Building robust active galactic nuclei mock catalogs to unveil black hole evolution and for survey planning
Building robust active galactic nuclei mock catalogs to unveil black hole evolution and for survey planning
 
  The statistical distributions of active galactic nuclei (AGNs), i.e., accreting supermassive black holes (BHs), in mass, space, and time are controlled by a series of key properties, namely, the BH–galaxy scaling relations, Eddington ratio distributions, and fraction of active BH (duty cycle). Shedding light on these properties yields strong constraints on the AGN triggering mechanisms while providing a clear baseline to create useful mock catalogs for the planning of large galaxy surveys. Here we delineate a robust methodology to create mock AGN catalogs built on top of large N-body dark matter simulations via state-of-the-art semiempirical models. We show that by using as independent tests the AGN clustering at fixed X-ray luminosity, galaxy stellar mass, and BH mass, along with the fraction of AGNs in groups and clusters, it is possible to significantly narrow down the choice in the relation between BH mass and host galaxy stellar mass, the duty cycle, and the average Eddington ratio distribution, delivering well-suited constraints to guide cosmological models for the coevolution of BHs and galaxies. Avoiding such a step-by-step methodology inevitably leads to strong degeneracies in the final mock catalogs, severely limiting their usefulness in understanding AGN evolution and in survey planning and testing.
  
  
  
    
      Allevato, V.
      
        8be704a6-2a3f-4e44-b9c3-c00991e45927
      
     
  
    
      Shankar, F.
      
        b10c91e4-85cd-4394-a18a-d4f049fd9cdb
      
     
  
    
      Marsden, C.
      
        9666abab-9536-4c32-b6d8-d85777e1045f
      
     
  
    
      Rasulov, U.
      
        83072efc-986c-4231-bbf6-720ff53358d3
      
     
  
    
      Viitanen, A.
      
        cb56f30c-e8d3-49b7-978b-0fac8dfc49d9
      
     
  
    
      Georgakakis, A.
      
        af2a2453-2c1c-427b-a26f-07e40bf1d795
      
     
  
    
      Ferrara, A.
      
        cb79de3b-1626-43ee-9cea-ea30c33ee9a5
      
     
  
    
      Finoguenov, A.
      
        dc4f9f99-e243-45e0-8de2-bb38530ad737
      
     
  
  
   
  
  
    
    
  
    
    
  
  
    
      Allevato, V.
      
        8be704a6-2a3f-4e44-b9c3-c00991e45927
      
     
  
    
      Shankar, F.
      
        b10c91e4-85cd-4394-a18a-d4f049fd9cdb
      
     
  
    
      Marsden, C.
      
        9666abab-9536-4c32-b6d8-d85777e1045f
      
     
  
    
      Rasulov, U.
      
        83072efc-986c-4231-bbf6-720ff53358d3
      
     
  
    
      Viitanen, A.
      
        cb56f30c-e8d3-49b7-978b-0fac8dfc49d9
      
     
  
    
      Georgakakis, A.
      
        af2a2453-2c1c-427b-a26f-07e40bf1d795
      
     
  
    
      Ferrara, A.
      
        cb79de3b-1626-43ee-9cea-ea30c33ee9a5
      
     
  
    
      Finoguenov, A.
      
        dc4f9f99-e243-45e0-8de2-bb38530ad737
      
     
  
       
    
 
  
    
      
  
  
  
  
  
  
    Allevato, V., Shankar, F., Marsden, C., Rasulov, U., Viitanen, A., Georgakakis, A., Ferrara, A. and Finoguenov, A.
  
  
  
  
   
    (2021)
  
  
    
    Building robust active galactic nuclei mock catalogs to unveil black hole evolution and for survey planning.
  
  
  
  
    Astrophysical Journal.
  
   (doi:10.3847/1538-4357/abfe59/meta). 
  
  
   
  
  
  
  
  
   
  
    
    
      
        
          Abstract
          The statistical distributions of active galactic nuclei (AGNs), i.e., accreting supermassive black holes (BHs), in mass, space, and time are controlled by a series of key properties, namely, the BH–galaxy scaling relations, Eddington ratio distributions, and fraction of active BH (duty cycle). Shedding light on these properties yields strong constraints on the AGN triggering mechanisms while providing a clear baseline to create useful mock catalogs for the planning of large galaxy surveys. Here we delineate a robust methodology to create mock AGN catalogs built on top of large N-body dark matter simulations via state-of-the-art semiempirical models. We show that by using as independent tests the AGN clustering at fixed X-ray luminosity, galaxy stellar mass, and BH mass, along with the fraction of AGNs in groups and clusters, it is possible to significantly narrow down the choice in the relation between BH mass and host galaxy stellar mass, the duty cycle, and the average Eddington ratio distribution, delivering well-suited constraints to guide cosmological models for the coevolution of BHs and galaxies. Avoiding such a step-by-step methodology inevitably leads to strong degeneracies in the final mock catalogs, severely limiting their usefulness in understanding AGN evolution and in survey planning and testing.
         
      
      
        
          
            
  
    Text
 Building Robust Active Galactic Nuclei Mock Catalogs to Unveil Black Hole Evolution and for Survey Planning
     - Accepted Manuscript
   
  
  
    
  
 
          
            
          
            
           
            
           
        
        
       
    
   
  
  
  More information
  
    
      Accepted/In Press date: 4 May 2021
 
    
      e-pub ahead of print date: 22 July 2021
 
    
  
  
    
  
    
     
        Additional Information:
        arxiv is am
      
    
  
    
  
    
  
    
  
    
  
    
  
    
  
  
  
    
  
  
        Identifiers
        Local EPrints ID: 451004
        URI: http://eprints.soton.ac.uk/id/eprint/451004
        
          
        
        
        
          ISSN: 0004-637X
        
        
          PURE UUID: cc5447a2-c0ea-488a-b1a0-83dff3bc7fe1
        
  
    
        
          
        
    
        
          
            
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
  
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  Date deposited: 01 Sep 2021 16:31
  Last modified: 17 Mar 2024 06:47
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      Contributors
      
          
          Author:
          
            
            
              V. Allevato
            
          
        
      
        
      
          
          Author:
          
            
            
              C. Marsden
            
          
        
      
          
          Author:
          
            
            
              U. Rasulov
            
          
        
      
          
          Author:
          
            
            
              A. Viitanen
            
          
        
      
          
          Author:
          
            
            
              A. Georgakakis
            
          
        
      
          
          Author:
          
            
            
              A. Ferrara
            
          
        
      
          
          Author:
          
            
            
              A. Finoguenov
            
          
        
      
      
      
    
  
   
  
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