Cosmology with AGN dust time lags–simulating the new VEILS survey
Cosmology with AGN dust time lags–simulating the new VEILS survey
 
  The time lag between optical and near-infrared continuum emission in active galactic nuclei (AGN) shows a tight correlation with luminosity and has been proposed as a standardizable candle for cosmology. In this paper, we explore the use of these AGN hot-dust time lags for cosmological model fitting under the constraints of the new VISTA Extragalactic Infrared Legacy Survey (VEILS). This new survey will target a 9 deg2 field observed in J and Ks band with a 14-d cadence and will run for 3 yr. The same area will be covered simultaneously in the optical griz bands by the Dark Energy Survey, providing complementary time-domain optical data. We perform realistic simulations of the survey setup, showing that we expect to recover dust time lags for about 450 objects out of a total of 1350 optical type 1 AGN, spanning a redshift range of 0.1 < z < 1.2. We use the lags recovered from our simulations to calculate precise distance moduli, establish a Hubble diagram, and fit cosmological models. Assuming realistic scatter in the distribution of the dust around the AGN as well as in the normalization of the lag–luminosity relation, we are able to constrain ΩΛ in ΛCDM with similar accuracy as current supernova samples. We discuss the benefits of combining AGN and supernovae for cosmology and connect the present work to future attempts to reach out to redshifts of z > 4.
  
  
  1693-1703
  
    
      Hoenig, S.F.
      
        be0bb8bc-bdac-4442-8edc-f735834f3917
      
     
  
    
      Watson, D.
      
        cd946f1b-19b2-4629-9111-7d3be5798c8b
      
     
  
    
      Kishimoto, M.
      
        fe6c96f7-7782-424c-b715-44f27bfd4f41
      
     
  
    
      Gandhi, P.
      
        5bc3b5af-42b0-4dd8-8f1f-f74048d4d4a9
      
     
  
    
      Goad, M.
      
        62ad798a-4d53-4b93-8e2a-ddd6dcef72a8
      
     
  
    
      Horne, K.
      
        53fcebf2-d0a1-453a-b141-6174ac5e4afe
      
     
  
    
      Shankar, F.
      
        b10c91e4-85cd-4394-a18a-d4f049fd9cdb
      
     
  
    
      Banerji, M.
      
        5a6a7c49-46d6-4187-899f-2ae7e9b1854a
      
     
  
    
      Boulderstone, B.
      
        b59a74b9-9bab-4da1-8b42-9ce1cda6caf4
      
     
  
    
      Jarvis, M.
      
        ab19a6b5-0be9-4535-a580-cf3566932e26
      
     
  
    
      Smith, M.
      
        8bdc74e1-a37b-434d-ae75-82763109bf7a
      
     
  
    
      Sullivan, M.
      
        2f31f9fa-8e79-4b35-98e2-0cb38f503850
      
     
  
  
   
  
  
    
    
  
    
    
  
    
      11 January 2017
    
    
  
  
    
      Hoenig, S.F.
      
        be0bb8bc-bdac-4442-8edc-f735834f3917
      
     
  
    
      Watson, D.
      
        cd946f1b-19b2-4629-9111-7d3be5798c8b
      
     
  
    
      Kishimoto, M.
      
        fe6c96f7-7782-424c-b715-44f27bfd4f41
      
     
  
    
      Gandhi, P.
      
        5bc3b5af-42b0-4dd8-8f1f-f74048d4d4a9
      
     
  
    
      Goad, M.
      
        62ad798a-4d53-4b93-8e2a-ddd6dcef72a8
      
     
  
    
      Horne, K.
      
        53fcebf2-d0a1-453a-b141-6174ac5e4afe
      
     
  
    
      Shankar, F.
      
        b10c91e4-85cd-4394-a18a-d4f049fd9cdb
      
     
  
    
      Banerji, M.
      
        5a6a7c49-46d6-4187-899f-2ae7e9b1854a
      
     
  
    
      Boulderstone, B.
      
        b59a74b9-9bab-4da1-8b42-9ce1cda6caf4
      
     
  
    
      Jarvis, M.
      
        ab19a6b5-0be9-4535-a580-cf3566932e26
      
     
  
    
      Smith, M.
      
        8bdc74e1-a37b-434d-ae75-82763109bf7a
      
     
  
    
      Sullivan, M.
      
        2f31f9fa-8e79-4b35-98e2-0cb38f503850
      
     
  
       
    
 
  
    
      
  
  
  
  
  
  
    Hoenig, S.F., Watson, D., Kishimoto, M., Gandhi, P., Goad, M., Horne, K., Shankar, F., Banerji, M., Boulderstone, B., Jarvis, M., Smith, M. and Sullivan, M.
  
  
  
  
   
    (2017)
  
  
    
    Cosmology with AGN dust time lags–simulating the new VEILS survey.
  
  
  
  
    Monthly Notices of the Royal Astronomical Society, 464 (2), .
  
   (doi:10.1093/mnras/stw2484). 
  
  
   
  
  
  
  
  
   
  
    
    
      
        
          Abstract
          The time lag between optical and near-infrared continuum emission in active galactic nuclei (AGN) shows a tight correlation with luminosity and has been proposed as a standardizable candle for cosmology. In this paper, we explore the use of these AGN hot-dust time lags for cosmological model fitting under the constraints of the new VISTA Extragalactic Infrared Legacy Survey (VEILS). This new survey will target a 9 deg2 field observed in J and Ks band with a 14-d cadence and will run for 3 yr. The same area will be covered simultaneously in the optical griz bands by the Dark Energy Survey, providing complementary time-domain optical data. We perform realistic simulations of the survey setup, showing that we expect to recover dust time lags for about 450 objects out of a total of 1350 optical type 1 AGN, spanning a redshift range of 0.1 < z < 1.2. We use the lags recovered from our simulations to calculate precise distance moduli, establish a Hubble diagram, and fit cosmological models. Assuming realistic scatter in the distribution of the dust around the AGN as well as in the normalization of the lag–luminosity relation, we are able to constrain ΩΛ in ΛCDM with similar accuracy as current supernova samples. We discuss the benefits of combining AGN and supernovae for cosmology and connect the present work to future attempts to reach out to redshifts of z > 4.
         
      
      
        
          
            
  
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      Accepted/In Press date: 1 October 2016
 
    
      e-pub ahead of print date: 4 October 2016
 
    
      Published date: 11 January 2017
 
    
  
  
    
  
    
  
    
  
    
  
    
  
    
  
    
     
        Organisations:
        Astronomy Group
      
    
  
    
  
  
  
    
  
  
        Identifiers
        Local EPrints ID: 402390
        URI: http://eprints.soton.ac.uk/id/eprint/402390
        
          
        
        
        
          ISSN: 1365-2966
        
        
          PURE UUID: 55576647-3f8c-430d-924b-2bb1665be8b0
        
  
    
        
          
            
          
        
    
        
          
        
    
        
          
        
    
        
          
            
              
            
          
        
    
        
          
        
    
        
          
        
    
        
          
            
          
        
    
        
          
        
    
        
          
            
              
            
          
        
    
        
          
        
    
        
          
            
              
            
          
        
    
        
          
            
              
            
          
        
    
  
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  Date deposited: 08 Nov 2016 11:40
  Last modified: 21 Aug 2025 02:15
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      Contributors
      
        
      
          
          Author:
          
            
            
              D. Watson
            
          
        
      
          
          Author:
          
            
            
              M. Kishimoto
            
          
        
      
        
      
          
          Author:
          
            
            
              M. Goad
            
          
        
      
          
          Author:
          
            
            
              K. Horne
            
          
        
      
        
      
          
          Author:
          
            
            
              M. Banerji
            
          
        
      
          
          Author:
          
            
              
              
                B. Boulderstone
              
              
                 
              
            
            
          
         
      
          
          Author:
          
            
            
              M. Jarvis
            
          
        
      
        
      
        
      
      
      
    
  
   
  
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