# HDF-N: Validation Report (FULL)

HDF-N: Validation Report (FULL)¶

too few sources with
xxxxxxxxxx
 
Master catalogue used: __master_catalogue_hdf-n_20180201.fits__<br>Number of rows: 130,679<br>Surveys included:<br>​| Survey        | Telescope / Instrument   | Filters (detection band in bold)  | Location        ||---------------|--------------------------|:---------------------------------:|-----------------|| CANDELS-3D-HST| HST                      | F140W, F160W, F606W, F814W, F125W | dmu0_CANDELS-3D-HST || CANDELS-GOODS-N| HST/ACS/WFC3/MOIRCS/WIRCAM/IRAC| F105W,F140W,F160W,F125W,F435W,F606W,F775W,F814W, F850LP,K,Ks,IRAC1234  |dmu0_CANDELS-GOODS-N|| PanSTARRS-3SS | PanSTARRS/GPC1           | g,r,i,z,y                         | dmu0_PanSTARRS1-3SS || Hawaii-HDFN   | Subaru/MOSAIC/Suprime/QUIRC     | u,B,V,r,i,z,HK             | dmu0_Hawai-HDFN || Ultradeep-Ks-GOODS-N | WIRCAM prior IRAC | Ks, IRAC1234                      | dmu0_Ultradeep_Ks_GOODS-N |​__NB: On HDF-N there are too few sources with multiple aperture magnitudes. We then cannot look for difference in aperture correction between point-source and extended objects for different surveys.__​

Master catalogue used: master_catalogue_hdf-n_20180201.fits
Number of rows: 130,679
Surveys included:

Survey	Telescope / Instrument	Filters (detection band in bold)	Location
CANDELS-3D-HST	HST	F140W, F160W, F606W, F814W, F125W	dmu0_CANDELS-3D-HST
CANDELS-GOODS-N	HST/ACS/WFC3/MOIRCS/WIRCAM/IRAC	F105W,F140W,F160W,F125W,F435W,F606W,F775W,F814W, F850LP,K,Ks,IRAC1234	dmu0_CANDELS-GOODS-N
PanSTARRS-3SS	PanSTARRS/GPC1	g,r,i,z,y	dmu0_PanSTARRS1-3SS
Hawaii-HDFN	Subaru/MOSAIC/Suprime/QUIRC	u,B,V,r,i,z,HK	dmu0_Hawai-HDFN
Ultradeep-Ks-GOODS-N	WIRCAM prior IRAC	Ks, IRAC1234	dmu0_Ultradeep_Ks_GOODS-N

NB: On HDF-N there are too few sources with multiple aperture magnitudes. We then cannot look for difference in aperture correction between point-source and extended objects for different surveys.

## I. Caveats

I. Caveats¶

 
### I.a. Magnitude errors ​At faint magnitudes (mag > 24), some surveys have very large errors on the magnitude. These objects may be unreliable for science puposes.<br>This includes __MOSAIC u aperture and total__ magnitude (at mag > 30), __PanSTARRS aperture and total__ magnitudes (at mag > 24), __WIRCAM Ks total__ magnitude (at mag > 28), __MOSAIC K total__ magnitude (at mag >18) and __IRAC total__ magnitudes (at mag > 25). <br>​<img src="help_plots/HDF-N_magVSmagerr_MOSAIC_u_mag_total.png" />​

I.a. Magnitude errors¶

At faint magnitudes (mag > 24), some surveys have very large errors on the magnitude. These objects may be unreliable for science puposes.
This includes MOSAIC u aperture and total magnitude (at mag > 30), PanSTARRS aperture and total magnitudes (at mag > 24), WIRCAM Ks total magnitude (at mag > 28), MOSAIC K total magnitude (at mag >18) and IRAC total magnitudes (at mag > 25).

## II. Flags

II. Flags¶

 
### II.a. Pan-STARRS aperture magnitude​Few Pan-STARRS sources have exactly the same error (of <font color='blue'>0.0010860000038519502</font>) on the __aperture and total__ magnitudes in all the grizy bands. The corresponding aperture magnitude should not be trusted for these objects.<br>​<img src="help_plots/HDF-N_gpc1Issues_GPC1_r_mag_aperture.png" />

II.a. Pan-STARRS aperture magnitude¶

Few Pan-STARRS sources have exactly the same error (of 0.0010860000038519502) on the aperture and total magnitudes in all the grizy bands. The corresponding aperture magnitude should not be trusted for these objects.

 
### II.c IRAC aperture magnitude​No IRAC aperture magnitude available for this field.

II.c IRAC aperture magnitude¶

No IRAC aperture magnitude available for this field.

 
### II.b. Outliers​By comparing magnitude in the same band between different surveys, we can see that some magnitudes are significanlty different could not be trusted. <br>The outliers are identified to have a large weighted magnitude difference (equivalent of the $chi^2$).​$$chi^2 = \frac{(mag_{1}-mag_{2})^2}{magerr_{1}^2 + magerr_{2}^2}$$ <br>We used the 75th and 25th percentile to flagged the objects 5$\sigma$ away on the large values tail of the $chi^2$ ditribution. (__NB:__ bright sources tend to have their errors underestimated with values as low as $10^{-6}$, which is unrealistic. So to avoid high $chi^2$ due to unrealistic small errors, we clip the error to get a minimum value of 0.1% (i.e. all errors smaller then $10^{-3}$ are set to $10^{-3}$).)<br><br>$$outliers == [chi^2 >  (75th \;percentile + 3.2\times (75th \;percentile - 25th \;percentile))]$$​<img src="help_plots/HDF-N_outliers_SUPRIME_i_total_-_GPC1_i_total.png"/>

II.b. Outliers¶

By comparing magnitude in the same band between different surveys, we can see that some magnitudes are significanlty different could not be trusted.
The outliers are identified to have a large weighted magnitude difference (equivalent of the $chi^2$ ).

c h i^{2} = \frac{(m a g_{1} - m a g_{2})^{2}}{m a g e r r_{1}^{2} + m a g e r r_{2}^{2}}

$chi^2 = \frac{(mag_{1}-mag_{2})^2}{magerr_{1}^2 + magerr_{2}^2}$
We used the 75th and 25th percentile to flagged the objects 5

σ

$\sigma$ away on the large values tail of the

c h i^{2}

$chi^2$ ditribution. (NB: bright sources tend to have their errors underestimated with values as low as

10^{- 6}

$10^{-6}$ , which is unrealistic. So to avoid high

c h i^{2}

$chi^2$ due to unrealistic small errors, we clip the error to get a minimum value of 0.1% (i.e. all errors smaller then

10^{- 3}

$10^{-3}$ are set to

10^{- 3}

$10^{-3}$ ).)

o u t l i e r s == [c h i^{2} > (75 t h p e r c e n t i l e + 3.2 \times (75 t h p e r c e n t i l e - 25 t h p e r c e n t i l e))]

$outliers == [chi^2 > (75th \;percentile + 3.2\times (75th \;percentile - 25th \;percentile))]$

In [ ]: