[daip] Fwd: GOODS-N Number Counts

[Glenn Morrison]

Hi Eric,

Could you review the email below and tell me if you agree with the  
statements made about the GAIN parameter in SAD?

-Thanks

--Glenn

Begin forwarded message:

> From: Eduardo Ibar <ibar at roe.ac.uk>
> Date: August 22, 2008 12:14:20 AM HST
> To: Glenn Morrison <morrison at cfht.hawaii.edu>
> Cc: Mark Dickinson <med at noao.edu>, Rob Ivison <rji at roe.ac.uk>,  
> Frazer Owen <fowen at aoc.nrao.edu>
> Subject: Re: GOODS-N Number Counts
>
>
> Hi Glenn,
>
>>> I have just modified the factor GAIN to =1.0 (it was 0.1 before)  
>>> in the IMMOD-SAD simulations I explained before. Basically, IMMOD  
>>> is used to introduce point sources smeared by bandwidth smearing  
>>> in a residual image and SAD is used to extract them under the same  
>>> criteria of the catalogues. The GAIN factor is critical to extract  
>>> faint sources and to not to overestimate the number of gaussian- 
>>> fits per source. This implies completeness as a function of flux  
>>> density is higher, which translates in lower LogN.
>>
>> Are you just inserting point sources or can you also insert a  
>> source distribution size (which is more realistic)?
>
> Just point sources but bandwidth smeared as a function of distance  
> from the pointing centre. You are completely right in saying it  
> would be much better to assume a distribution in size, although  
> which one? Windhorst et al. (1990) and Bondi et al. (2003) have  
> provided an angular distribution before but they differ quite  
> substantially. To assume a distribution from the GOODSN sources  
> itself is tricky due to bandwidth smearing too. This is why I  
> decided to introduce point sources only but then applying a  
> resolution bias factor.
>
>>>> The GAIN factor is critical to extract faint sources and to not  
>>>> to overestimate the number of gaussian-fits per source.
>>
>> What do you mean here about "overestimate the number of gaussian- 
>> fits per source" and why GAIN is helpful in this respect?
>
> In previous source extractions I completely missed the importance of  
> GAIN factor. It is one of those parameters by default I prefer not  
> to touch but somehow it was set to 0.1 that time. Look at the  
> attached images which compare different SAD extractions:
>
> top-left: ICUT = 1.0, GAIN = 1.0
> top-right: ICUT = 1.0, GAIN = 0.1
> bottom-left: ICUT = 0.1, GAIN = 1.0
> bottom-right: ICUT = 0.1, GAIN = 0.1
>
> Clearly GAIN plays a key role in extended bright sources, but also  
> (surprisingly) in some single sources that are completely rejected.
>
> On the other hand, it's also clear SAD is fitting significant  
> numbers of sources by two Gaussians (the radio contours in the small  
> image). To be honest, I do not really understand the reasons why it  
> does it, but
> basically GAIN = 1 does two things:
>
> 1) Less sources are split into multiples
> 2) Less sources are rejected by SAD based on the rms of the fit
>
> cheers
>
> edo
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