# xFLS: Validation Report (FULL)

Master catalogue used: __master_catalogue_xfls_20171201.fits__<br>

Number of rows: 977,148

<br>

Surveys included:<br>

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

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

| KPNO-FLS      |                        | R                                 | dmu0_KPNO-FLS   |

| INT-WFC       | INT/WFC                | ugriz                             | dmu0_INT-WFC    |   

| PanSTARRS-3SS | PanSTARRS/GPC1         | ugriz                             | dmu0_PanSTARRS1-3SS |

| Legacy Survey | BASS                   | grz                               | dmu0_LegacySurvey |

| UHS           | UKIRT                  | J                                 | dmu0_UHS        |

| DataFusion    | Spitzer/IRAC           | IRAC1234                          | dmu0_DataFusion-Spitzer |

## 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 __Legacy Survey aperture and total__ magnitudes (at mag > 26) and __PanSTARRS aperture and total__ magnitudes (at mag > 23). Alse few sources in __IRAC__ have very large __total__ magnitude errors (at mag > 24).<br>

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<img src="help_plots/xFLS_magVSmagerr_BASS_g_mag_total.png" />

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### 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 ugriz bands, for bright sources, there is a two peaks distribution when comparing INT, Legacy Survey and Pan-STARRS.

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

### II.a. Pan-STARRS aperture magnitude

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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/xFLS_gpc1Issues_GPC1_g_mag_aperture.png" />

### II.c IRAC aperture magnitude

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IRAC is available for this field but no source have exactly the same magnitude.

### II.b. Outliers

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

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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/xFLS_outliers_BASS_g_aperture_-_GPC1_g_aperture.png"/>