# XMM-LSS: Validation Report (10% SUBSET)

Master catalogue used: __master_catalogue_xmm-lss_RANDOM10PCSAMPLE_20180221.fits (10% of the master catalogue)__ <br>

Number of rows: 870,476

<br>

Surveys included:<br>

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

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

| CANDELS-3D-HST | HST  | F140W, F160W, F606W, F814W, F125W            | dmu0_CANDELS-3D-HST |

| CANDELS-UDS    | HST  | ACS_F606W, ACS_F814W, WFC3_F125W, WFC3_F140W, WFC3_F160W                                                 | dmu0_CANDELS-UDS    |

| CFHTLS         | CFHT / Megacam  | u*, g', r', i', z'                | dmu0_CFHTLS         |

| CFHTLenS       | CFHT / Megacam  | u, g, r, i, z                     | dmu0_CFHTLenS       |

| VIPERS-MLS     | CFHT / Megacam / WIRCam| u, g, r, i, z, Y, Ks       | dmu0_VIPERS-MLS     |

| SpARCS         | CFHT / Megacam  | u, g, r, y, z                     | dmu0_SpARCS         |

| DES            | Blanco/DECam     | grizy                        | dmu0_DES            |

| DECaLS         | DEC             | g, r, z                           | dmu0_DECaLS         |

| HSC-SSP        | Subaru / Suprime| g, r, i, z, y                     | dmu0_HSC            |

| SXDS           | Subaru / Suprime| B, V, r, i, z                     | dmu0_SXDS           |

| PanSTARRS-3SS  | GPC1            | g, r, i, z, y                     | dmu0_PanSTARRS1-3SS |

| CFHT-WIRDS     | CFHT / WIRCAM   | J, H, Ks                          | dmu0_CFHT-WIRDS     |

| UKIDSS-DXS     | UKIRT / WFCAM   | J, H, K                           | dmu0_UKIDSS-DXS_DR10plus |

| UKIDSS-UDS     | UKIRT / WFCAM   | J, H, K                           | dmu0_UKIDSS-UDS    |

| VHS            | VISTA / VIRCAM  | Y, J, H, Ks                       | dmu0_VISTA-VHS      |

| VIDEO          | VISTA / VIRCAM  | Z, Y, J, H, Ks                    | dmu0_VISTA-VIDEO-private |

| VIKING         | VISTA / VIRCAM  | Z, Y, J, H, Ks                    | dmu0_VISTA-VIKING   |

| SERVS          | Spitzer / IRAC  | IRAC1, IRAC2                      | dmu0_DataFusion-Spitzer |

| SWIRE          | Spitzer / IRAC  | IRAC1, IRAC2, IRAC3, IRAC4        | dmu0_DataFusion-Spitzer |

​

## 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 __DECaLS aperture and total__ magnitudes (at m >  23), __PanSTARRS aperture and total__ magnitudes (at mag > 23), __VISTA aperture and total__ magnitudes (at mag > 22) and __HSC-SSP aperture and total__ magnitudes (at mag > 25, with magnitude as faint as 60 and error ap to 10$^{13}$). <br>

Also, the __CFHT (Megacam and WIRCam) aperture and total__ magnitude errors (at mag > 26), and the __UKIDSS aperture and total__ magnitude errors (at mag > 26) can be very large too but for few sources. <br>

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<img src="help_plots/XMM-LSS_magVSmagerr_DECam_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 griz bands, for bright sources, there is a two peaks distribution when comparing Pan-STARRS, DES, Megacam and Suprime aperture magnitues. Except when comparing Suprime with DES magnitudes, $\Delta_{mag}$ is similar for point-sources and extended objects.<br>

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<img src="help_plots/XMM-LSS_apcorrIssues_DECam_z_aperture_-_GPC1_z_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/XMM-LSS_gpc1Issues_GPC1_g_mag_aperture.png" />

### II.c IRAC aperture magnitude

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Few IRAC sources have exactly the same aperture magnitude (of <font color='blue'>3.9000000001085695</font>) in the IRAC1 IRAC2 band (for the subset). These magnitudes also have extremely small errors (around 10$^{-8}$-10$^{-9}$). The corresponding magnitudes should not be trusted. <br>

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<img src="help_plots/XMM-LSS_iracIssues_i1_i2.png" />

### II.d. 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/XMM-LSS_outliers_DECam_g_aperture_-_GPC1_g_aperture.png" />