# HATLAS-SGP: Validation Report (10% SUBSET)

Master catalogue used: __master_catalogue_sgp_RANDOM10PCSAMPLE_20180221.fits (Sample of 10% of the master catalogue)__ <br>

Number of rows:  2,979,069

<br>

Surveys included:<br>

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| Survey | Telescope / Instrument  | Filters (detection band in bold)  | Location        |

|--------|-------------------------|:---------------------------------:|-----------------|

| ATLAS         | VST/ OmegaCAM    | ugriz                             | dmu0_ATLAS      |  

| KIDS          | VLT OmegaCAM     | ugri                              | dmu0_KIDS       |  

| DES       | Blanco/DECam         | grizy                             | dmu0_DES        |  

| PanSTARRS-3SS | GPC1             | grizy                          | dmu0_PanSTARRS-3SS |     

| VIKING        | VISTA VIRCAM     | ZYHJKs                          | dmu0_VISTA-VIKING |

## I. Caveats

### I.a. Magnitude errors 

At faint magnitudes (mag > 24), some surveys have very large errors (> 10) on the magnitude. These objects may be unreliable for science puposes.<br>

This in includes __PanSTARRS aperture and total__ magnitudes (at mag > 23), __OmegaCAM aperture and total__ magnitudes (at m > 26), __DES aperture and total__ magnitudes (at mag > 26) and __UKIDSS aperture and total__ magnitudes (at mag > 22).<br>

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<img src="help_plots/HATLAS-SGP_magVSmagerr_OmegaCAM_g_mag_total.png" />

### I.b. Aperture corrections

In most of the case when comparing the aperture magnitudes between surveys, we observed a two peak distribution in the difference between the magnitudes ($\Delta_{mag} = mag_{survey1} - mag_{survey2}$). We have one peak around 0 for point-source objects, with a small spread. And a second peak at higher $\Delta_{mag}$ with a larger spread for extended objects; implying a different aperture correction between surveys for these objects.<br>

That means that galaxies will not have the same aperture magnitude in different surveys. <br>

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In the grizy bands, for bright sources, there is a two peaks distribution when comparing Pan-STARRS with DES, and Pan-STARRS with OmegaCAM aperture magnitues. <br>

Also, in the z-, y-band, we get again a two peak distribution on $\Delta_{mag}$ whgen comparing VISTA and Pan-STARRS magnitudes.

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<img src="help_plots/HATLAS-SGP_apcorrIssues_DECam_r_aperture_-_GPC1_r_aperture.png" />

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### II.a. Pan-STARRS aperture and total magnitudes

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>

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<img src="help_plots/HATLAS-SGP_gpc1Issues_GPC1_z_mag_aperture.png" />

### II.c. 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 $chi^2$).

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$$chi^2 = \frac{(mag_{1}-mag_{2})^2}{magerr_{1}^2 + magerr_{2}^2}$$ 

<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>

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

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<img src="help_plots/HATLAS-SGP_outliers_DECam_r_total_-_GPC1_r_total.png" />