这样复杂的系统。
Since violent formation of stars (i.e. Starburst) and growth of SMBHs (i.e.active galactic nucleus, AGN) are coupled and ongoing together, dust-obscuredStarburst-AGN composite galaxies represent important phases in the formationand evolution of galaxies, and are ideal laboratories for studying starburst-AGNconnections. The spectral energy distributions (SEDs) are encoded with infor-mation about star formations, stellar populations, interstellar mediums (ISM)and AGN in these interesting objects. However, it is currently still very chal-lenging to efciently extract the basic physical properties of these galaxies fromthe analysis of their SEDs.
In this thesis, we frstly described the feld of the analysis of SEDs (or ft-ting), including the basic concept of SED, the construction of observed multi-wavelength SED of galaxies, and the methods for the analysis of SEDs. Then,we present our work on this feld in detail.
The luminosity function (LF) of AGN is an important observable quantityfor our understanding of AGN activities and their evolution. In practice, the LFsof AGN are measured independently from diferent wavelength bands, all of whichare sufered by diferent limitations. To obtain an accurate determination of theLF of AGN, multi-wavelength observations need to be combined self-consistently.Given these, we present a detailed comparison between the210keV hard X-ray and infrared (IR) LF of AGN, by employing a simple but well tested modelfor the SEDs of AGN. We fnd that the IRLFs predicted from HXLFs tend tounderestimate the number of the most IR-luminous AGN. This is independent ofthe choices of HXLF, and even more obvious for the HXLFs recently measured.We show that the discrepancy between the independently obtained HXLFs andIRLFs of AGN can be largely resolved when the anticorrelation between the UVto X-ray slope αoxand UV luminosity LUVis appropriately considered in themodel for the SEDs of AGN. We also discuss other possible explanations for thediscrepancy, such as the missing population of Compton-thick AGN and possible contribution of star-formation in the host to the mid-IR. Meanwhile, we fndthat the HXLFs and IRLFs of AGN can be more consistent with each other ifthe obscuration mechanisms of Quasars and Seyferts are assumed to be diferent.This is consistent with the widely accepted idea that the mechanisms of the twotypes of AGN are fundamentally diferent.
The dust-obscured Starburst-AGN composite galaxies are more complicatedthan AGN, and the analysis of their multi-wavelength SEDs is more challenging.Given these, we have built BayeSED, a general purpose tool for doing Bayesiananalysis of SEDs by using whatever pre-existing model SED libraries or theirlinear combinations. The artifcial neural networks (ANNs), principal compo-nent analysis (PCA) and multimodal nested sampling (MultiNest) techniquesare employed to allow a highly efcient sampling of posterior distribution andthe calculation of Bayesian evidence. As a demonstration, we apply this toolto a sample of hyperluminous infrared galaxies (HLIRGs). The Bayesian evi-dences obtained for a pure Starburst, a pure AGN, and a linear combination ofStarburst+AGN models show that the Starburst+AGN model have the highestevidence for all galaxies in this sample. The Bayesian evidences for the threemodels and the estimated contributions of starburst and AGN to infrared lumi-nosity show that HLIRGs can be classifed into two groups: one dominated bystarburst and the other dominated by AGN. Other parameters and correspondinguncertainties about starburst and AGN are also estimated by using the modelwith the highest Bayesian evidence. We found that the starburst region of theHLIRGs dominated by starburst tends to be more compact and has a higherfraction of OB star than that of HLIRGs dominated by AGN. Meanwhile, theAGN torus of the HLIRGs dominated by AGN tend to be more dusty than thatof HLIRGs dominated by starburst. Overall, we believe that BayeSED could bea reliable and efcient tool for exploring the nature of complex systems such asdust-obscured Starburst-AGN composite systems from decoding their SEDs.
引文
[1]Mo H., van den Bosch F., White S. Galaxy Formation and Evolution. The Edinburgh Building, Cambridge CB28RU, UK:Cambridge University Press,2010.
[2]Smoot G. F., Bennett C. L., Kogut A., Wright E. L., Aymon J., Boggess N. W., Cheng E. S., de Amici G., et al. Structure in the COBE differential microwave radiometer first-year maps. ApJL,1992,396:L1-L5.
[3]李宗伟,肖兴华.天体物理学.第1版.北京市西城区德外大街4号：高等教育出版社,2000.
[4]黄润乾.恒星物理.第1版.北京市海淀区中关村南大街16号：中国科学技术出版社,2006.
[5]Davis M., Guhathakurta P., Konidaris N. P., Newman J. A., Ashby M. L. N., Biggs A. D., Barmby P., Bundy K., et al. The All-Wavelength Extended Groth Strip International Survey (AEGIS) Data Sets. ApJL,2007,660: L1-L6.
[6]Wolf C., Meisenheimer K., Rix H.-W., Borch A., Dye S., Kleinheinrich M. The COMBO-17survey:Evolution of the galaxy luminosity function from25000galaxies with0.2 [7]Scoville N., Aussel H., Brusa M., Capak P., Carollo C. M., Elvis M., Gi-avalisco M., Guzzo L., et al. The Cosmic Evolution Survey (COSMOS): Overview. ApJS,2007,172:1-8.
[8]Driver S. P., Norberg P., Baldry I. K., Bamford S. P., Hopkins A. M., Liske J., Loveday J., Peacock J. A., et al. GAMA:towards a physical under-standing of galaxy formation. Astronomy and Geophysics,2009,50(5):050000-5.
[9] Johnson B. D., Schiminovich D., Seibert M., Treyer M., Martin D. C., Bar-low T. A., Forster K., Friedman P. G., et al. Ultraviolet, Optical, and In-frared Constraints on Models of Stellar Populations and Dust Attenuation.ApJS,2007,173:377–391.
[10] Gavazzi G., Boselli A., Donati A., Franzetti P., Scodeggio M. IntroducingGOLDMine: A new galaxy database on the WEB. A&A,2003,400:451–455.
[11] Giavalisco M., Ferguson H. C., Koekemoer A. M., Dickinson M., AlexanderD. M., Bauer F. E., Bergeron J., Biagetti C., et al. The Great Observato-ries Origins Deep Survey: Initial Results from Optical and Near-InfraredImaging. ApJL,2004,600:L93–L98.
[12] Berriman G. B., Good J. C., Lonsdale C. J. The Infrared Science Archive(IRSA)at IPAC: Moving Towards the NVO. In American AstronomicalSociety Meeting Abstracts, volume32of Bulletin of the American Astro-nomical Society, page116.10,2000.
[13] Dale D. A., Cohen S. A., Johnson L. C., Schuster M. D., Calzetti D., En-gelbracht C. W., Gil de Paz A., Kennicutt R. C., et al. The Spitzer LocalVolume Legacy: Survey Description and Infrared Photometry. ApJ,2009,703:517–556.
[14] Imhof C., Abney F., Christian D., Donahue M., Hanisch R., Kimball T.,Levay K., Padovani P., et al. Resources Available through the MultimissionArchive at Space Telescope (MAST). In American Astronomical SocietyMeeting Abstracts#194, volume31of Bulletin of the American Astronom-ical Society, page968,1999.
[15] Taylor E. N., Franx M., van Dokkum P. G., Quadri R. F., Gawiser E., BellE. F., Barrientos L. F., Blanc G. A., et al. A Public, K-Selected, Optical-to-Near-Infrared Catalog of the Extended Chandra Deep Field South(ECDFS) from the Multiwavelength Survey by Yale-Chile (MUSYC).ApJS,2009,183:295–319.
[16] Abazajian K. N., Adelman-McCarthy J. K., Agu¨eros M. A., Allam S. S.,Allende Prieto C., An D., Anderson K. S. J., Anderson S. F., et al. TheSeventh Data Release of the Sloan Digital Sky Survey. ApJS,2009,182:543–558.
[17] Kennicutt Jr. R. C., Armus L., Bendo G., Calzetti D., Dale D. A., DraineB. T., Engelbracht C. W., Gordon K. D., et al. SINGS: The SIRTF NearbyGalaxies Survey. PASP,2003,115:928–952.
[18] Treyer M., Schiminovich D., Johnson B. D., O’Dowd M., Martin C. D.,Wyder T., Charlot S., Heckman T., et al. Mid-infrared Spectral Indica-tors of Star Formation and Active Galactic Nucleus Activity in NormalGalaxies. ApJ,2010,719:1191–1211.
[19] Lonsdale C. J., Smith H. E., Rowan-Robinson M., Surace J., Shupe D., XuC., Oliver S., Padgett D., et al. SWIRE: The SIRTF Wide-Area InfraredExtragalactic Survey. PASP,2003,115:897–927.
[20] Le F`evre O., Vettolani G., Garilli B., Tresse L., Bottini D., Le Brun V.,Maccagni D., Picat J. P., et al. The VIMOS VLT deep survey. First epochVVDS-deep survey:11564spectra with17.5≤IAB≤24, and the redshiftdistribution over0≤z≤5. A&A,2005,439:845–862.
[21] Casali M., Adamson A., Alves de Oliveira C., Almaini O., Burch K., ChuterT., Elliot J., Folger M., et al. The UKIRT wide-feld camera. A&A,2007,467:777–784.
[22] Walcher J., Groves B., Budava′ri T., Dale D. Fitting the integrated spectralenergy distributions of galaxies. Ap&SS,2011,331:1–52.
[23] Johnson H. L., Morgan W. W. Fundamental stellar photometry for stan-dards of spectral type on the revised system of the Yerkes spectral atlas.ApJ,1953,117:313.
[24] Bessell M. S. UBVRI passbands. PASP,1990,102:1181–1199.
[25] Koleva M., Prugniel P., Ocvirk P., Le Borgne D., Soubiran C. Spectroscopicages and metallicities of stellar populations: validation of full spectrumftting. MNRAS,2008,385:1998–2010.
[26] Koornneef J., Bohlin R., Buser R., Horne K., Turnshek D. Synthetic pho-tometry and the calibration of the Hubble Space Telescope. Highlights ofAstronomy,1986,7:833–843.
[27] Landolt A. U. UBVRI photometric standard stars in the magnitude range11.5-16.0around the celestial equator. AJ,1992,104:340–371.
[28] van Dokkum P. G., Labb′e I., Marchesini D., Quadri R., Brammer G.,Whitaker K. E., Kriek M., Franx M., et al. The NEWFIRM Medium-BandSurvey: Filter Defnitions and First Results. PASP,2009,121:2–8.
[29] Kakazu Y., Cowie L. L., Hu E. M. Mapping Extremely Low MetallicityGalaxies to Redshift One. ApJ,2007,668:853–875.
[30] Guillaume M., Llebaria A., Aymeric D., Arnouts S., Milliard B. Deblendingof the UV photometry in GALEX deep surveys using optical priors in thevisible wavelengths. In E. R. Dougherty, J. T. Astola, K. O. Egiazarian,N. M. Nasrabadi,&S. A. Rizvi, editor, Society of Photo-Optical Instru-mentation Engineers (SPIE) Conference Series, volume6064of Society ofPhoto-Optical Instrumentation Engineers (SPIE) Conference Series, pages332–341,2006.
[31] Roseboom I. G., Oliver S., Parkinson D., Vaccari M. A new approach tomultiwavelength associations of astronomical sources. MNRAS,2009,400:1062–1074.
[32] Oemler Jr. A. The structure of elliptical and cD galaxies. ApJ,1976,209:693–709.
[33] Carter D. The optical extent of giant E and cD galaxies. MNRAS,1977,178:137–148.
[34] Baade W. The Resolution of Messier32, NGC205, and the Central Regionof the Andromeda Nebula. ApJ,1944,100:137.
[35] Spinrad H., Taylor B. J. The Stellar Content of the Nuclei of Nearby Galax-ies. I. M31, M32, and M81. ApJS,1971,22:445.
[36] Faber S. M. Quadratic programming applied to the problem of galaxypopulation synthesis. A&A,1972,20:361–374.
[37] O’Connell R. W. Galaxy spectral synthesis. I-Stellar populations in thenuclei of giant ellipticals. ApJ,1976,206:370–390.
[38] Turnrose B. E. The stellar content of the nuclear regions of SC galaxies.ApJ,1976,210:33–37.
[39] Tinsley B. M. Galactic Evolution. A&A,1972,20:383–+.
[40] Searle L., Sargent W. L. W., Bagnuolo W. G. The History of Star Formationand the Colors of Late-Type Galaxies. ApJ,1973,179:427–438.
[41] Larson R. B., Tinsley B. M. Star formation rates in normal and peculiargalaxies. ApJ,1978,219:46–59.
[42] Tinsley B. M. Evolutionary synthesis of the stellar population in ellipticalgalaxies. II-Late M giants and composition efects. ApJ,1978,222:14–22.
[43] Bruzual A. G. Spectral evolution of galaxies. I-Early-type systems. ApJ,1983,273:105–127.
[44] Arimoto N., Yoshii Y. Chemical and photometric properties of a galacticwind model for elliptical galaxies. A&A,1987,173:23–38.
[45] Guiderdoni B., Rocca-Volmerange B. A model of spectrophotometric evo-lution for high-redshift galaxies. A&A,1987,186:1–21.
[46] Buzzoni A. Evolutionary population synthesis in stellar systems. I-Aglobal approach. ApJS,1989,71:817–869.
[47] Bruzual A. G., Charlot S. Spectral evolution of stellar populations usingisochrone synthesis. ApJ,1993,405:538–553.
[48] Bressan A., Chiosi C., Fagotto F. Spectrophotometric evolution of ellipti-cal galaxies.1: Ultraviolet excess and color-magnitude-redshift relations.ApJS,1994,94:63–115.
[49] Worthey G. Comprehensive stellar population models and the disentangle-ment of age and metallicity efects. ApJS,1994,95:107–149.
[50] Leitherer C., Heckman T. M. Synthetic properties of starburst galaxies.ApJS,1995,96:9–38.
[51] Fioc M., Rocca-Volmerange B. PEGASE: a UV to NIR spectral evolutionmodel of galaxies. Application to the calibration of bright galaxy counts.A&A,1997,326:950–962.
[52] Maraston C. Evolutionary synthesis of stellar populations: a modular tool.MNRAS,1998,300:872–892.
[53] Leitherer C., Schaerer D., Goldader J. D., Gonza′lez Delgado R. M., RobertC., Kune D. F., de Mello D. F., Devost D., et al. Starburst99: SynthesisModels for Galaxies with Active Star Formation. ApJS,1999,123:3–40.
[54] Vazdekis A. Evolutionary Stellar Population Synthesis at2A SpectralResolution. ApJ,1999,513:224–241.
[55] Bruzual G., Charlot S. Stellar population synthesis at the resolution of2003. MNRAS,2003,344:1000–1028.
[56] Maraston C. Evolutionary population synthesis: models, analysis of theingredients and application to high-z galaxies. MNRAS,2005,362:799–825.
[57] Zhang F., Han Z., Li L., Hurley J. R. Inclusion of binaries in evolutionarypopulation synthesis. MNRAS,2005,357:1088–1103.
[58] Bruzual A. G. On TP-AGB stars and the mass of galaxies. Proceedings ofthe International Astronomical Union,2007,2(Symposium S241):125–132.
[59] Benson A. J. Galaxy formation theory. Physics Reports,2010,495:33–86.
[60] Salpeter E. E. The Luminosity Function and Stellar Evolution. ApJ,1955,121:161.
[61] Massey P. The Initial Mass Function of Massive Stars in the Local Group.In G. Gilmore&D. Howell, editor, The Stellar Initial Mass Function (38thHerstmonceux Conference), volume142of Astronomical Society of the Pa-cifc Conference Series, page17,1998.
[62] Kroupa P. On the variation of the initial mass function. MNRAS,2001,322:231–246.
[63] Chabrier G. The Galactic Disk Mass Budget. I. Stellar Mass Function andDensity. ApJ,2001,554:1274–1281.
[64] Corbelli E., Palla F., Zinnecker H., editors. The Initial Mass Function50years later, volume327of Astrophysics and Space Science Library,2005.
[65] Marigo P., Girardi L. Evolution of asymptotic giant branch stars. I. Up-dated synthetic TP-AGB models and their basic calibration. A&A,2007,469:239–263.
[66] Marigo P., Girardi L., Bressan A., Groenewegen M. A. T., Silva L., GranatoG. L. Evolution of asymptotic giant branch stars. II. Optical to far-infraredisochrones with improved TP-AGB models. A&A,2008,482:883–905.
[67] Lejeune T., Schaerer D. Database of Geneva stellar evolution tracks andisochrones for (UBV)J(RI)CJHKLL’M, HST-WFPC2, Geneva and Wash-ington photometric systems. A&A,2001,366:538–546.
[68] Demarque P., Woo J.-H., Kim Y.-C., Yi S. K. Y2Isochrones with an Im-proved Core Overshoot Treatment. ApJS,2004,155:667–674.
[69] Weiss A., Schlattl H. GARSTEC—the Garching Stellar Evolution Code.The direct descendant of the legendary Kippenhahn code. Ap&SS,2008,316:99–106.
[70] Pietrinferni A., Cassisi S., Salaris M., Percival S., Ferguson J. W. A LargeStellar Evolution Database for Population Synthesis Studies. V. StellarModels and Isochrones with CNONa Abundance Anticorrelations. ApJ,2009,697:275–282.
[71] Kurucz R. L. Model Atmospheres for Population Synthesis. In B. Barbuy&A. Renzini, editor, The Stellar Populations of Galaxies, volume149ofIAU Symposium, page225,1992.
[72] Westera P., Lejeune T., Buser R., Cuisinier F., Bruzual G. A standardstellar library for evolutionary synthesis. III. Metallicity calibration. A&A,2002,381:524–538.
[73] Smith L. J., Norris R. P. F., Crowther P. A. Realistic ionizing fuxes foryoung stellar populations from0.05to2Zsolar. MNRAS,2002,337:1309–1328.
[74] Coelho P., Barbuy B., Mel′endez J., Schiavon R. P., Castilho B. V. A libraryof high resolution synthetic stellar spectra from300nm to1.8μm withsolar and α-enhanced composition. A&A,2005,443:735–746.
[75] Martins L. P., Gonza′lez Delgado R. M., Leitherer C., Cervin o M.,Hauschildt P. A high-resolution stellar library for evolutionary populationsynthesis. MNRAS,2005,358:49–65.
[76] Lanc on A., Hauschildt P. H., Ladjal D., Mouhcine M. Near-IR spectra ofred supergiants and giants. I. Models with solar and with mixing-inducedsurface abundance ratios. A&A,2007,468:205–220.
[77] Le Borgne J.-F., Bruzual G., Pello′R., Lanc on A., Rocca-Volmerange B.,Sanahuja B., Schaerer D., Soubiran C., et al. STELIB: A library of stellarspectra at R2000. A&A,2003,402:433–442.
[78] Sa′nchez-Bla′zquez P., Peletier R. F., Jim′enez-Vicente J., Cardiel N., CenarroA. J., Falc′on-Barroso J., Gorgas J., Selam S., et al. Medium-resolution IsaacNewton Telescope library of empirical spectra. MNRAS,2006,371:703–718.
[79] Cenarro A. J., Peletier R. F., Sa′nchez-Bla′zquez P., Selam S. O., Toloba E.,Cardiel N., Falc′on-Barroso J., Gorgas J., et al. Medium-resolution IsaacNewton Telescope library of empirical spectra-II. The stellar atmosphericparameters. MNRAS,2007,374:664–690.
[80] Valdes F., Gupta R., Rose J. A., Singh H. P., Bell D. J. The Indo-US Libraryof Coud′e Feed Stellar Spectra. ApJS,2004,152:251–259.
[81] Prugniel P., Soubiran C. A database of high and medium-resolution stellarspectra. A&A,2001,369:1048–1057.
[82] Prugniel P., Soubiran C., Koleva M., Le Borgne D. New release of theELODIE library: Version3.1. ArXiv Astrophysics e-prints,2007.
[83] Gregg M. D., Silva D., Rayner J., Valdes F., Worthey G., Pickles A., Rose J.A., Vacca W., et al. The HST/STIS Next Generation Spectral Library. InAmerican Astronomical Society Meeting Abstracts, volume36of Bulletinof the American Astronomical Society, page1496,2004.
[84] Coelho P. Spectral libraries and their uncertainties. In G. Giobbi, A.Tornambe, G. Raimondo, M. Limongi, L. A. Antonelli, N. Menci,&E.Brocato, editor, American Institute of Physics Conference Series, volume1111of American Institute of Physics Conference Series, pages67–74,2009.
[85] Kurucz R. L. Including all the lines. Memorie della Societa AstronomicaItaliana Supplementi,2005,8:86.
[86] Walcher C. J., Coelho P., Gallazzi A., Charlot S. Diferential stellar pop-ulation models: how to reliably measure [Fe/H] and [α/Fe] in galaxies.MNRAS,2009,398:L44–L48.
[87] Maeder A., Meynet G. Tables of evolutionary star models from0.85to120solar masses with overshooting and mass loss. A&AS,1988,76:411–425.
[88] Prather M. J. The efect of a Brans-Dicke cosmology upon stellar evolutionand the evolution of galaxies. PhD thesis, Yale University., New Haven,CT.,1976.
[89] Bressan A., Granato G. L., Silva L. Modelling intermediate age and oldstellar populations in the Infrared. A&A,1998,332:135–148.
[90] Le Borgne D., Rocca-Volmerange B., Prugniel P., Lan con A., Fioc M.,Soubiran C. Evolutionary synthesis of galaxies at high spectral resolu-tion with the code PEGASE-HR. Metallicity and age tracers. A&A,2004,425:881–897.
[91] Dotter A., Chaboyer B., Ferguson J. W., Lee H.-c., Worthey G., Jevre-movi′c D., Baron E. Stellar Population Models and Individual ElementAbundances. I. Sensitivity of Stellar Evolution Models. ApJ,2007,666:403–412.
[92] Conroy C., Gunn J. E., White M. The Propagation of Uncertainties in Stel-lar Population Synthesis Modeling. I. The Relevance of Uncertain Aspectsof Stellar Evolution and the Initial Mass Function to the Derived PhysicalProperties of Galaxies. ApJ,2009,699:486–506.
[93] Lee H.-c., Worthey G., Dotter A., Chaboyer B., Jevremovi′c D., Baron E.,Briley M. M., Ferguson J. W., et al. Stellar Population Models and Individ-ual Element Abundances. II. Stellar Spectra and Integrated Light Models.ApJ,2009,694:902–923.
[94] Ferland G., Korista K., Verner D., Ferguson J., Kingdon J., Verner E.CLOUDY90: Numerical Simulation of Plasmas and Their Spectra. PASP,1998,110(749):761.
[95] Groves B., Dopita M. A., Sutherland R. S., Kewley L. J., Fischera J., Lei-therer C., Brandl B., van Breugel W. Modeling the Pan-Spectral EnergyDistribution of Starburst Galaxies. IV. The Controlling Parameters of theStarburst SED. ApJS,2008,176:438–456.
[96] Ferland G. J. Quantitative Spectroscopy of Photoionized Clouds. ARA&A,2003,41:517–554.
[97] Cepa J. The Emission-Line Universe. Canary Islands Winter School ofAstrophysics, Cambridge University Press,2009.
[98] Draine B. T. Interstellar Dust Grains. ARA&A,2003,41:241–289.
[99] Mathis J. S., Rumpl W., Nordsieck K. H. The size distribution of interstellargrains. ApJ,1977,217:425–433.
[100] Leger A., Puget J. L. Identifcation of the’unidentifed’ IR emission featuresof interstellar dust? A&A,1984,137:L5–L8.
[101] Jones A. P., Tielens A. G. G. M., Hollenbach D. J. Grain Shattering inShocks: The Interstellar Grain Size Distribution. ApJ,1996,469:740.
[102] Draine B. T., Lee H. M. Optical properties of interstellar graphite andsilicate grains. ApJ,1984,285:89–108.
[103] Calzetti D., Kinney A. L., Storchi-Bergmann T. Dust extinction of thestellar continua in starburst galaxies: The ultraviolet and optical extinctionlaw. ApJ,1994,429:582–601.
[104] Calzetti D. Reddening and Star Formation in Starburst Galaxies. AJ,1997,113:162–184.
[105] Silva L., Granato G. L., Bressan A., Danese L. Modeling the Efects ofDust on Galactic Spectral Energy Distributions from the Ultraviolet to theMillimeter Band. ApJ,1998,509:103–117.
[106] Charlot S., Fall S. M. A Simple Model for the Absorption of Starlight byDust in Galaxies. ApJ,2000,539:718–731.
[107] Andriesse C. D. Far-infrared properties of interstellar grains. A&A,1974,37:257–262.
[108] Agladze N. I., Sievers A. J., Jones S. A., Burlitch J. M., Beckwith S. V.W. Laboratory Results on Millimeter-Wave Absorption in Silicate GrainMaterials at Cryogenic Temperatures. ApJ,1996,462:1026.
[109] Mennella V., Brucato J. R., Colangeli L., Palumbo P., Rotundi A., Busso-letti E. Temperature Dependence of the Absorption Coefcient of CosmicAnalog Grains in the Wavelength Range20Microns to2Millimeters. ApJ,1998,496:1058.
[110] Popescu C. C., Tufs R. J. The percentage of stellar light re-radiated bydust in late-type Virgo Cluster galaxies. MNRAS,2002,335:L41–L44.
[111] Hippelein H., Haas M., Tufs R. J., Lemke D., Stickel M., Klaas U., Vo¨lk H.J. The spiral galaxy M33mapped in the FIR by ISOPHOT. A spatiallyresolved study of the warm and cold dust. A&A,2003,407:137–146.
[112] Sauvage M., Tufs R. J., Popescu C. C. Normal Nearby Galaxies. SSRv,2005,119:313–353.
[113] Dale D. A., Helou G., Contursi A., Silbermann N. A., Kolhatkar S. TheInfrared Spectral Energy Distribution of Normal Star-forming Galaxies.ApJ,2001,549:215–227.
[114] Dale D. A., Helou G. The Infrared Spectral Energy Distribution of Nor-mal Star-forming Galaxies: Calibration at Far-Infrared and SubmillimeterWavelengths. ApJ,2002,576:159–168.
[115] Draine B. T., Li A. Infrared Emission from Interstellar Dust. IV. TheSilicate-Graphite-PAH Model in the Post-Spitzer Era. ApJ,2007,657:810–837.
[116] Devriendt J. E. G., Guiderdoni B., Sadat R. Galaxy modelling. I. Spectralenergy distributions from far-UV to sub-mm wavelengths. A&A,1999,350:381–398.
[117] da Cunha E., Charlot S., Elbaz D. A simple model to interpret the ultra-violet, optical and infrared emission from galaxies. MNRAS,2008,388:1595–1617.
[118] Desert F.-X., Boulanger F., Puget J. L. Interstellar dust models for extinc-tion and emission. A&A,1990,237:215–236.
[119] Noll S., Burgarella D., Giovannoli E., Buat V., Marcillac D., Mun oz-MateosJ. C. Analysis of galaxy spectral energy distributions from far-UV to far-IRwith CIGALE: studying a SINGS test sample. A&A,2009,507:1793–1813.
[120] Efstathiou A., Rowan-Robinson M., Siebenmorgen R. Massive star forma-tion in galaxies: radiative transfer models of the UV to millimetre emissionof starburst galaxies. MNRAS,2000,313:734–744.
[121] Siebenmorgen R., Kru¨gel E. Dust in starburst nuclei and ULIRGs. SEDmodels for observers. A&A,2007,461:445–453.
[122] Granato G. L., Lacey C. G., Silva L., Bressan A., Baugh C. M., Cole S.,Frenk C. S. The Infrared Side of Galaxy Formation. I. The Local Universein the Semianalytical Framework. ApJ,2000,542:710–730.
[123] Tufs R. J., Popescu C. C., Vo¨lk H. J., Kylafs N. D., Dopita M. A. Modellingthe spectral energy distribution of galaxies. III. Attenuation of stellar lightin spiral galaxies. A&A,2004,419:821–835.
[124] Kylafs N. D., Bahcall J. N. Dust distribution in spiral galaxies. ApJ,1987,317:637–645.
[125] Gordon K. D., Misselt K. A., Witt A. N., Clayton G. C. The DIRTY Model.I. Monte Carlo Radiative Transfer through Dust. ApJ,2001,551:269–276.
[126] Misselt K. A., Gordon K. D., Clayton G. C., Wolf M. J. The DIRTY Model.II. Self-consistent Treatment of Dust Heating and Emission in a Three-dimensional Radiative Transfer Code. ApJ,2001,551:277–293.
[127] Chakrabarti S., Whitney B. A. Panchromatic Spectral Energy Distributionsof Dusty Galaxies with RADISHE. I. Predictions for Herschel: CorrelatingColors with Galactic Energy Sources. ApJ,2009,690:1432–1451.
[128] Baes M., Davies J. I., Dejonghe H., Sabatini S., Roberts S., Evans R., LinderS. M., Smith R. M., et al. Radiative transfer in disc galaxies-III. Theobserved kinematics of dusty disc galaxies. MNRAS,2003,343:1081–1094.
[129] Jonsson P. SUNRISE: polychromatic dust radiative transfer in arbitrarygeometries. MNRAS,2006,372:2–20.
[130] Jonsson P., Groves B. A., Cox T. J. High-resolution panchromatic spectralmodels of galaxies including photoionization and dust. MNRAS,2010,403:17–44.
[131] Bianchi S., Ferrara A., Giovanardi C. Monte Carlo Simulations of DustySpiral Galaxies: Extinction and Polarization Properties. ApJ,1996,465:127.
[132] Bianchi S., Davies J. I., Alton P. B. Monte Carlo predictions of far-infraredemission from spiral galaxies. A&A,2000,359:65–81.
[133] Bianchi S. Dust extinction and emission in a clumpy galactic disk. Anapplication of the radiative transfer code TRADING. A&A,2008,490:461–475.
[134] Treister E., Urry C. M., Chatzichristou E., Bauer F., Alexander D. M.,Koekemoer A., Van Duyne J., Brandt W. N., et al. Obscured Active Galac-tic Nuclei and the X-Ray, Optical, and Far-Infrared Number Counts ofActive Galactic Nuclei in the GOODS Fields. ApJ,2004,616(1):123.
[135] Treister E., Urry C. M., Van Duyne J., Dickinson M., Chary R., AlexanderD. M., Bauer F., Natarajan P., et al. Spitzer Number Counts of ActiveGalactic Nuclei in the GOODS Fields. ApJ,2006,640(2):603.
[136] Nenkova M., Sirocky M. M., Ivezi′cZˇ., Elitzur M. AGN Dusty Tori. I.Handling of Clumpy Media. ApJ,2008,685:147–159.
[137] Nenkova M., Sirocky M. M., Nikutta R., Ivezi′cZˇ., Elitzur M. AGN DustyTori. II. Observational Implications of Clumpiness. ApJ,2008,685:160–180.
[138] Ballantyne D. R., Shi Y., Rieke G. H., Donley J. L., Papovich C., Rigby J.R. Does the AGN Unifed Model Evolve with Redshift?: Using the X-RayBackground to Predict the Mid-Infrared Emission of AGNs. ApJ,2006,653:1070–1088.
[139] Tozzi P., Gilli R., Mainieri V., Norman C., Risaliti G., Rosati P., BergeronJ., Borgani S., et al. X-ray spectral properties of active galactic nuclei inthe Chandra Deep Field South. A&A,2006,451(2):457.
[140] Ballantyne D. R., Everett J. E., Murray N. Connecting Galaxy Evolution,Star Formation, and the Cosmic X-Ray Background. ApJ,2006,639(2):740.
[141] Hao L., Strauss M. A., Fan X., Tremonti C. A., Schlegel D. J., Heckman T.M., Kaufmann G., Blanton M. R., et al. Active Galactic Nuclei in the SloanDigital Sky Survey. II. Emission-Line Luminosity Function. AJ,2005,129(4):1795.
[142] Hasinger G. Absorption properties and evolution of active galactic nuclei.A&A,2008,490(3):905.
[143] Baldwin J. A., Phillips M. M., Terlevich R. Classifcation parameters forthe emission-line spectra of extragalactic objects. PASP,1981,93:5.
[144] Kewley L. J., Dopita M. A., Smith H. A. Do Mergers Stop Monsters? InBulletin of the American Astronomical Society, volume33of Bulletin ofthe American Astronomical Society, page1365,2001.
[145] Kaufmann G., Heckman T. M., Tremonti C., Brinchmann J., Charlot S.,White S. D. M., Ridgway S. E., Brinkmann J., et al. The host galaxies ofactive galactic nuclei. MNRAS,2003,346(4):1055.
[146] Kewley L. J., Groves B., Kaufmann G., Heckman T. The host galaxies andclassifcation of active galactic nuclei. MNRAS,2006,372(3):961.
[147] Moran E. C., Filippenko A. V., Chornock R.“Hidden” Seyfert2Galaxiesand the X-Ray Background. ApJ,2002,579(2):L71.
[148] Netzer H., Mainieri V., Rosati P., Trakhtenbrot B. The correlation of narrowline emission and X-ray luminosity in active galactic nuclei. A&A,2006,453(2):525.
[149] Rigby J. R., Rieke G. H., Donley J. L., Alonso-Herrero A., Perez-GonzalezP. G. Why X-Ray-selected Active Galactic Nuclei Appear Optically Dull.ApJ,2006,645(1):115.
[150] Brusa M., Civano F., Comastri A., Miyaji T., Salvato M., Zamorani G.,Cappelluti N., Fiore F., et al. THE XMM-NEWTONWIDE-FIELD SUR-VEY IN THE COSMOS FIELD (XMM-COSMOS): DEMOGRAPHYAND MULTIWAVELENGTH PROPERTIES OF OBSCURED AND UN-OBSCURED LUMINOUS ACTIVE GALACTIC NUCLEI. ApJ,2010,716(1):348.
[151] Risaliti G., Maiolino R., Salvati M. The Distribution of Absorbing ColumnDensities among Seyfert2Galaxies. ApJ,1999,522(1):157.
[152] Matt G., Guainazzi M., Frontera F., Bassani L., Brandt W. N., Fabian A.C., Fiore F., Haardt F., et al. Hard X-ray detection of NGC1068withBeppoSAX. A&A,1997,325:–13.
[153] Stefen A. T., Strateva I., Brandt W. N., Alexander D. M., Koekemoer A. M.,Lehmer B. D., Schneider D. P., Vignali C. The X-Ray-to-Optical Propertiesof Optically Selected Active Galaxies over Wide Luminosity and RedshiftRanges. AJ,2006,131:2826–2842.
[154] Hopkins P. F., Richards G. T., Hernquist L. An Observational Determi-nation of the Bolometric Quasar Luminosity Function. ApJ,2007,654:731–753.
[155] Vagnetti F., Turriziani S., Trevese D., Antonucci M. Variability and theX-ray/UV ratio of active galactic nuclei. A&A,2010,519:A17.
[156] Alonso-Herrero A., Quillen A. C., Simpson C., Efstathiou A., Ward M. J.The Nonstellar Infrared Continuum of Seyfert Galaxies. AJ,2001,121(3):1369.
[157] Krabbe A., Boker T., Maiolino R. N-Band Imaging of Seyfert Nuclei andthe Mid-Infrared–X-Ray Correlation. ApJ,2001,557(2):626.
[158] Lutz D., Maiolino R., Spoon H. W. W., Moorwood A. F. M. The relationbetween AGN hard X-ray emission and mid-infrared continuum from ISOspectra: Scatter and unifcation aspects. A&A,2004,418(2):465.
[159] Horst H., Smette A., Gandhi P., Duschl W. J. The small dispersion of themid IR–hard X-ray correlation in active galactic nuclei. A&A,2006,457(2):L17.
[160] Horst H., Gandhi P., Smette A., Duschl W. J. The mid IR–hard X-raycorrelation in AGN and its implications for dusty torus models. A&A,2008,479(2):389.
[161] Ho¨nig S. F., Kishimoto M., Gandhi P., Smette A., Asmus D., Duschl W.,Polletta M., Weigelt G. The dusty heart of nearby active galaxies I. High-spatial resolution mid-IR spectro-photometry of Seyfert galaxies. A&A,2010,515:A23.
[162] Ho¨nig S. F., Kishimoto M. The dusty heart of nearby active galaxies II.From clumpy torus models to physical properties of dust around AGN.A&A,2010,523:A27.
[163] Gandhi P., Horst H., Smette A., Ho¨nig S., Comastri A., Gilli R., Vignali C.,Duschl W. Resolving the mid-infrared cores of local Seyferts. A&A,2009,502(2):457.
[164] Mullaney J. R., Alexander D. M., Goulding A. D., Hickox R. C. Defningthe intrinsic AGN infrared spectral energy distribution and measuring itscontribution to the infrared output of composite galaxies. MNRAS,2011,414:1082–1110.
[165] Draper A. R., Ballantyne D. R. Properties and Expected Number Countsof Active Galactic Nuclei and Their Hosts in the Far-infrared. ApJ,2011,729(2):109.
[166] Hopkins P. F., Hernquist L., Cox T. J., Robertson B., Krause E. An Ob-served Fundamental Plane Relation for Supermassive Black Holes. ApJ,2007,669:67–73.
[167] Kormendy J., Bender R. Correlations between Supermassive Black Holes,Velocity Dispersions, and Mass Defcits in Elliptical Galaxies with Cores.ApJL,2009,691:L142–L146.
[168] Gu¨ltekin K., Richstone D. O., Gebhardt K., Lauer T. R., Tremaine S., AllerM. C., Bender R., Dressler A., et al. The M-σ and M-L Relations in GalacticBulges, and Determinations of Their Intrinsic Scatter. ApJ,2009,698:198–221.
[169] Merloni A., Bongiorno A., Bolzonella M., Brusa M., Civano F., Comastri A.,Elvis M., Fiore F., et al. On the Cosmic Evolution of the Scaling RelationsBetween Black Holes and Their Host Galaxies: Broad-Line Active GalacticNuclei in the zCOSMOS Survey. ApJ,2010,708:137–157.
[170] Ferrarese L., Merritt D. A Fundamental Relation between SupermassiveBlack Holes and Their Host Galaxies. ApJ,2000,539(1):L9.
[171] Gebhardt K., Bender R., Bower G., Dressler A., Faber S. M., Filippenko A.V., Green R., Grillmair C., et al. A Relationship between Nuclear BlackHole Mass and Galaxy Velocity Dispersion. ApJ,2000,539(1):L13.
[172] Tremaine S., Gebhardt K., Bender R., Bower G., Dressler A., Faber S. M.,Filippenko A. V., Green R., et al. The Slope of the Black Hole Mass versusVelocity Dispersion Correlation. ApJ,2002,574:740–753.
[173] Magorrian J., Tremaine S., Richstone D., Bender R., Bower G., Dressler A.,Faber S. M., Gebhardt K., et al. The Demography of Massive Dark Objectsin Galaxy Centers. AJ,1998,115(6):2285.
[174] Ha¨ring N., Rix H.-W. On the Black Hole Mass-Bulge Mass Relation. ApJL,2004,604:L89–L92.
[175] Graham A. W. Core Depletion from Coalescing Supermassive Black Holes.ApJL,2004,613:L33–L36.
[176] Kormendy J., Richstone D. Inward Bound–The Search for SupermassiveBlack Holes in Galactic Nuclei. ARA&A,1995,33(1):581.
[177] Marconi A., Hunt L. K. The Relation between Black Hole Mass, BulgeMass, and Near-Infrared Luminosity. ApJ,2003,589(1):L21.
[178] Hopkins A. M. On the Evolution of Star-forming Galaxies. ApJ,2004,615(1):209.
[179] Silverman J. D., Green P. J., Barkhouse W. A., Kim D. W., Kim M., WilkesB. J., Cameron R. A., Hasinger G., et al. The Luminosity Function ofX-Ray-selected Active Galactic Nuclei: Evolution of Supermassive BlackHoles at High Redshift. ApJ,2008,679:118–139.
[180] Aird J., Nandra K., Laird E. S., Georgakakis A., Ashby M. L. N., BarmbyP., Coil A. L., Huang J.-S., et al. The evolution of the hard X-ray luminosityfunction of AGN. MNRAS,2010,401(4):2531.
[181] Yu Q., Tremaine S. Observational constraints on growth of massive blackholes. MNRAS,2002,335:965–976.
[182] Marconi A., Risaliti G., Gilli R., Hunt L. K., Maiolino R., Salvati M. Lo-cal supermassive black holes, relics of active galactic nuclei and the X-raybackground. MNRAS,2004,351(1):169.
[183] Merloni A. The anti-hierarchical growth of supermassive black holes. MN-RAS,2004,353:1035–1047.
[184] Yu Q., Lu Y. Toward Precise Constraints on the Growth of Massive BlackHoles. ApJ,2008,689:732–754.
[185] Croton D. J., Springel V., White S. D. M., De Lucia G., Frenk C. S., GaoL., Jenkins A., Kaufmann G., et al. The many lives of active galactic nu-clei: cooling fows, black holes and the luminosities and colours of galaxies.MNRAS,2006,365(1):11.
[186] Bower R. G., Benson A. J., Malbon R., Helly J. C., Frenk C. S., BaughC. M., Cole S., Lacey C. G. Breaking the hierarchy of galaxy formation.MNRAS,2006,370(0):645–655.
[187] Di Matteo T., Springel V., Hernquist L. Energy input from quasars regu-lates the growth and activity of black holes and their host galaxies. Nature,2005,433:604–607.
[188] Di Matteo T., Colberg J., Springel V., Hernquist L., Sijacki D. Direct Cos-mological Simulations of the Growth of Black Holes and Galaxies. ApJ,2008,676(1):33.
[189] Hopkins P. F., Hernquist L., Cox T. J., Di Matteo T., Martini P., RobertsonB., Springel V. Black Holes in Galaxy Mergers: Evolution of Quasars. ApJ,2005,630(2):705.
[190] Hopkins P. F., Somerville R. S., Hernquist L., Cox T. J., Robertson B., Li Y.The Relation between Quasar and Merging Galaxy Luminosity Functionsand the Merger-driven Star Formation History of the Universe. ApJ,2006,652:864–888.
[191] Hopkins P. F., Hernquist L., Cox T. J., Keres D. A Cosmological Frameworkfor the Co-Evolution of Quasars, Supermassive Black Holes, and EllipticalGalaxies: I. Galaxy Mergers&Quasar Activity. ApJ,2008,175:356.
[192] Nagar N. M., Falcke H., Wilson A. S. Radio sources in low-luminosity activegalactic nuclei. A&A,2005,435(2):521.
[193] Babbedge T. S. R., Rowan-Robinson M., Vaccari M., Surace J. A., LonsdaleC. J., Clements D. L., Fang F., Farrah D., et al. Luminosity functions forgalaxies and quasars in the Spitzer Wide-area Infrared Extragalactic LegacySurvey. MNRAS,2006,370(3):1159.
[194] Brown M. J. I., Brand K., Dey A., Jannuzi B. T., Cool R., Le Floc’h E.,Kochanek C. S., Armus L., et al. The1 [195] Matute I., La Franca F., Pozzi F., Gruppioni C., Lari C., Zamorani G. Ac-tive galactic nuclei in the mid-IR. A&A,2006,451(2):443.
[196] Fan X., Strauss M. A., Schneider D. P., Gunn J. E., Lupton R. H., BeckerR. H., Davis M., Newman J. A., et al. High-Redshift Quasars Found inSloan Digital Sky Survey Commissioning Data. IV. Luminosity Functionfrom the Fall Equatorial Stripe Sample. AJ,2001,121(1):54.
[197] Wolf C., Wisotzki L., Borch A., Dye S., Kleinheinrich M., Meisenheimer K.The evolution of faint AGN between z=1and z=5from the COMBO-17survey. A&A,2003,408:499–514.
[198] Croom S. M., Smith R. J., Boyle B. J., Shanks T., Miller L., Outram P.J., Loaring N. S. The2dF QSO Redshift Survey-XII. The spectroscopiccatalogue and luminosity function. MNRAS,2004,349:1397–1418.
[199] Richards G. T., Strauss M. A., Fan X., Hall P. B., Jester S., Schneider D.P., Vanden Berk D. E., Stoughton C., et al. The Sloan Digital Sky SurveyQuasar Survey: Quasar Luminosity Function from Data Release3. AJ,2006,131:2766–2787.
[200] Bongiorno A., Zamorani G., Gavignaud I., Marano. The VVDS type-1AGNsample: the faint end of the luminosity function. A&A,2007,472:443–454.
[201] Fontanot F., Cristiani S., Monaco P., Nonino M., Vanzella E., Brandt W. N.,Grazian A., Mao J. The luminosity function of high-redshift quasi-stellarobjects. A combined analysis of GOODS and SDSS. A&A,2007,461(1):39.
[202] Shankar F., Mathur S. On the Faint End of the High-Redshift ActiveGalactic Nucleus Luminosity Function. ApJ,2007,660(2):1051.
[203] Miyaji T., Hasinger G., Schmidt M. Soft X-ray AGN luminosity functionfrom it ROSAT surveys. I. Cosmological evolution and contribution to thesoft X-ray background. A&A,2000,353:25–40.
[204] Miyaji T., Hasinger G., Schmidt M. Soft X-ray AGN luminosity functionfrom ROSAT surveys. A&A,2001,369(1):49.
[205] Silverman J. D., Green P. J., Barkhouse W. A., Cameron R. A., Foltz C.,Jannuzi B. T., Kim D.-W., Kim M., et al. Comoving Space Density ofX-Ray-selected Active Galactic Nuclei. ApJ,2005,624:630–637.
[206] Hasinger G., Miyaji T., Schmidt M. Luminosity-dependent evolution ofsoft X-ray selected AGN. New Chandra and XMM-Newton surveys. A&A,2005,441:417–434.
[207] Ueda Y., Akiyama M., Ohta K., Miyaji T. Cosmological Evolution of theHard X-Ray Active Galactic Nucleus Luminosity Function and the Originof the Hard X-Ray Background. ApJ,2003,598(2):886.
[208] La Franca F., Fiore F., Comastri A., Perola G. C., Sacchi N., Brusa M.,Cocchia F., Feruglio C., et al. The HELLAS2XMM Survey. VII. The HardX-Ray Luminosity Function of AGNs up to z=4: More Absorbed AGNsat Low Luminosities and High Redshifts. ApJ,2005,635:864–879.
[209] Silverman J. D., Green P. J., Barkhouse W. A., Kim D.-W., Aldcroft T.L., Cameron R. A., Wilkes B. J., Mossman A., et al. Hard X-Ray-emittingActive Galactic Nuclei Selected by the Chandra Multiwavelength Project.ApJ,2005,618:123–138.
[210] Yencho B., Barger A. J., Trouille L., Winter L. M. The OPTX Project. II.Hard X-Ray Luminosity Functions of Active Galactic Nuclei for z lsim5.ApJ,2009,698:380–396.
[211] Ebrero J., Carrera F. J., Page M. J., Silverman J. D., Barcons X., CeballosM. T., Corral A., Della Ceca R., et al. The XMM-Newton serendipitoussurvey. VI. The X-ray luminosity function. A&A,2009,493:55–69.
[212] Barger A. J., Cowie L. L., Mushotzky R. F., Yang Y., Wang W.-H., StefenA. T., Capak P. The Cosmic Evolution of Hard X-Ray-selected ActiveGalactic Nuclei. AJ,2005,129(2):578.
[213] Cirasuolo M., Magliocchetti M., Celotti A. Faint radio-loud quasars: cluesto their evolution. MNRAS,2005,357:1267–1280.
[214] Barcons X., Carrera F. J., Ceballos M. T., Page M. J., Bussons-Gordo J.,Corral A., Ebrero J., Mateos S., et al. The XMM-Newton serendipitoussurvey. A&A,2007,476(3):1191.
[215] Fu H., Yan L., Scoville N. Z., Capak P., Aussel H., Floc’h E. L., IlbertO., Salvato M., et al. Decomposing Star Formation and Active GalacticNucleus with Spitzer Mid-infrared Spectra: Luminosity Functions and Co-evolution. ApJ,2010,722(1):653.
[216] Hopkins P. F., Younger J. D., Hayward C. C., Narayanan D., HernquistL. Mergers, active galactic nuclei and ‘normal’ galaxies: contributions tothe distribution of star formation rates and infrared luminosity functions.MNRAS,2010,402(3):1693–1713.
[217] Netzer H., Lutz D., Schweitzer M., Contursi A., Sturm E., Tacconi L.J., Veilleux S., Kim D., et al. Spitzer Quasar and ULIRG EvolutionStudy (QUEST). II. The Spectral Energy Distributions of Palomar-GreenQuasars. ApJ,2007,666(2):806.
[218] Nenkova M., Ivezi′cZˇ., Elitzur M. Dust Emission from Active GalacticNuclei. ApJ,2002,570(1):L9.
[219] Ho¨nig S. F., Beckert T., Ohnaka K., Weigelt G. Radiative transfer modelingof three-dimensional clumpy AGN tori and its application to NGC1068.A&A,2006,452:459–471.
[220] Canalizo G., Stockton A. Quasi-Stellar Objects, Ultraluminous InfraredGalaxies, and Mergers. ApJ,2001,555(2):719.
[221] Hutchings J. B. What is the diference between radio galaxies and radioquasar galaxies? ApJ,1987,320:122.
[222] Disney M. J., Boyce P. J., Blades J. C., Boksenberg A., Crane P., DeharvengJ. M., Macchetto F., Mackay C. D., et al. Interacting elliptical galaxies ashosts of intermediate-redshift quasars. Nat,1995,376(6536):150.
[223] Bahcall J. N., Kirhakos S., Saxe D. H., Schneider D. P. Hubble Space Tele-scopeImages of a Sample of20Nearby Luminous Quasars. ApJ,1997,479(2):642.
[224] Kirhakos S., Bahcall J. N., Schneider D. P., Kristian J. The Host Galaxiesof Three Radio-loud Quasars:3C48,3C345, and B21425+267. ApJ,1999,520(1):67.
[225] Laurikainen E., Salo H. Environments of Seyfert galaxies. II. Statisticalanalyses. A&A,1995,293:683–702.
[226] Schmitt H. R. The Frequency of Active and Quiescent Galaxies with Com-panions: Implications for the Feeding of the Nucleus. AJ,2001,122(5):2243.
[227] Grogin N. A., Conselice C. J., Chatzichristou E., Alexander D. M., BauerF. E., Hornschemeier A. E., Jogee S., Koekemoer A. M., et al. AGN HostGalaxies atz0.4-1.3: Bulge-dominated and Lacking Merger-AGN Connec-tion. ApJ,2005,627(2):L97.
[228] Ben′tez N. Bayesian Photometric Redshift Estimation. ApJ,2000,536:571–583.
[229] Kaufmann G., Heckman T. M., White S. D. M., Charlot S., Tremonti C.,Brinchmann J., Bruzual G., Peng E. W., et al. Stellar masses and starformation histories for105galaxies from the Sloan Digital Sky Survey.MNRAS,2003,341:33–53.
[230] Feldmann R., Carollo C. M., Porciani C., Lilly S. J., Capak P., Taniguchi Y.,Le F`evre O., Renzini A., et al. The Zurich Extragalactic Bayesian RedshiftAnalyzer and its frst application: COSMOS. MNRAS,2006,372:565–577.
[231] Salim S., Rich R. M., Charlot S., Brinchmann J., Johnson B. D., Schimi-novich D., Seibert M., Mallery R., et al. UV Star Formation Rates in theLocal Universe. ApJS,2007,173:267–292.
[232] Bailer-Jones C. A. L. Bayesian inference of stellar parameters and interstel-lar extinction using parallaxes and multiband photometry. MNRAS,2011,411:435–452.
[233] Lahav O., Naim A., Sodr′e Jr. L., Storrie-Lombardi M. C. Neural computa-tion as a tool for galaxy classifcation: methods and examples. MNRAS,1996,283:207–+.
[234] Bertin E., Arnouts S. SExtractor: Software for source extraction. A&AS,1996,117:393–404.
[235] Andreon S., Gargiulo G., Longo G., Tagliaferri R., Capuano N. Widefeld imaging-I. Applications of neural networks to object detection andstar/galaxy classifcation. MNRAS,2000,319:700–716.
[236] Firth A. E., Lahav O., Somerville R. S. Estimating photometric redshiftswith artifcial neural networks. MNRAS,2003,339:1195–1202.
[237] Collister A. A., Lahav O. ANNz: Estimating Photometric Redshifts UsingArtifcial Neural Networks. PASP,2004,116:345–351.
[238] Vanzella E., Cristiani S., Fontana A., Nonino M., Arnouts S., Giallongo E.,Grazian A., Fasano G., et al. Photometric redshifts with the MultilayerPerceptron Neural Network: Application to the HDF-S and SDSS. A&A,2004,423:761–776.
[239] Carballo R., Gonza′lez-Serrano J. I., Benn C. R., Jim′enez-Luja′n F. Use ofneural networks for the identifcation of new z>=3.6QSOs from FIRST-SDSS DR5. MNRAS,2008,391:369–382.
[240] Auld T., Bridges M., Hobson M. P. COSMONET: fast cosmological param-eter estimation in non-fat models using neural networks. MNRAS,2008,387:1575–1582.
[241] Francis P. J., Hewett P. C., Foltz C. B., Chafee F. H. An objective classif-cation scheme for QSO spectra. ApJ,1992,398:476–490.
[242] Glazebrook K., Ofer A. R., Deeley K. Automatic Redshift Determinationby Use of Principal Component Analysis. I. Fundamentals. ApJ,1998,492:98–+.
[243] Wild V., Hewett P. C. Peering through the OH forest: a new techniqueto remove residual sky features from Sloan Digital Sky Survey spectra.MNRAS,2005,358:1083–1099.
[244] Wild V., Kaufmann G., Heckman T., Charlot S., Lemson G., BrinchmannJ., Reichard T., Pasquali A. Bursty stellar populations and obscured activegalactic nuclei in galaxy bulges. MNRAS,2007,381:543–572.
[245] Budava′ri T., Wild V., Szalay A. S., Dobos L., Yip C.-W. Reliable eigen-spectra for new generation surveys. MNRAS,2009,394:1496–1502.
[246] Asensio Ramos A., Ramos Almeida C. Bayesclumpy: Bayesian Inferencewith Clumpy Dusty Torus Models. ApJ,2009,696:2075–2085.
[247] Almeida C., Baugh C. M., Lacey C. G., Frenk C. S., Granato G. L., SilvaL., Bressan A. Modelling the dusty universe-I. Introducing the artifcialneural network and frst applications to luminosity and colour distributions.MNRAS,2010,402:544–564.
[248] Silva L., Schurer A., Granato G. L., Almeida C., Baugh C. M., Frenk C. S.,Lacey C. G., Paoletti L., et al. Modelling the spectral energy distributionof galaxies: introducing the artifcial neural network. MNRAS,2011,410:2043–2056.
[249] White S. D. M., Rees M. J. Core condensation in heavy halos-A two-stagetheory for galaxy formation and clustering. MNRAS,1978,183:341–358.
[250] Lacey C., Silk J. Tidally triggered galaxy formation. I-Evolution of thegalaxy luminosity function. ApJ,1991,381:14–32.
[251] White S. D. M., Frenk C. S. Galaxy formation through hierarchical cluster-ing. ApJ,1991,379:52–79.
[252] Ghosh J. K., Delampady M., Samanta T. An Introduction to BayesianAnalysis: Theory and Methods (Springer Texts in Statistics).1. Springer,2006.
[253] Trotta R. Bayes in the sky: Bayesian inference and model selection incosmology. Contemporary Physics,2008,49:71–104.
[254] Lyons L. A Particle Physicist’s Perspective on Astrostatistics. In G. J. Babu&E. D. Feigelson, editor, Statistical Challenges in Modern Astronomy IV,volume371of Astronomical Society of the Pacifc Conference Series, page361,2007.
[255] Jaynes E. T. Probability Theory: The Logic of Science. UK: CambridgeUniversity Press,2003.
[256] Ruiz de Austri R., Trotta R., Roszkowski L. A Markov chain Monte Carloanalysis of the CMSSM. Journal of High Energy Physics,2006,5:2.
[257] Trotta R., de Austri R. R., Roszkowski L. Prospects for direct dark matterdetection in the constrained MSSM. NewAR,2007,51:316–320.
[258] Roszkowski L., Ruiz de Austri R., Trotta R. On the detectability of theCMSSM light Higgs boson at the Tevatron. Journal of High Energy Physics,2007,4:84.
[259] Roszkowski L., Ruiz de Austri R., Trotta R. Implications for the Con-strained MSSM from a new prediction for b→sγ. Journal of High EnergyPhysics,2007,7:75.
[260] Trotta R., Feroz F., Hobson M., Roszkowski L., Ruiz de Austri R. Theimpact of priors and observables on parameter inferences in the constrainedMSSM. Journal of High Energy Physics,2008,12:24.
[261] Trotta R., Ruiz de Austri R., P′erez de los Heros C. Prospects for darkmatter detection with IceCube in the context of the CMSSM. JCAP,2009,8:34.
[262] Feroz F., Hobson M. P., Bridges M. MULTINEST: an efcient and robustBayesian inference tool for cosmology and particle physics. MNRAS,2009,398:1601–1614.
[263] Feroz F., Cranmer K., Hobson M., Ruiz de Austri R., Trotta R. Challengesof profle likelihood evaluation in multi-dimensional SUSY scans. Journalof High Energy Physics,2011,6:42.
[264] Gregory P. Bayesian Logical Data Analysis for the Physical Sciences. NewYork, NY, USA: Cambridge University Press,2005.
[265] Press W. H., Teukolsky S. A., Vetterling W. T., Flannery B. P. NumericalRecipes3rd Edition: The Art of Scientifc Computing.3. CambridgeUniversity Press,2007.
[266] Hobson M. P., McLachlan C. A Bayesian approach to discrete object de-tection in astronomical data sets. MNRAS,2003,338:765–784.
[267] Marshall P. J., Hobson M. P., Slosar A. Bayesian joint analysis of clusterweak lensing and Sunyaev-Zel’dovich efect data. MNRAS,2003,346:489–500.
[268] Slosar A., Carreira P., Cleary K., Davies R. D., Davis R. J., Dickinson C.,Genova-Santos R., Grainge K., et al. Cosmological parameter estimationand Bayesian model comparison using Very Small Array data. MNRAS,2003,341:L29–L34.
[269] Bassett B. A., Corasaniti P. S., Kunz M. The Essence of Quintessence andthe Cost of Compression. ApJL,2004,617:L1–L4.
[270] Niarchou A., Jafe A. H., Pogosian L. Large-scale power in the CMB andnew physics: An analysis using Bayesian model comparison. PhRvD,2004,69(6):063515.
[271] Beltra′n M., Garc′a-Bellido J., Lesgourgues J., Liddle A. R., Slosar A.Bayesian model selection and isocurvature perturbations. PhRvD,2005,71(6):063532.
[272] Bridges M., Lasenby A. N., Hobson M. P. A Bayesian analysis of the pri-mordial power spectrum. MNRAS,2006,369:1123–1130.
[273] Trotta R. Applications of Bayesian model selection to cosmological param-eters. MNRAS,2007,378:72–82.
[274] Skilling J. Nested Sampling. In R. Fischer, R. Preuss,&U. V. Toussaint,editor, American Institute of Physics Conference Series, volume735ofAmerican Institute of Physics Conference Series, pages395–405,2004.
[275] Mukherjee P., Parkinson D., Liddle A. R. A Nested Sampling Algorithmfor Cosmological Model Selection. ApJL,2006,638:L51–L54.
[276] Shaw J. R., Bridges M., Hobson M. P. Efcient Bayesian inference for mul-timodal problems in cosmology. MNRAS,2007,378:1365–1370.
[277] Feroz F., Hobson M. P. Multimodal nested sampling: an efcient and robustalternative to Markov Chain Monte Carlo methods for astronomical dataanalyses. MNRAS,2008,384:449–463.
[278] Cybenko G. Approximation by superpositions of a sigmoidal function.Mathematics of Control, Signals, and Systems (MCSS),1989,2:303–314,10.1007/BF02551274.
[279] Hornik K. Approximation capabilities of multilayer feedforward networks.Neural Networks,1991,4(2):251–257.
[280] Haykin S. Neural Networks: A Comprehensive Foundation. Upper SaddleRiver, NJ: Prentice Hall,1999.
[281] Ruiz A., Carrera F. J., Panessa F. An XMM-Newton study ofhyper-luminous infrared galaxies. A&A,2007,471:775–786.
[282] Rowan-Robinson M. Hyperluminous infrared galaxies. MNRAS,2000,316:885–900.
[283] Ruiz A., Miniutti G., Panessa F., Carrera F. J. Spectral energy distributionof hyperluminous infrared galaxies. A&A,2010,515:A99+.
[284] Cole S., Lacey C. G., Baugh C. M., Frenk C. S. Hierarchical galaxy forma-tion. MNRAS,2000,319:168–204.
[285] Kaufmann G., Haehnelt M. A unifed model for the evolution of galaxiesand quasars. MNRAS,2000,311:576–588.
[286] Hatton S., Devriendt J. E. G., Ninin S., Bouchet F. R., Guiderdoni B., Vib-ert D. GALICS-I. A hybrid N-body/semi-analytic model of hierarchicalgalaxy formation. MNRAS,2003,343:75–106.
[287] De Lucia G., Kaufmann G., White S. D. M. Chemical enrichment of theintracluster and intergalactic medium in a hierarchical galaxy formationmodel. MNRAS,2004,349:1101–1116.
[288] Somerville R. S., Hopkins P. F., Cox T. J., Robertson B. E., Hernquist L. Asemi-analytic model for the co-evolution of galaxies, black holes and activegalactic nuclei. MNRAS,2008,391:481–506.
[289] De Lucia G., Boylan-Kolchin M., Benson A. J., Fontanot F., Monaco P. Asemi-analytic model comparison-gas cooling and galaxy mergers. MNRAS,2010,406:1533–1552.
[290] Benson A. J. GALACTICUS: A semi-analytic model of galaxy formation.NewA,2012,17:175–197.
[291] Han Y., Han Z. Decoding Spectral Energy Distributions of Dust-obscuredStarburst-Active Galactic Nucleus. ApJ,2012,749:123.
[292] Han Y., Dai B., Wang B., Zhang F., Han Z. Evolution of luminosity functionand obscuration of AGN: connecting X-ray and Infrared. MNRAS,2012,accepted.
[293] Wang B., Liu Z., Han Y., Lei Z., Luo Y., Han Z. Birthrates and delay timesof Type Ia supernovae. Science in China G: Physics and Astronomy,2010,53:586–590.
[294] Jarosik N., Bennett C. L., Dunkley J., Gold B., Greason M. R., Halpern M.,Hill R. S., Hinshaw G., et al. Seven-year Wilkinson Microwave AnisotropyProbe (WMAP) Observations: Sky Maps, Systematic Errors, and BasicResults. ApJS,2011,192:14.
[2]Smoot G. F., Bennett C. L., Kogut A., Wright E. L., Aymon J., Boggess N. W., Cheng E. S., de Amici G., et al. Structure in the COBE differential microwave radiometer first-year maps. ApJL,1992,396:L1-L5.
[3]李宗伟,肖兴华.天体物理学.第1版.北京市西城区德外大街4号：高等教育出版社,2000.
[4]黄润乾.恒星物理.第1版.北京市海淀区中关村南大街16号：中国科学技术出版社,2006.
[5]Davis M., Guhathakurta P., Konidaris N. P., Newman J. A., Ashby M. L. N., Biggs A. D., Barmby P., Bundy K., et al. The All-Wavelength Extended Groth Strip International Survey (AEGIS) Data Sets. ApJL,2007,660: L1-L6.
[6]Wolf C., Meisenheimer K., Rix H.-W., Borch A., Dye S., Kleinheinrich M. The COMBO-17survey:Evolution of the galaxy luminosity function from25000galaxies with0.2
[8]Driver S. P., Norberg P., Baldry I. K., Bamford S. P., Hopkins A. M., Liske J., Loveday J., Peacock J. A., et al. GAMA:towards a physical under-standing of galaxy formation. Astronomy and Geophysics,2009,50(5):050000-5.
[9] Johnson B. D., Schiminovich D., Seibert M., Treyer M., Martin D. C., Bar-low T. A., Forster K., Friedman P. G., et al. Ultraviolet, Optical, and In-frared Constraints on Models of Stellar Populations and Dust Attenuation.ApJS,2007,173:377–391.
[10] Gavazzi G., Boselli A., Donati A., Franzetti P., Scodeggio M. IntroducingGOLDMine: A new galaxy database on the WEB. A&A,2003,400:451–455.
[11] Giavalisco M., Ferguson H. C., Koekemoer A. M., Dickinson M., AlexanderD. M., Bauer F. E., Bergeron J., Biagetti C., et al. The Great Observato-ries Origins Deep Survey: Initial Results from Optical and Near-InfraredImaging. ApJL,2004,600:L93–L98.
[12] Berriman G. B., Good J. C., Lonsdale C. J. The Infrared Science Archive(IRSA)at IPAC: Moving Towards the NVO. In American AstronomicalSociety Meeting Abstracts, volume32of Bulletin of the American Astro-nomical Society, page116.10,2000.
[13] Dale D. A., Cohen S. A., Johnson L. C., Schuster M. D., Calzetti D., En-gelbracht C. W., Gil de Paz A., Kennicutt R. C., et al. The Spitzer LocalVolume Legacy: Survey Description and Infrared Photometry. ApJ,2009,703:517–556.
[14] Imhof C., Abney F., Christian D., Donahue M., Hanisch R., Kimball T.,Levay K., Padovani P., et al. Resources Available through the MultimissionArchive at Space Telescope (MAST). In American Astronomical SocietyMeeting Abstracts#194, volume31of Bulletin of the American Astronom-ical Society, page968,1999.
[15] Taylor E. N., Franx M., van Dokkum P. G., Quadri R. F., Gawiser E., BellE. F., Barrientos L. F., Blanc G. A., et al. A Public, K-Selected, Optical-to-Near-Infrared Catalog of the Extended Chandra Deep Field South(ECDFS) from the Multiwavelength Survey by Yale-Chile (MUSYC).ApJS,2009,183:295–319.
[16] Abazajian K. N., Adelman-McCarthy J. K., Agu¨eros M. A., Allam S. S.,Allende Prieto C., An D., Anderson K. S. J., Anderson S. F., et al. TheSeventh Data Release of the Sloan Digital Sky Survey. ApJS,2009,182:543–558.
[17] Kennicutt Jr. R. C., Armus L., Bendo G., Calzetti D., Dale D. A., DraineB. T., Engelbracht C. W., Gordon K. D., et al. SINGS: The SIRTF NearbyGalaxies Survey. PASP,2003,115:928–952.
[18] Treyer M., Schiminovich D., Johnson B. D., O’Dowd M., Martin C. D.,Wyder T., Charlot S., Heckman T., et al. Mid-infrared Spectral Indica-tors of Star Formation and Active Galactic Nucleus Activity in NormalGalaxies. ApJ,2010,719:1191–1211.
[19] Lonsdale C. J., Smith H. E., Rowan-Robinson M., Surace J., Shupe D., XuC., Oliver S., Padgett D., et al. SWIRE: The SIRTF Wide-Area InfraredExtragalactic Survey. PASP,2003,115:897–927.
[20] Le F`evre O., Vettolani G., Garilli B., Tresse L., Bottini D., Le Brun V.,Maccagni D., Picat J. P., et al. The VIMOS VLT deep survey. First epochVVDS-deep survey:11564spectra with17.5≤IAB≤24, and the redshiftdistribution over0≤z≤5. A&A,2005,439:845–862.
[21] Casali M., Adamson A., Alves de Oliveira C., Almaini O., Burch K., ChuterT., Elliot J., Folger M., et al. The UKIRT wide-feld camera. A&A,2007,467:777–784.
[22] Walcher J., Groves B., Budava′ri T., Dale D. Fitting the integrated spectralenergy distributions of galaxies. Ap&SS,2011,331:1–52.
[23] Johnson H. L., Morgan W. W. Fundamental stellar photometry for stan-dards of spectral type on the revised system of the Yerkes spectral atlas.ApJ,1953,117:313.
[24] Bessell M. S. UBVRI passbands. PASP,1990,102:1181–1199.
[25] Koleva M., Prugniel P., Ocvirk P., Le Borgne D., Soubiran C. Spectroscopicages and metallicities of stellar populations: validation of full spectrumftting. MNRAS,2008,385:1998–2010.
[26] Koornneef J., Bohlin R., Buser R., Horne K., Turnshek D. Synthetic pho-tometry and the calibration of the Hubble Space Telescope. Highlights ofAstronomy,1986,7:833–843.
[27] Landolt A. U. UBVRI photometric standard stars in the magnitude range11.5-16.0around the celestial equator. AJ,1992,104:340–371.
[28] van Dokkum P. G., Labb′e I., Marchesini D., Quadri R., Brammer G.,Whitaker K. E., Kriek M., Franx M., et al. The NEWFIRM Medium-BandSurvey: Filter Defnitions and First Results. PASP,2009,121:2–8.
[29] Kakazu Y., Cowie L. L., Hu E. M. Mapping Extremely Low MetallicityGalaxies to Redshift One. ApJ,2007,668:853–875.
[30] Guillaume M., Llebaria A., Aymeric D., Arnouts S., Milliard B. Deblendingof the UV photometry in GALEX deep surveys using optical priors in thevisible wavelengths. In E. R. Dougherty, J. T. Astola, K. O. Egiazarian,N. M. Nasrabadi,&S. A. Rizvi, editor, Society of Photo-Optical Instru-mentation Engineers (SPIE) Conference Series, volume6064of Society ofPhoto-Optical Instrumentation Engineers (SPIE) Conference Series, pages332–341,2006.
[31] Roseboom I. G., Oliver S., Parkinson D., Vaccari M. A new approach tomultiwavelength associations of astronomical sources. MNRAS,2009,400:1062–1074.
[32] Oemler Jr. A. The structure of elliptical and cD galaxies. ApJ,1976,209:693–709.
[33] Carter D. The optical extent of giant E and cD galaxies. MNRAS,1977,178:137–148.
[34] Baade W. The Resolution of Messier32, NGC205, and the Central Regionof the Andromeda Nebula. ApJ,1944,100:137.
[35] Spinrad H., Taylor B. J. The Stellar Content of the Nuclei of Nearby Galax-ies. I. M31, M32, and M81. ApJS,1971,22:445.
[36] Faber S. M. Quadratic programming applied to the problem of galaxypopulation synthesis. A&A,1972,20:361–374.
[37] O’Connell R. W. Galaxy spectral synthesis. I-Stellar populations in thenuclei of giant ellipticals. ApJ,1976,206:370–390.
[38] Turnrose B. E. The stellar content of the nuclear regions of SC galaxies.ApJ,1976,210:33–37.
[39] Tinsley B. M. Galactic Evolution. A&A,1972,20:383–+.
[40] Searle L., Sargent W. L. W., Bagnuolo W. G. The History of Star Formationand the Colors of Late-Type Galaxies. ApJ,1973,179:427–438.
[41] Larson R. B., Tinsley B. M. Star formation rates in normal and peculiargalaxies. ApJ,1978,219:46–59.
[42] Tinsley B. M. Evolutionary synthesis of the stellar population in ellipticalgalaxies. II-Late M giants and composition efects. ApJ,1978,222:14–22.
[43] Bruzual A. G. Spectral evolution of galaxies. I-Early-type systems. ApJ,1983,273:105–127.
[44] Arimoto N., Yoshii Y. Chemical and photometric properties of a galacticwind model for elliptical galaxies. A&A,1987,173:23–38.
[45] Guiderdoni B., Rocca-Volmerange B. A model of spectrophotometric evo-lution for high-redshift galaxies. A&A,1987,186:1–21.
[46] Buzzoni A. Evolutionary population synthesis in stellar systems. I-Aglobal approach. ApJS,1989,71:817–869.
[47] Bruzual A. G., Charlot S. Spectral evolution of stellar populations usingisochrone synthesis. ApJ,1993,405:538–553.
[48] Bressan A., Chiosi C., Fagotto F. Spectrophotometric evolution of ellipti-cal galaxies.1: Ultraviolet excess and color-magnitude-redshift relations.ApJS,1994,94:63–115.
[49] Worthey G. Comprehensive stellar population models and the disentangle-ment of age and metallicity efects. ApJS,1994,95:107–149.
[50] Leitherer C., Heckman T. M. Synthetic properties of starburst galaxies.ApJS,1995,96:9–38.
[51] Fioc M., Rocca-Volmerange B. PEGASE: a UV to NIR spectral evolutionmodel of galaxies. Application to the calibration of bright galaxy counts.A&A,1997,326:950–962.
[52] Maraston C. Evolutionary synthesis of stellar populations: a modular tool.MNRAS,1998,300:872–892.
[53] Leitherer C., Schaerer D., Goldader J. D., Gonza′lez Delgado R. M., RobertC., Kune D. F., de Mello D. F., Devost D., et al. Starburst99: SynthesisModels for Galaxies with Active Star Formation. ApJS,1999,123:3–40.
[54] Vazdekis A. Evolutionary Stellar Population Synthesis at2A SpectralResolution. ApJ,1999,513:224–241.
[55] Bruzual G., Charlot S. Stellar population synthesis at the resolution of2003. MNRAS,2003,344:1000–1028.
[56] Maraston C. Evolutionary population synthesis: models, analysis of theingredients and application to high-z galaxies. MNRAS,2005,362:799–825.
[57] Zhang F., Han Z., Li L., Hurley J. R. Inclusion of binaries in evolutionarypopulation synthesis. MNRAS,2005,357:1088–1103.
[58] Bruzual A. G. On TP-AGB stars and the mass of galaxies. Proceedings ofthe International Astronomical Union,2007,2(Symposium S241):125–132.
[59] Benson A. J. Galaxy formation theory. Physics Reports,2010,495:33–86.
[60] Salpeter E. E. The Luminosity Function and Stellar Evolution. ApJ,1955,121:161.
[61] Massey P. The Initial Mass Function of Massive Stars in the Local Group.In G. Gilmore&D. Howell, editor, The Stellar Initial Mass Function (38thHerstmonceux Conference), volume142of Astronomical Society of the Pa-cifc Conference Series, page17,1998.
[62] Kroupa P. On the variation of the initial mass function. MNRAS,2001,322:231–246.
[63] Chabrier G. The Galactic Disk Mass Budget. I. Stellar Mass Function andDensity. ApJ,2001,554:1274–1281.
[64] Corbelli E., Palla F., Zinnecker H., editors. The Initial Mass Function50years later, volume327of Astrophysics and Space Science Library,2005.
[65] Marigo P., Girardi L. Evolution of asymptotic giant branch stars. I. Up-dated synthetic TP-AGB models and their basic calibration. A&A,2007,469:239–263.
[66] Marigo P., Girardi L., Bressan A., Groenewegen M. A. T., Silva L., GranatoG. L. Evolution of asymptotic giant branch stars. II. Optical to far-infraredisochrones with improved TP-AGB models. A&A,2008,482:883–905.
[67] Lejeune T., Schaerer D. Database of Geneva stellar evolution tracks andisochrones for (UBV)J(RI)CJHKLL’M, HST-WFPC2, Geneva and Wash-ington photometric systems. A&A,2001,366:538–546.
[68] Demarque P., Woo J.-H., Kim Y.-C., Yi S. K. Y2Isochrones with an Im-proved Core Overshoot Treatment. ApJS,2004,155:667–674.
[69] Weiss A., Schlattl H. GARSTEC—the Garching Stellar Evolution Code.The direct descendant of the legendary Kippenhahn code. Ap&SS,2008,316:99–106.
[70] Pietrinferni A., Cassisi S., Salaris M., Percival S., Ferguson J. W. A LargeStellar Evolution Database for Population Synthesis Studies. V. StellarModels and Isochrones with CNONa Abundance Anticorrelations. ApJ,2009,697:275–282.
[71] Kurucz R. L. Model Atmospheres for Population Synthesis. In B. Barbuy&A. Renzini, editor, The Stellar Populations of Galaxies, volume149ofIAU Symposium, page225,1992.
[72] Westera P., Lejeune T., Buser R., Cuisinier F., Bruzual G. A standardstellar library for evolutionary synthesis. III. Metallicity calibration. A&A,2002,381:524–538.
[73] Smith L. J., Norris R. P. F., Crowther P. A. Realistic ionizing fuxes foryoung stellar populations from0.05to2Zsolar. MNRAS,2002,337:1309–1328.
[74] Coelho P., Barbuy B., Mel′endez J., Schiavon R. P., Castilho B. V. A libraryof high resolution synthetic stellar spectra from300nm to1.8μm withsolar and α-enhanced composition. A&A,2005,443:735–746.
[75] Martins L. P., Gonza′lez Delgado R. M., Leitherer C., Cervin o M.,Hauschildt P. A high-resolution stellar library for evolutionary populationsynthesis. MNRAS,2005,358:49–65.
[76] Lanc on A., Hauschildt P. H., Ladjal D., Mouhcine M. Near-IR spectra ofred supergiants and giants. I. Models with solar and with mixing-inducedsurface abundance ratios. A&A,2007,468:205–220.
[77] Le Borgne J.-F., Bruzual G., Pello′R., Lanc on A., Rocca-Volmerange B.,Sanahuja B., Schaerer D., Soubiran C., et al. STELIB: A library of stellarspectra at R2000. A&A,2003,402:433–442.
[78] Sa′nchez-Bla′zquez P., Peletier R. F., Jim′enez-Vicente J., Cardiel N., CenarroA. J., Falc′on-Barroso J., Gorgas J., Selam S., et al. Medium-resolution IsaacNewton Telescope library of empirical spectra. MNRAS,2006,371:703–718.
[79] Cenarro A. J., Peletier R. F., Sa′nchez-Bla′zquez P., Selam S. O., Toloba E.,Cardiel N., Falc′on-Barroso J., Gorgas J., et al. Medium-resolution IsaacNewton Telescope library of empirical spectra-II. The stellar atmosphericparameters. MNRAS,2007,374:664–690.
[80] Valdes F., Gupta R., Rose J. A., Singh H. P., Bell D. J. The Indo-US Libraryof Coud′e Feed Stellar Spectra. ApJS,2004,152:251–259.
[81] Prugniel P., Soubiran C. A database of high and medium-resolution stellarspectra. A&A,2001,369:1048–1057.
[82] Prugniel P., Soubiran C., Koleva M., Le Borgne D. New release of theELODIE library: Version3.1. ArXiv Astrophysics e-prints,2007.
[83] Gregg M. D., Silva D., Rayner J., Valdes F., Worthey G., Pickles A., Rose J.A., Vacca W., et al. The HST/STIS Next Generation Spectral Library. InAmerican Astronomical Society Meeting Abstracts, volume36of Bulletinof the American Astronomical Society, page1496,2004.
[84] Coelho P. Spectral libraries and their uncertainties. In G. Giobbi, A.Tornambe, G. Raimondo, M. Limongi, L. A. Antonelli, N. Menci,&E.Brocato, editor, American Institute of Physics Conference Series, volume1111of American Institute of Physics Conference Series, pages67–74,2009.
[85] Kurucz R. L. Including all the lines. Memorie della Societa AstronomicaItaliana Supplementi,2005,8:86.
[86] Walcher C. J., Coelho P., Gallazzi A., Charlot S. Diferential stellar pop-ulation models: how to reliably measure [Fe/H] and [α/Fe] in galaxies.MNRAS,2009,398:L44–L48.
[87] Maeder A., Meynet G. Tables of evolutionary star models from0.85to120solar masses with overshooting and mass loss. A&AS,1988,76:411–425.
[88] Prather M. J. The efect of a Brans-Dicke cosmology upon stellar evolutionand the evolution of galaxies. PhD thesis, Yale University., New Haven,CT.,1976.
[89] Bressan A., Granato G. L., Silva L. Modelling intermediate age and oldstellar populations in the Infrared. A&A,1998,332:135–148.
[90] Le Borgne D., Rocca-Volmerange B., Prugniel P., Lan con A., Fioc M.,Soubiran C. Evolutionary synthesis of galaxies at high spectral resolu-tion with the code PEGASE-HR. Metallicity and age tracers. A&A,2004,425:881–897.
[91] Dotter A., Chaboyer B., Ferguson J. W., Lee H.-c., Worthey G., Jevre-movi′c D., Baron E. Stellar Population Models and Individual ElementAbundances. I. Sensitivity of Stellar Evolution Models. ApJ,2007,666:403–412.
[92] Conroy C., Gunn J. E., White M. The Propagation of Uncertainties in Stel-lar Population Synthesis Modeling. I. The Relevance of Uncertain Aspectsof Stellar Evolution and the Initial Mass Function to the Derived PhysicalProperties of Galaxies. ApJ,2009,699:486–506.
[93] Lee H.-c., Worthey G., Dotter A., Chaboyer B., Jevremovi′c D., Baron E.,Briley M. M., Ferguson J. W., et al. Stellar Population Models and Individ-ual Element Abundances. II. Stellar Spectra and Integrated Light Models.ApJ,2009,694:902–923.
[94] Ferland G., Korista K., Verner D., Ferguson J., Kingdon J., Verner E.CLOUDY90: Numerical Simulation of Plasmas and Their Spectra. PASP,1998,110(749):761.
[95] Groves B., Dopita M. A., Sutherland R. S., Kewley L. J., Fischera J., Lei-therer C., Brandl B., van Breugel W. Modeling the Pan-Spectral EnergyDistribution of Starburst Galaxies. IV. The Controlling Parameters of theStarburst SED. ApJS,2008,176:438–456.
[96] Ferland G. J. Quantitative Spectroscopy of Photoionized Clouds. ARA&A,2003,41:517–554.
[97] Cepa J. The Emission-Line Universe. Canary Islands Winter School ofAstrophysics, Cambridge University Press,2009.
[98] Draine B. T. Interstellar Dust Grains. ARA&A,2003,41:241–289.
[99] Mathis J. S., Rumpl W., Nordsieck K. H. The size distribution of interstellargrains. ApJ,1977,217:425–433.
[100] Leger A., Puget J. L. Identifcation of the’unidentifed’ IR emission featuresof interstellar dust? A&A,1984,137:L5–L8.
[101] Jones A. P., Tielens A. G. G. M., Hollenbach D. J. Grain Shattering inShocks: The Interstellar Grain Size Distribution. ApJ,1996,469:740.
[102] Draine B. T., Lee H. M. Optical properties of interstellar graphite andsilicate grains. ApJ,1984,285:89–108.
[103] Calzetti D., Kinney A. L., Storchi-Bergmann T. Dust extinction of thestellar continua in starburst galaxies: The ultraviolet and optical extinctionlaw. ApJ,1994,429:582–601.
[104] Calzetti D. Reddening and Star Formation in Starburst Galaxies. AJ,1997,113:162–184.
[105] Silva L., Granato G. L., Bressan A., Danese L. Modeling the Efects ofDust on Galactic Spectral Energy Distributions from the Ultraviolet to theMillimeter Band. ApJ,1998,509:103–117.
[106] Charlot S., Fall S. M. A Simple Model for the Absorption of Starlight byDust in Galaxies. ApJ,2000,539:718–731.
[107] Andriesse C. D. Far-infrared properties of interstellar grains. A&A,1974,37:257–262.
[108] Agladze N. I., Sievers A. J., Jones S. A., Burlitch J. M., Beckwith S. V.W. Laboratory Results on Millimeter-Wave Absorption in Silicate GrainMaterials at Cryogenic Temperatures. ApJ,1996,462:1026.
[109] Mennella V., Brucato J. R., Colangeli L., Palumbo P., Rotundi A., Busso-letti E. Temperature Dependence of the Absorption Coefcient of CosmicAnalog Grains in the Wavelength Range20Microns to2Millimeters. ApJ,1998,496:1058.
[110] Popescu C. C., Tufs R. J. The percentage of stellar light re-radiated bydust in late-type Virgo Cluster galaxies. MNRAS,2002,335:L41–L44.
[111] Hippelein H., Haas M., Tufs R. J., Lemke D., Stickel M., Klaas U., Vo¨lk H.J. The spiral galaxy M33mapped in the FIR by ISOPHOT. A spatiallyresolved study of the warm and cold dust. A&A,2003,407:137–146.
[112] Sauvage M., Tufs R. J., Popescu C. C. Normal Nearby Galaxies. SSRv,2005,119:313–353.
[113] Dale D. A., Helou G., Contursi A., Silbermann N. A., Kolhatkar S. TheInfrared Spectral Energy Distribution of Normal Star-forming Galaxies.ApJ,2001,549:215–227.
[114] Dale D. A., Helou G. The Infrared Spectral Energy Distribution of Nor-mal Star-forming Galaxies: Calibration at Far-Infrared and SubmillimeterWavelengths. ApJ,2002,576:159–168.
[115] Draine B. T., Li A. Infrared Emission from Interstellar Dust. IV. TheSilicate-Graphite-PAH Model in the Post-Spitzer Era. ApJ,2007,657:810–837.
[116] Devriendt J. E. G., Guiderdoni B., Sadat R. Galaxy modelling. I. Spectralenergy distributions from far-UV to sub-mm wavelengths. A&A,1999,350:381–398.
[117] da Cunha E., Charlot S., Elbaz D. A simple model to interpret the ultra-violet, optical and infrared emission from galaxies. MNRAS,2008,388:1595–1617.
[118] Desert F.-X., Boulanger F., Puget J. L. Interstellar dust models for extinc-tion and emission. A&A,1990,237:215–236.
[119] Noll S., Burgarella D., Giovannoli E., Buat V., Marcillac D., Mun oz-MateosJ. C. Analysis of galaxy spectral energy distributions from far-UV to far-IRwith CIGALE: studying a SINGS test sample. A&A,2009,507:1793–1813.
[120] Efstathiou A., Rowan-Robinson M., Siebenmorgen R. Massive star forma-tion in galaxies: radiative transfer models of the UV to millimetre emissionof starburst galaxies. MNRAS,2000,313:734–744.
[121] Siebenmorgen R., Kru¨gel E. Dust in starburst nuclei and ULIRGs. SEDmodels for observers. A&A,2007,461:445–453.
[122] Granato G. L., Lacey C. G., Silva L., Bressan A., Baugh C. M., Cole S.,Frenk C. S. The Infrared Side of Galaxy Formation. I. The Local Universein the Semianalytical Framework. ApJ,2000,542:710–730.
[123] Tufs R. J., Popescu C. C., Vo¨lk H. J., Kylafs N. D., Dopita M. A. Modellingthe spectral energy distribution of galaxies. III. Attenuation of stellar lightin spiral galaxies. A&A,2004,419:821–835.
[124] Kylafs N. D., Bahcall J. N. Dust distribution in spiral galaxies. ApJ,1987,317:637–645.
[125] Gordon K. D., Misselt K. A., Witt A. N., Clayton G. C. The DIRTY Model.I. Monte Carlo Radiative Transfer through Dust. ApJ,2001,551:269–276.
[126] Misselt K. A., Gordon K. D., Clayton G. C., Wolf M. J. The DIRTY Model.II. Self-consistent Treatment of Dust Heating and Emission in a Three-dimensional Radiative Transfer Code. ApJ,2001,551:277–293.
[127] Chakrabarti S., Whitney B. A. Panchromatic Spectral Energy Distributionsof Dusty Galaxies with RADISHE. I. Predictions for Herschel: CorrelatingColors with Galactic Energy Sources. ApJ,2009,690:1432–1451.
[128] Baes M., Davies J. I., Dejonghe H., Sabatini S., Roberts S., Evans R., LinderS. M., Smith R. M., et al. Radiative transfer in disc galaxies-III. Theobserved kinematics of dusty disc galaxies. MNRAS,2003,343:1081–1094.
[129] Jonsson P. SUNRISE: polychromatic dust radiative transfer in arbitrarygeometries. MNRAS,2006,372:2–20.
[130] Jonsson P., Groves B. A., Cox T. J. High-resolution panchromatic spectralmodels of galaxies including photoionization and dust. MNRAS,2010,403:17–44.
[131] Bianchi S., Ferrara A., Giovanardi C. Monte Carlo Simulations of DustySpiral Galaxies: Extinction and Polarization Properties. ApJ,1996,465:127.
[132] Bianchi S., Davies J. I., Alton P. B. Monte Carlo predictions of far-infraredemission from spiral galaxies. A&A,2000,359:65–81.
[133] Bianchi S. Dust extinction and emission in a clumpy galactic disk. Anapplication of the radiative transfer code TRADING. A&A,2008,490:461–475.
[134] Treister E., Urry C. M., Chatzichristou E., Bauer F., Alexander D. M.,Koekemoer A., Van Duyne J., Brandt W. N., et al. Obscured Active Galac-tic Nuclei and the X-Ray, Optical, and Far-Infrared Number Counts ofActive Galactic Nuclei in the GOODS Fields. ApJ,2004,616(1):123.
[135] Treister E., Urry C. M., Van Duyne J., Dickinson M., Chary R., AlexanderD. M., Bauer F., Natarajan P., et al. Spitzer Number Counts of ActiveGalactic Nuclei in the GOODS Fields. ApJ,2006,640(2):603.
[136] Nenkova M., Sirocky M. M., Ivezi′cZˇ., Elitzur M. AGN Dusty Tori. I.Handling of Clumpy Media. ApJ,2008,685:147–159.
[137] Nenkova M., Sirocky M. M., Nikutta R., Ivezi′cZˇ., Elitzur M. AGN DustyTori. II. Observational Implications of Clumpiness. ApJ,2008,685:160–180.
[138] Ballantyne D. R., Shi Y., Rieke G. H., Donley J. L., Papovich C., Rigby J.R. Does the AGN Unifed Model Evolve with Redshift?: Using the X-RayBackground to Predict the Mid-Infrared Emission of AGNs. ApJ,2006,653:1070–1088.
[139] Tozzi P., Gilli R., Mainieri V., Norman C., Risaliti G., Rosati P., BergeronJ., Borgani S., et al. X-ray spectral properties of active galactic nuclei inthe Chandra Deep Field South. A&A,2006,451(2):457.
[140] Ballantyne D. R., Everett J. E., Murray N. Connecting Galaxy Evolution,Star Formation, and the Cosmic X-Ray Background. ApJ,2006,639(2):740.
[141] Hao L., Strauss M. A., Fan X., Tremonti C. A., Schlegel D. J., Heckman T.M., Kaufmann G., Blanton M. R., et al. Active Galactic Nuclei in the SloanDigital Sky Survey. II. Emission-Line Luminosity Function. AJ,2005,129(4):1795.
[142] Hasinger G. Absorption properties and evolution of active galactic nuclei.A&A,2008,490(3):905.
[143] Baldwin J. A., Phillips M. M., Terlevich R. Classifcation parameters forthe emission-line spectra of extragalactic objects. PASP,1981,93:5.
[144] Kewley L. J., Dopita M. A., Smith H. A. Do Mergers Stop Monsters? InBulletin of the American Astronomical Society, volume33of Bulletin ofthe American Astronomical Society, page1365,2001.
[145] Kaufmann G., Heckman T. M., Tremonti C., Brinchmann J., Charlot S.,White S. D. M., Ridgway S. E., Brinkmann J., et al. The host galaxies ofactive galactic nuclei. MNRAS,2003,346(4):1055.
[146] Kewley L. J., Groves B., Kaufmann G., Heckman T. The host galaxies andclassifcation of active galactic nuclei. MNRAS,2006,372(3):961.
[147] Moran E. C., Filippenko A. V., Chornock R.“Hidden” Seyfert2Galaxiesand the X-Ray Background. ApJ,2002,579(2):L71.
[148] Netzer H., Mainieri V., Rosati P., Trakhtenbrot B. The correlation of narrowline emission and X-ray luminosity in active galactic nuclei. A&A,2006,453(2):525.
[149] Rigby J. R., Rieke G. H., Donley J. L., Alonso-Herrero A., Perez-GonzalezP. G. Why X-Ray-selected Active Galactic Nuclei Appear Optically Dull.ApJ,2006,645(1):115.
[150] Brusa M., Civano F., Comastri A., Miyaji T., Salvato M., Zamorani G.,Cappelluti N., Fiore F., et al. THE XMM-NEWTONWIDE-FIELD SUR-VEY IN THE COSMOS FIELD (XMM-COSMOS): DEMOGRAPHYAND MULTIWAVELENGTH PROPERTIES OF OBSCURED AND UN-OBSCURED LUMINOUS ACTIVE GALACTIC NUCLEI. ApJ,2010,716(1):348.
[151] Risaliti G., Maiolino R., Salvati M. The Distribution of Absorbing ColumnDensities among Seyfert2Galaxies. ApJ,1999,522(1):157.
[152] Matt G., Guainazzi M., Frontera F., Bassani L., Brandt W. N., Fabian A.C., Fiore F., Haardt F., et al. Hard X-ray detection of NGC1068withBeppoSAX. A&A,1997,325:–13.
[153] Stefen A. T., Strateva I., Brandt W. N., Alexander D. M., Koekemoer A. M.,Lehmer B. D., Schneider D. P., Vignali C. The X-Ray-to-Optical Propertiesof Optically Selected Active Galaxies over Wide Luminosity and RedshiftRanges. AJ,2006,131:2826–2842.
[154] Hopkins P. F., Richards G. T., Hernquist L. An Observational Determi-nation of the Bolometric Quasar Luminosity Function. ApJ,2007,654:731–753.
[155] Vagnetti F., Turriziani S., Trevese D., Antonucci M. Variability and theX-ray/UV ratio of active galactic nuclei. A&A,2010,519:A17.
[156] Alonso-Herrero A., Quillen A. C., Simpson C., Efstathiou A., Ward M. J.The Nonstellar Infrared Continuum of Seyfert Galaxies. AJ,2001,121(3):1369.
[157] Krabbe A., Boker T., Maiolino R. N-Band Imaging of Seyfert Nuclei andthe Mid-Infrared–X-Ray Correlation. ApJ,2001,557(2):626.
[158] Lutz D., Maiolino R., Spoon H. W. W., Moorwood A. F. M. The relationbetween AGN hard X-ray emission and mid-infrared continuum from ISOspectra: Scatter and unifcation aspects. A&A,2004,418(2):465.
[159] Horst H., Smette A., Gandhi P., Duschl W. J. The small dispersion of themid IR–hard X-ray correlation in active galactic nuclei. A&A,2006,457(2):L17.
[160] Horst H., Gandhi P., Smette A., Duschl W. J. The mid IR–hard X-raycorrelation in AGN and its implications for dusty torus models. A&A,2008,479(2):389.
[161] Ho¨nig S. F., Kishimoto M., Gandhi P., Smette A., Asmus D., Duschl W.,Polletta M., Weigelt G. The dusty heart of nearby active galaxies I. High-spatial resolution mid-IR spectro-photometry of Seyfert galaxies. A&A,2010,515:A23.
[162] Ho¨nig S. F., Kishimoto M. The dusty heart of nearby active galaxies II.From clumpy torus models to physical properties of dust around AGN.A&A,2010,523:A27.
[163] Gandhi P., Horst H., Smette A., Ho¨nig S., Comastri A., Gilli R., Vignali C.,Duschl W. Resolving the mid-infrared cores of local Seyferts. A&A,2009,502(2):457.
[164] Mullaney J. R., Alexander D. M., Goulding A. D., Hickox R. C. Defningthe intrinsic AGN infrared spectral energy distribution and measuring itscontribution to the infrared output of composite galaxies. MNRAS,2011,414:1082–1110.
[165] Draper A. R., Ballantyne D. R. Properties and Expected Number Countsof Active Galactic Nuclei and Their Hosts in the Far-infrared. ApJ,2011,729(2):109.
[166] Hopkins P. F., Hernquist L., Cox T. J., Robertson B., Krause E. An Ob-served Fundamental Plane Relation for Supermassive Black Holes. ApJ,2007,669:67–73.
[167] Kormendy J., Bender R. Correlations between Supermassive Black Holes,Velocity Dispersions, and Mass Defcits in Elliptical Galaxies with Cores.ApJL,2009,691:L142–L146.
[168] Gu¨ltekin K., Richstone D. O., Gebhardt K., Lauer T. R., Tremaine S., AllerM. C., Bender R., Dressler A., et al. The M-σ and M-L Relations in GalacticBulges, and Determinations of Their Intrinsic Scatter. ApJ,2009,698:198–221.
[169] Merloni A., Bongiorno A., Bolzonella M., Brusa M., Civano F., Comastri A.,Elvis M., Fiore F., et al. On the Cosmic Evolution of the Scaling RelationsBetween Black Holes and Their Host Galaxies: Broad-Line Active GalacticNuclei in the zCOSMOS Survey. ApJ,2010,708:137–157.
[170] Ferrarese L., Merritt D. A Fundamental Relation between SupermassiveBlack Holes and Their Host Galaxies. ApJ,2000,539(1):L9.
[171] Gebhardt K., Bender R., Bower G., Dressler A., Faber S. M., Filippenko A.V., Green R., Grillmair C., et al. A Relationship between Nuclear BlackHole Mass and Galaxy Velocity Dispersion. ApJ,2000,539(1):L13.
[172] Tremaine S., Gebhardt K., Bender R., Bower G., Dressler A., Faber S. M.,Filippenko A. V., Green R., et al. The Slope of the Black Hole Mass versusVelocity Dispersion Correlation. ApJ,2002,574:740–753.
[173] Magorrian J., Tremaine S., Richstone D., Bender R., Bower G., Dressler A.,Faber S. M., Gebhardt K., et al. The Demography of Massive Dark Objectsin Galaxy Centers. AJ,1998,115(6):2285.
[174] Ha¨ring N., Rix H.-W. On the Black Hole Mass-Bulge Mass Relation. ApJL,2004,604:L89–L92.
[175] Graham A. W. Core Depletion from Coalescing Supermassive Black Holes.ApJL,2004,613:L33–L36.
[176] Kormendy J., Richstone D. Inward Bound–The Search for SupermassiveBlack Holes in Galactic Nuclei. ARA&A,1995,33(1):581.
[177] Marconi A., Hunt L. K. The Relation between Black Hole Mass, BulgeMass, and Near-Infrared Luminosity. ApJ,2003,589(1):L21.
[178] Hopkins A. M. On the Evolution of Star-forming Galaxies. ApJ,2004,615(1):209.
[179] Silverman J. D., Green P. J., Barkhouse W. A., Kim D. W., Kim M., WilkesB. J., Cameron R. A., Hasinger G., et al. The Luminosity Function ofX-Ray-selected Active Galactic Nuclei: Evolution of Supermassive BlackHoles at High Redshift. ApJ,2008,679:118–139.
[180] Aird J., Nandra K., Laird E. S., Georgakakis A., Ashby M. L. N., BarmbyP., Coil A. L., Huang J.-S., et al. The evolution of the hard X-ray luminosityfunction of AGN. MNRAS,2010,401(4):2531.
[181] Yu Q., Tremaine S. Observational constraints on growth of massive blackholes. MNRAS,2002,335:965–976.
[182] Marconi A., Risaliti G., Gilli R., Hunt L. K., Maiolino R., Salvati M. Lo-cal supermassive black holes, relics of active galactic nuclei and the X-raybackground. MNRAS,2004,351(1):169.
[183] Merloni A. The anti-hierarchical growth of supermassive black holes. MN-RAS,2004,353:1035–1047.
[184] Yu Q., Lu Y. Toward Precise Constraints on the Growth of Massive BlackHoles. ApJ,2008,689:732–754.
[185] Croton D. J., Springel V., White S. D. M., De Lucia G., Frenk C. S., GaoL., Jenkins A., Kaufmann G., et al. The many lives of active galactic nu-clei: cooling fows, black holes and the luminosities and colours of galaxies.MNRAS,2006,365(1):11.
[186] Bower R. G., Benson A. J., Malbon R., Helly J. C., Frenk C. S., BaughC. M., Cole S., Lacey C. G. Breaking the hierarchy of galaxy formation.MNRAS,2006,370(0):645–655.
[187] Di Matteo T., Springel V., Hernquist L. Energy input from quasars regu-lates the growth and activity of black holes and their host galaxies. Nature,2005,433:604–607.
[188] Di Matteo T., Colberg J., Springel V., Hernquist L., Sijacki D. Direct Cos-mological Simulations of the Growth of Black Holes and Galaxies. ApJ,2008,676(1):33.
[189] Hopkins P. F., Hernquist L., Cox T. J., Di Matteo T., Martini P., RobertsonB., Springel V. Black Holes in Galaxy Mergers: Evolution of Quasars. ApJ,2005,630(2):705.
[190] Hopkins P. F., Somerville R. S., Hernquist L., Cox T. J., Robertson B., Li Y.The Relation between Quasar and Merging Galaxy Luminosity Functionsand the Merger-driven Star Formation History of the Universe. ApJ,2006,652:864–888.
[191] Hopkins P. F., Hernquist L., Cox T. J., Keres D. A Cosmological Frameworkfor the Co-Evolution of Quasars, Supermassive Black Holes, and EllipticalGalaxies: I. Galaxy Mergers&Quasar Activity. ApJ,2008,175:356.
[192] Nagar N. M., Falcke H., Wilson A. S. Radio sources in low-luminosity activegalactic nuclei. A&A,2005,435(2):521.
[193] Babbedge T. S. R., Rowan-Robinson M., Vaccari M., Surace J. A., LonsdaleC. J., Clements D. L., Fang F., Farrah D., et al. Luminosity functions forgalaxies and quasars in the Spitzer Wide-area Infrared Extragalactic LegacySurvey. MNRAS,2006,370(3):1159.
[194] Brown M. J. I., Brand K., Dey A., Jannuzi B. T., Cool R., Le Floc’h E.,Kochanek C. S., Armus L., et al. The1
[196] Fan X., Strauss M. A., Schneider D. P., Gunn J. E., Lupton R. H., BeckerR. H., Davis M., Newman J. A., et al. High-Redshift Quasars Found inSloan Digital Sky Survey Commissioning Data. IV. Luminosity Functionfrom the Fall Equatorial Stripe Sample. AJ,2001,121(1):54.
[197] Wolf C., Wisotzki L., Borch A., Dye S., Kleinheinrich M., Meisenheimer K.The evolution of faint AGN between z=1and z=5from the COMBO-17survey. A&A,2003,408:499–514.
[198] Croom S. M., Smith R. J., Boyle B. J., Shanks T., Miller L., Outram P.J., Loaring N. S. The2dF QSO Redshift Survey-XII. The spectroscopiccatalogue and luminosity function. MNRAS,2004,349:1397–1418.
[199] Richards G. T., Strauss M. A., Fan X., Hall P. B., Jester S., Schneider D.P., Vanden Berk D. E., Stoughton C., et al. The Sloan Digital Sky SurveyQuasar Survey: Quasar Luminosity Function from Data Release3. AJ,2006,131:2766–2787.
[200] Bongiorno A., Zamorani G., Gavignaud I., Marano. The VVDS type-1AGNsample: the faint end of the luminosity function. A&A,2007,472:443–454.
[201] Fontanot F., Cristiani S., Monaco P., Nonino M., Vanzella E., Brandt W. N.,Grazian A., Mao J. The luminosity function of high-redshift quasi-stellarobjects. A combined analysis of GOODS and SDSS. A&A,2007,461(1):39.
[202] Shankar F., Mathur S. On the Faint End of the High-Redshift ActiveGalactic Nucleus Luminosity Function. ApJ,2007,660(2):1051.
[203] Miyaji T., Hasinger G., Schmidt M. Soft X-ray AGN luminosity functionfrom it ROSAT surveys. I. Cosmological evolution and contribution to thesoft X-ray background. A&A,2000,353:25–40.
[204] Miyaji T., Hasinger G., Schmidt M. Soft X-ray AGN luminosity functionfrom ROSAT surveys. A&A,2001,369(1):49.
[205] Silverman J. D., Green P. J., Barkhouse W. A., Cameron R. A., Foltz C.,Jannuzi B. T., Kim D.-W., Kim M., et al. Comoving Space Density ofX-Ray-selected Active Galactic Nuclei. ApJ,2005,624:630–637.
[206] Hasinger G., Miyaji T., Schmidt M. Luminosity-dependent evolution ofsoft X-ray selected AGN. New Chandra and XMM-Newton surveys. A&A,2005,441:417–434.
[207] Ueda Y., Akiyama M., Ohta K., Miyaji T. Cosmological Evolution of theHard X-Ray Active Galactic Nucleus Luminosity Function and the Originof the Hard X-Ray Background. ApJ,2003,598(2):886.
[208] La Franca F., Fiore F., Comastri A., Perola G. C., Sacchi N., Brusa M.,Cocchia F., Feruglio C., et al. The HELLAS2XMM Survey. VII. The HardX-Ray Luminosity Function of AGNs up to z=4: More Absorbed AGNsat Low Luminosities and High Redshifts. ApJ,2005,635:864–879.
[209] Silverman J. D., Green P. J., Barkhouse W. A., Kim D.-W., Aldcroft T.L., Cameron R. A., Wilkes B. J., Mossman A., et al. Hard X-Ray-emittingActive Galactic Nuclei Selected by the Chandra Multiwavelength Project.ApJ,2005,618:123–138.
[210] Yencho B., Barger A. J., Trouille L., Winter L. M. The OPTX Project. II.Hard X-Ray Luminosity Functions of Active Galactic Nuclei for z lsim5.ApJ,2009,698:380–396.
[211] Ebrero J., Carrera F. J., Page M. J., Silverman J. D., Barcons X., CeballosM. T., Corral A., Della Ceca R., et al. The XMM-Newton serendipitoussurvey. VI. The X-ray luminosity function. A&A,2009,493:55–69.
[212] Barger A. J., Cowie L. L., Mushotzky R. F., Yang Y., Wang W.-H., StefenA. T., Capak P. The Cosmic Evolution of Hard X-Ray-selected ActiveGalactic Nuclei. AJ,2005,129(2):578.
[213] Cirasuolo M., Magliocchetti M., Celotti A. Faint radio-loud quasars: cluesto their evolution. MNRAS,2005,357:1267–1280.
[214] Barcons X., Carrera F. J., Ceballos M. T., Page M. J., Bussons-Gordo J.,Corral A., Ebrero J., Mateos S., et al. The XMM-Newton serendipitoussurvey. A&A,2007,476(3):1191.
[215] Fu H., Yan L., Scoville N. Z., Capak P., Aussel H., Floc’h E. L., IlbertO., Salvato M., et al. Decomposing Star Formation and Active GalacticNucleus with Spitzer Mid-infrared Spectra: Luminosity Functions and Co-evolution. ApJ,2010,722(1):653.
[216] Hopkins P. F., Younger J. D., Hayward C. C., Narayanan D., HernquistL. Mergers, active galactic nuclei and ‘normal’ galaxies: contributions tothe distribution of star formation rates and infrared luminosity functions.MNRAS,2010,402(3):1693–1713.
[217] Netzer H., Lutz D., Schweitzer M., Contursi A., Sturm E., Tacconi L.J., Veilleux S., Kim D., et al. Spitzer Quasar and ULIRG EvolutionStudy (QUEST). II. The Spectral Energy Distributions of Palomar-GreenQuasars. ApJ,2007,666(2):806.
[218] Nenkova M., Ivezi′cZˇ., Elitzur M. Dust Emission from Active GalacticNuclei. ApJ,2002,570(1):L9.
[219] Ho¨nig S. F., Beckert T., Ohnaka K., Weigelt G. Radiative transfer modelingof three-dimensional clumpy AGN tori and its application to NGC1068.A&A,2006,452:459–471.
[220] Canalizo G., Stockton A. Quasi-Stellar Objects, Ultraluminous InfraredGalaxies, and Mergers. ApJ,2001,555(2):719.
[221] Hutchings J. B. What is the diference between radio galaxies and radioquasar galaxies? ApJ,1987,320:122.
[222] Disney M. J., Boyce P. J., Blades J. C., Boksenberg A., Crane P., DeharvengJ. M., Macchetto F., Mackay C. D., et al. Interacting elliptical galaxies ashosts of intermediate-redshift quasars. Nat,1995,376(6536):150.
[223] Bahcall J. N., Kirhakos S., Saxe D. H., Schneider D. P. Hubble Space Tele-scopeImages of a Sample of20Nearby Luminous Quasars. ApJ,1997,479(2):642.
[224] Kirhakos S., Bahcall J. N., Schneider D. P., Kristian J. The Host Galaxiesof Three Radio-loud Quasars:3C48,3C345, and B21425+267. ApJ,1999,520(1):67.
[225] Laurikainen E., Salo H. Environments of Seyfert galaxies. II. Statisticalanalyses. A&A,1995,293:683–702.
[226] Schmitt H. R. The Frequency of Active and Quiescent Galaxies with Com-panions: Implications for the Feeding of the Nucleus. AJ,2001,122(5):2243.
[227] Grogin N. A., Conselice C. J., Chatzichristou E., Alexander D. M., BauerF. E., Hornschemeier A. E., Jogee S., Koekemoer A. M., et al. AGN HostGalaxies atz0.4-1.3: Bulge-dominated and Lacking Merger-AGN Connec-tion. ApJ,2005,627(2):L97.
[228] Ben′tez N. Bayesian Photometric Redshift Estimation. ApJ,2000,536:571–583.
[229] Kaufmann G., Heckman T. M., White S. D. M., Charlot S., Tremonti C.,Brinchmann J., Bruzual G., Peng E. W., et al. Stellar masses and starformation histories for105galaxies from the Sloan Digital Sky Survey.MNRAS,2003,341:33–53.
[230] Feldmann R., Carollo C. M., Porciani C., Lilly S. J., Capak P., Taniguchi Y.,Le F`evre O., Renzini A., et al. The Zurich Extragalactic Bayesian RedshiftAnalyzer and its frst application: COSMOS. MNRAS,2006,372:565–577.
[231] Salim S., Rich R. M., Charlot S., Brinchmann J., Johnson B. D., Schimi-novich D., Seibert M., Mallery R., et al. UV Star Formation Rates in theLocal Universe. ApJS,2007,173:267–292.
[232] Bailer-Jones C. A. L. Bayesian inference of stellar parameters and interstel-lar extinction using parallaxes and multiband photometry. MNRAS,2011,411:435–452.
[233] Lahav O., Naim A., Sodr′e Jr. L., Storrie-Lombardi M. C. Neural computa-tion as a tool for galaxy classifcation: methods and examples. MNRAS,1996,283:207–+.
[234] Bertin E., Arnouts S. SExtractor: Software for source extraction. A&AS,1996,117:393–404.
[235] Andreon S., Gargiulo G., Longo G., Tagliaferri R., Capuano N. Widefeld imaging-I. Applications of neural networks to object detection andstar/galaxy classifcation. MNRAS,2000,319:700–716.
[236] Firth A. E., Lahav O., Somerville R. S. Estimating photometric redshiftswith artifcial neural networks. MNRAS,2003,339:1195–1202.
[237] Collister A. A., Lahav O. ANNz: Estimating Photometric Redshifts UsingArtifcial Neural Networks. PASP,2004,116:345–351.
[238] Vanzella E., Cristiani S., Fontana A., Nonino M., Arnouts S., Giallongo E.,Grazian A., Fasano G., et al. Photometric redshifts with the MultilayerPerceptron Neural Network: Application to the HDF-S and SDSS. A&A,2004,423:761–776.
[239] Carballo R., Gonza′lez-Serrano J. I., Benn C. R., Jim′enez-Luja′n F. Use ofneural networks for the identifcation of new z>=3.6QSOs from FIRST-SDSS DR5. MNRAS,2008,391:369–382.
[240] Auld T., Bridges M., Hobson M. P. COSMONET: fast cosmological param-eter estimation in non-fat models using neural networks. MNRAS,2008,387:1575–1582.
[241] Francis P. J., Hewett P. C., Foltz C. B., Chafee F. H. An objective classif-cation scheme for QSO spectra. ApJ,1992,398:476–490.
[242] Glazebrook K., Ofer A. R., Deeley K. Automatic Redshift Determinationby Use of Principal Component Analysis. I. Fundamentals. ApJ,1998,492:98–+.
[243] Wild V., Hewett P. C. Peering through the OH forest: a new techniqueto remove residual sky features from Sloan Digital Sky Survey spectra.MNRAS,2005,358:1083–1099.
[244] Wild V., Kaufmann G., Heckman T., Charlot S., Lemson G., BrinchmannJ., Reichard T., Pasquali A. Bursty stellar populations and obscured activegalactic nuclei in galaxy bulges. MNRAS,2007,381:543–572.
[245] Budava′ri T., Wild V., Szalay A. S., Dobos L., Yip C.-W. Reliable eigen-spectra for new generation surveys. MNRAS,2009,394:1496–1502.
[246] Asensio Ramos A., Ramos Almeida C. Bayesclumpy: Bayesian Inferencewith Clumpy Dusty Torus Models. ApJ,2009,696:2075–2085.
[247] Almeida C., Baugh C. M., Lacey C. G., Frenk C. S., Granato G. L., SilvaL., Bressan A. Modelling the dusty universe-I. Introducing the artifcialneural network and frst applications to luminosity and colour distributions.MNRAS,2010,402:544–564.
[248] Silva L., Schurer A., Granato G. L., Almeida C., Baugh C. M., Frenk C. S.,Lacey C. G., Paoletti L., et al. Modelling the spectral energy distributionof galaxies: introducing the artifcial neural network. MNRAS,2011,410:2043–2056.
[249] White S. D. M., Rees M. J. Core condensation in heavy halos-A two-stagetheory for galaxy formation and clustering. MNRAS,1978,183:341–358.
[250] Lacey C., Silk J. Tidally triggered galaxy formation. I-Evolution of thegalaxy luminosity function. ApJ,1991,381:14–32.
[251] White S. D. M., Frenk C. S. Galaxy formation through hierarchical cluster-ing. ApJ,1991,379:52–79.
[252] Ghosh J. K., Delampady M., Samanta T. An Introduction to BayesianAnalysis: Theory and Methods (Springer Texts in Statistics).1. Springer,2006.
[253] Trotta R. Bayes in the sky: Bayesian inference and model selection incosmology. Contemporary Physics,2008,49:71–104.
[254] Lyons L. A Particle Physicist’s Perspective on Astrostatistics. In G. J. Babu&E. D. Feigelson, editor, Statistical Challenges in Modern Astronomy IV,volume371of Astronomical Society of the Pacifc Conference Series, page361,2007.
[255] Jaynes E. T. Probability Theory: The Logic of Science. UK: CambridgeUniversity Press,2003.
[256] Ruiz de Austri R., Trotta R., Roszkowski L. A Markov chain Monte Carloanalysis of the CMSSM. Journal of High Energy Physics,2006,5:2.
[257] Trotta R., de Austri R. R., Roszkowski L. Prospects for direct dark matterdetection in the constrained MSSM. NewAR,2007,51:316–320.
[258] Roszkowski L., Ruiz de Austri R., Trotta R. On the detectability of theCMSSM light Higgs boson at the Tevatron. Journal of High Energy Physics,2007,4:84.
[259] Roszkowski L., Ruiz de Austri R., Trotta R. Implications for the Con-strained MSSM from a new prediction for b→sγ. Journal of High EnergyPhysics,2007,7:75.
[260] Trotta R., Feroz F., Hobson M., Roszkowski L., Ruiz de Austri R. Theimpact of priors and observables on parameter inferences in the constrainedMSSM. Journal of High Energy Physics,2008,12:24.
[261] Trotta R., Ruiz de Austri R., P′erez de los Heros C. Prospects for darkmatter detection with IceCube in the context of the CMSSM. JCAP,2009,8:34.
[262] Feroz F., Hobson M. P., Bridges M. MULTINEST: an efcient and robustBayesian inference tool for cosmology and particle physics. MNRAS,2009,398:1601–1614.
[263] Feroz F., Cranmer K., Hobson M., Ruiz de Austri R., Trotta R. Challengesof profle likelihood evaluation in multi-dimensional SUSY scans. Journalof High Energy Physics,2011,6:42.
[264] Gregory P. Bayesian Logical Data Analysis for the Physical Sciences. NewYork, NY, USA: Cambridge University Press,2005.
[265] Press W. H., Teukolsky S. A., Vetterling W. T., Flannery B. P. NumericalRecipes3rd Edition: The Art of Scientifc Computing.3. CambridgeUniversity Press,2007.
[266] Hobson M. P., McLachlan C. A Bayesian approach to discrete object de-tection in astronomical data sets. MNRAS,2003,338:765–784.
[267] Marshall P. J., Hobson M. P., Slosar A. Bayesian joint analysis of clusterweak lensing and Sunyaev-Zel’dovich efect data. MNRAS,2003,346:489–500.
[268] Slosar A., Carreira P., Cleary K., Davies R. D., Davis R. J., Dickinson C.,Genova-Santos R., Grainge K., et al. Cosmological parameter estimationand Bayesian model comparison using Very Small Array data. MNRAS,2003,341:L29–L34.
[269] Bassett B. A., Corasaniti P. S., Kunz M. The Essence of Quintessence andthe Cost of Compression. ApJL,2004,617:L1–L4.
[270] Niarchou A., Jafe A. H., Pogosian L. Large-scale power in the CMB andnew physics: An analysis using Bayesian model comparison. PhRvD,2004,69(6):063515.
[271] Beltra′n M., Garc′a-Bellido J., Lesgourgues J., Liddle A. R., Slosar A.Bayesian model selection and isocurvature perturbations. PhRvD,2005,71(6):063532.
[272] Bridges M., Lasenby A. N., Hobson M. P. A Bayesian analysis of the pri-mordial power spectrum. MNRAS,2006,369:1123–1130.
[273] Trotta R. Applications of Bayesian model selection to cosmological param-eters. MNRAS,2007,378:72–82.
[274] Skilling J. Nested Sampling. In R. Fischer, R. Preuss,&U. V. Toussaint,editor, American Institute of Physics Conference Series, volume735ofAmerican Institute of Physics Conference Series, pages395–405,2004.
[275] Mukherjee P., Parkinson D., Liddle A. R. A Nested Sampling Algorithmfor Cosmological Model Selection. ApJL,2006,638:L51–L54.
[276] Shaw J. R., Bridges M., Hobson M. P. Efcient Bayesian inference for mul-timodal problems in cosmology. MNRAS,2007,378:1365–1370.
[277] Feroz F., Hobson M. P. Multimodal nested sampling: an efcient and robustalternative to Markov Chain Monte Carlo methods for astronomical dataanalyses. MNRAS,2008,384:449–463.
[278] Cybenko G. Approximation by superpositions of a sigmoidal function.Mathematics of Control, Signals, and Systems (MCSS),1989,2:303–314,10.1007/BF02551274.
[279] Hornik K. Approximation capabilities of multilayer feedforward networks.Neural Networks,1991,4(2):251–257.
[280] Haykin S. Neural Networks: A Comprehensive Foundation. Upper SaddleRiver, NJ: Prentice Hall,1999.
[281] Ruiz A., Carrera F. J., Panessa F. An XMM-
[282] Rowan-Robinson M. Hyperluminous infrared galaxies. MNRAS,2000,316:885–900.
[283] Ruiz A., Miniutti G., Panessa F., Carrera F. J. Spectral energy distributionof hyperluminous infrared galaxies. A&A,2010,515:A99+.
[284] Cole S., Lacey C. G., Baugh C. M., Frenk C. S. Hierarchical galaxy forma-tion. MNRAS,2000,319:168–204.
[285] Kaufmann G., Haehnelt M. A unifed model for the evolution of galaxiesand quasars. MNRAS,2000,311:576–588.
[286] Hatton S., Devriendt J. E. G., Ninin S., Bouchet F. R., Guiderdoni B., Vib-ert D. GALICS-I. A hybrid N-body/semi-analytic model of hierarchicalgalaxy formation. MNRAS,2003,343:75–106.
[287] De Lucia G., Kaufmann G., White S. D. M. Chemical enrichment of theintracluster and intergalactic medium in a hierarchical galaxy formationmodel. MNRAS,2004,349:1101–1116.
[288] Somerville R. S., Hopkins P. F., Cox T. J., Robertson B. E., Hernquist L. Asemi-analytic model for the co-evolution of galaxies, black holes and activegalactic nuclei. MNRAS,2008,391:481–506.
[289] De Lucia G., Boylan-Kolchin M., Benson A. J., Fontanot F., Monaco P. Asemi-analytic model comparison-gas cooling and galaxy mergers. MNRAS,2010,406:1533–1552.
[290] Benson A. J. GALACTICUS: A semi-analytic model of galaxy formation.NewA,2012,17:175–197.
[291] Han Y., Han Z. Decoding Spectral Energy Distributions of Dust-obscuredStarburst-Active Galactic Nucleus. ApJ,2012,749:123.
[292] Han Y., Dai B., Wang B., Zhang F., Han Z. Evolution of luminosity functionand obscuration of AGN: connecting X-ray and Infrared. MNRAS,2012,accepted.
[293] Wang B., Liu Z., Han Y., Lei Z., Luo Y., Han Z. Birthrates and delay timesof Type Ia supernovae. Science in China G: Physics and Astronomy,2010,53:586–590.
[294] Jarosik N., Bennett C. L., Dunkley J., Gold B., Greason M. R., Halpern M.,Hill R. S., Hinshaw G., et al. Seven-year Wilkinson Microwave AnisotropyProbe (WMAP) Observations: Sky Maps, Systematic Errors, and BasicResults. ApJS,2011,192:14.