This file describes the maps and catalogs for the H-ATLAS Data Release 2. Details are 
contained in the publications Smith et al. (2017, Paper I),  Maddox et al. (2018, paper II) 
and Furlanetto at al. (2018, Paper III). Please refer to these papers every time you 
use these products in publications.

----------------------------------------------------------------
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1. FILES 
----------------------------------------------------------------

We release 4 catalogue files: two files including sources from the NGP and SGP fields
respectively and two files related with UKIRT/WFCAM observations and described in the file
README_UKIRT.TXT (see paper III for more details). For each field a total of 21 files are 
released: 7 map files for each of the 3 bands. The PSFs and the filters used to smooth the 
maps are the same released in DR1 (see Paper I for more details).

catalogues from filtered backsub map 
(including details, for 
the NGP only, of the most 
probable optical ID):		HATLAS_NGP_DR2_CATALOGUE_<version>
							HATLAS_SGP_DR2_CATALOGUE_<version> 
catalogue from filtered backsub map 
(with entries, for 
the NGP only, of all 
potential optical IDs):		HATLAS_NGP_DR2_CATALOGUE_ALLIDS_<version>
column description:         HATLAS_<FIELD>_DR2_CATALOGUE.COLUMNS

SPIRE MAPS
raw maps:      				HATLAS_<FIELD>_DR2_RAW<BAND>.FITS
nscan maps:					HATLAS_<FIELD>_DR2_NSCAN<BAND>.FITS
masks:                      HATLAS_<FIELD>_DR2_MASK<BAND>.FITS 
background subtracted maps: HATLAS_<FIELD>_DR2_BACKSUB<BAND>.FITS
noise (excluding confusion) 
maps:   				   	HATLAS_<FIELD>_DR2_SIGMA<BAND>.FITS
filtered background 
subtracted maps:      	   	HATLAS_<FIELD>_DR2_FILT_BACKSUB<BAND>.FITS
noise (excluding confusion) 
for filtered maps: 		   	HATLAS_<FIELD>_DR2_FILT_SIGMA<BAND>.FITS

PACS MAPS
background subtracted maps: HATLAS_<FIELD>_DR2_BACKSUB<BAND>.FITS
nscan maps:					HATLAS_<FIELD>_DR2_NSCAN<BAND>.FITS
						
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2. NOTES ON SPIRE MAPS (see Paper I for further details)
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The 'raw' map files contain the image extension of the HIPE product with the masks applied
in order to exclude data where Herschel slows and turns around at the end of each scan leg.
No correction has been made for the map transfer function in the current release which
means that flux densities of structure larger than 20 arcmin will be attentuated
(see Figure 12 in Paper I).

The 'nscan' map files show the number individual SPIRE observations
used to estimate the flux density in each map pixel. 

The 'mask' files limit the map to the region where there is good data from at least two 
individual SPIRE observations; this is the region that should be used for science analysis.  
All masks have the same dimensions as the maps they mask and consist of 1s and 0s.

The 'backsub' maps have had a local background subtracted from the raw map using the 
nebuliser function from the CASU package
(see http://casu.ast.cam.ac.uk/surveys-projects/software-release/background-filtering
for further details). These maps might introduce a bias if used to measure fluxes of 
extended sources with an aperture radius larger than 1.5 arcmin (see below).

The 'sigma' noise maps give an estimate of the instrumental noise each pixel in the raw 
data map. Use this in preference to the error map contained within the HIPE product. The 
map file error extension is not consistently reliable, because in some areas there are not 
enough scans to accurately determine the noise from the variance in the data. Please use 
instead the 'sigma' noise map supplied which is created as described in the section about
"Noise maps" below. 
THESE MAPS DO NOT INCLUDE THE CONFUSION NOISE.

The 'fbacksub' files are the background subtracted, noise-weighted, filtered maps using 
a customised matched filter designed to maximise the signal-to-noise for a point source. 
This is the map that should used to detect point sources and measure their fluxes.

The 'fsigma' files are the corresponding instrumental noise maps. THESE MAPS DO NOT INCLUDE 
THE CONFUSION NOISE.

----------------
2.1. Astrometric Calibration
----------------

Astrometry of the maps of the individual observations that form the mosaic has been 
performed by a stacking analysis on the SDSS (for the NGP) and on the VLT Survey Telscope 
ATLAS (for the SGP). In the maps made from the indivudual observations we found astrometric 
shifts of 1-2 arcsec. In making the final mosaics, we have corrected for these shifts. 

-----------------------
2.2. Flux Measurements
-----------------------

The units of the map are Jy/beam. The calibration of the maps is SPIRE Calibration Tree 
Version 11 and is based on Neptune. The SPIRE data reduction pipeline is based on the 
assumption that the flux density of the sources depends on frequency^(-1). 
This calibration is slightly different from that used for the GAMA fields in DR1 (Valiante 
et al. 2016). To put the fluxes for the GAMA fields on the same scale as for the NGP and 
SGP, the DR1 flux densities must be multiplied by 1.025, 1.018 and 1.013 at 250, 350 and 
500 microns, respectively.

Users interested in modelling the SED of a source or who have some knowledge of the
SED should correct the flux densities using the colour corrections in either Table 5.7
or Table 5.8 in the SPIRE handbook. It is important to apply these corrections, since
they can be quite large: for a point source with a typical dust spectrum (T=20K, Beta=2),
the multiplicative corrections are 0.96, 0.94 and 0.90 at 250, 350 and 500 microns,
respectively.

To convert the maps from Jy/beam to Jy/pixel, in order to carry out aperture photometry, 
the values in the maps should be divided by the ratio between the beam area and the pixel 
area in arcsec^2 (469.4/36, 831.2/64 and 1804.3/144 at 250, 350 and 500 microns respectively). 
We recommend that aperture photometry is carried out on the background-subtracted raw maps. 
We have supplied a SPIRE point spread function at each wavelength if the user wishes to 
make a correction for the part of the PSF outside the aperture. Section 5.3 of Paper I 
gives a detailed recipe for aperture photometry and equations 3 and 4 in Paper I can be 
used to derive errors for the aperture photometry.

There is a 5.5% calibration uncertainty in the fluxes. Some of this uncertainty is 
correlated between bands. For those wishing to take account of this effect, a useful 
prescription is to assume that there is a 4% calibration uncertainty which is perfectly 
correlated between the bands and a 1.5% calibration uncertainty that is uncorrelated. The
current recommendation (SPIRE Handbook) is that these factors should be added, obtaining a 
total calibration uncertainty of 5.5%.

-----------------------------------------------
2.3. Stacking Analyses - Matched-filtered maps
-----------------------------------------------

For obtaining the best S/N in the flux measurement of point sources, we have also provided 
maps that have been convolved with a matched filter, derived to produce the maximum
S/N for a point source (Valiante et al. 2016). 
The units of these maps are also Jy/beam. The mean of these maps is not zero
(nebuliser effectively uses a combination of the mode and the median as an estimate of the 
background).
THESE MAPS SHOULD BE USED IN STACKING ANALYSES ONLY AFTER THEIR MEAN HAS BEEN SET TO ZERO
(Paper I).
Estimates of the errors in stacking measurements should be obtained by Monte-Carlo 
simulations.

----------------
2.4. Noise maps
----------------

The 'sigma' noise maps contain estimates of the instrumental noise on each pixel in the 
data maps and should be used in preference to the extension to the maps produced by HIPE.
They are created from the coverage maps (the extension called 'coverage' in the 
raw map fits file) by assuming that the noise decreases as sqrt(N_passes), and using the 
comparison between cross-scan measurements to determine the noise per pass
(Valiante et al. 2016; Paper I). The noise per pass that we have assumed for each pixel 
for this data release is 31.3, 32.0 and 35.9 (for the NGP) and 31.4, 32.1, 36.5 (for the 
SGP) mJy/beam at 250, 350 and 500 microns, respectively.  Pixels that have particularly 
high values in the error map are flagged as 'hot pixels'. The thresholds for being flagged 
as a hot pixel depend on the field and are
NGP: 0.51, 0.14, 0.043
SGP: 0.50, 0.16, 0.086
Jy/beam at the three wavelengths.
These pixels are given the noise as given by the HIPE extension.

The 'fsigma' noise map is the noise appropriate to the noise-weighted filtered map. The 
instrumental noise is calculated as the square-root of the inverse variance-weighted 
filtered variance from above. Confusion noise is not included: it should be calculated using 
Eq. 14 in Valiante et al. 2016 and added in quadrature.

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3. NOTES ON PACS MAPS (see Paper I for further details)
----------------------------------------------------------------

The 'backsub' maps are Level 1 maps from HIPE, processed by JScanamorphos and filtered
using the nebuliser function from the CASU package to remove any residual large-scale 
artefact (see http://casu.ast.cam.ac.uk/surveys-projects/software-release/background-filtering
for further details). The units are Jy/pixel. These maps might introduce a bias if used to 
measure fluxes of extended sources with an aperture radius larger than 4 arcmin (see below). 

The 'nscan' maps are produced by JScanamorphos and show the number of individual 
observations contributing to each pixel. It is used to derive the noise for each source 
(see below).

----------------
3.1. Astrometric Calibration
----------------

We performed an astrometric calibration of the indvidual PACS observations using a 
stacking analysis on 3.4-micron sources detected in the WISE survey (Paper I). Note that 
this is different from the technique we used for the GAMA fields. The final mosaics have
been corrected for the astrometric shifts found using this technique.

-----------------------
3.2. Stacking Analyses
-----------------------

The mean of the PACS maps is not zero, because of the background subtraction filter. THESE 
MAPS SHOULD BE USED IN STACKING ANALYSES ONLY AFTER THEIR MEAN HAS BEEN SET TO ZERO. 
Estimates of the errors in stacking measurements should be obtained by Monte-Carlo 
simulations.

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4. NOTES ON CATALOGUES (see Paper I and II for further details)
----------------------------------------------------------------

Columns description is in the file HATLAS_<FIELD>_DR2_CATALOGUE.COLUMNS

----------------------------
4.1. SPIRE Catalog Creation
----------------------------

This catalogue contains all SPIRE sources which are >4 sigma significance (including 
confusion noise) in any of the three SPIRE bands (250, 350, 500um).

The source catalogue is based on finding peaks in the noise-weighted matched filter 
filtered the maps using the MADX algorithm.

Maps are background subtracted before source extraction.

SPIRE FLUXES - The catalogue is produced by using the 250 micron map to perform the source 
detection. The flux in each band is then estimated as the flux from the noise-weighted 
matched-filter filtered map in each band at the 250-micron position. Aperture fluxes are 
included where the identification in the optical suggested the source would be resolved by 
Herschel or where it was clear from the appearance of the source that it is extended (see 
Extended source description).
'F<BAND>' columns are the point source fluxes from MADX, 'F<BAND>BEST' flux columns use the 
largest of the aperture or point source fluxes. To assess which one of the 2 values is the 
largest, we take into account the noise. The aperture flux is preferred over the point 
source flux if:
(F_AP-F_PS)>sqrt(sigma_AP^2-sigma_PS^2)
We consider the flux at 250um the most reliable to define a source as extended or not.
This is because at longer wavelengths, the effect of confusion is larger. This means that, 
if the condition above prefers the point source flux at 250um, and the aperture flux at 
350 or 500um, we keep anyway the point source flux as best flux in all bands.  
Some sources have been assigned a point sources flux as best flux after visual inspection.
F<BAND>BEST values are what we consider the most reliable estimate of the flux for a source
(see Paper II for a full description).

UNCERTAINTIES ON SPIRE FLUXES - The uncertainty maps are calculated from the coverage maps 
and assume instrumental noise values of 31.3, 32.0, 35.9 (for the NGP) or 31.4, 32.1, 36.5 
(for the SGP) mJy per pixel per pass per beam. 
The maps are deep enough that confusion noise is an important factor that must be included 
in any error estimates. For point sources, we have used the confusion estimates from the 
simulations described in Valiante et al. (2016), which are constant values of 6.59 and 6.62 
mJy at 350 and 500 microns, respectively, and a value that depends on the source flux at 
250 microns, which is given by equation 14 in that paper.
The error on each flux in the catalogue is the sum in quadrature of the instrumental noise 
and confusion noise. We describe how we estimate the flux errors for the extended SPIRE 
sources in the following section.

******************************************************************* 
A 5.5% calibration uncertainty should be added in quadrature to all
SPIRE fluxes in this catalogue.
*******************************************************************

POSITIONS - From the positions of the optical IDs, we estimate that the relationship 
between position accuracy and S/N at 250 microns is given by sigma_pos = 2.4(SNR/5.0)^-0.84, 
with a minimum positional accuracy of 1 arcsec (Paper II).

COLOUR CORRECTION - The SPIRE data reduction pipeline is based on the assumption that the 
flux density of the sources depends on frequency^(-1). Users interested in accurately 
modelling SEDs should multiply the measured flux densities by the colour corrections given 
in Tables 5.7 and 5.8 in the SPIRE Handbook.

OTHER ISSUES - Flux boosting from Eddington bias and source confusion is present for 
sources near the detection limits. Please see Paper II for details and averaged correction 
values. This catalogue is NOT CORRECTED for flux boosting.

--------------------------------------------
4.2. Extended SPIRE source flux description
--------------------------------------------

If we believed that the SPIRE source is likely to be extended, either because the source 
is associated with a large nearby galaxy or is clearly extended on the images, we measured 
a flux density through an aperture.
If the aperture flux is significantly larger than the point-source flux (Paper 2), the 
aperture fluxes are the ones reported in the 'F<BAND>BEST' columns; otherwise the fluxes 
in these columns are the point-source flux densities. The only exceptions are when we 
realised from inspection of the images that it was not possible to define a suitable 
aperture without including a neighbouring point source.

We measured aperture flux densities in two situations: 
(1) if the source had an optical counterpart, an optical size (SDSS parameter 
ISOA_R_ARCSEC) > 10 arcsec and was not stellar (GSQ_FLAG!=1); 
(2) if from visual inspection of the images the source was clearly extended. 
Since neither the galaxies in the NGP nor SGP had measurements of ISOA_R_ARCSEC (the size 
parameter we used in DR1), we used the SDSS size parameter PETROR90_R for the NGP, using
the scaling ISOA_R_ARCSEC = 1.156*PETROR90_R, and the 2MASS size parameter sup_r_3sig for 
the SGP, using the scaling ISOA_R_ARCSEC = 1.96*sup_r_3sig.
For the sources with optical IDs, we initially calculated an aperture radius, r_ap, of
r_ap = sqrt(FWHM^2.0 + ISOA_R_ARCSEC^2.0). We then visually inspected the images and, if 
necessary, adjusted the apertures to avoid nearby sources and better include the emission 
from the source. We also chose suitable apertures for the extended sources without optical 
IDs. We allowed these 'customised apertures' to be elliptical, and these can be easily 
found in the catalogue because sources with customised apertures have values of 
AP_RMIN and AP_PA. 

The aperture photometry was performed on the backsub maps made by MADX.
The errors on the aperture flux densities were calculated using equations 3 and 4 in 
Paper I, which are fits to the results of Monte-Carlo simulations, and have been scaled to 
correct for the proportion of emission that is expected to fall outside the aperture
using a PSF derived from observations of Neptune.
More details of how we did the aperture photometry are given in Paper II.

The same issues of colour correction and flux boosting apply to these aperture fluxes 
(see above).

******************************************************************* 
A 5.5% calibration uncertainty should be added in quadrature to all
SPIRE fluxes in this catalogue.
*******************************************************************

-----------------
4.3. PACS FLUXES
-----------------

PACS flux densities were measured using circular apertures placed at the optical positions
when there is an optical ID with RELIABILITY > 0.8, which is only
the case for the NGP. Otherwise, the SPIRE positions were
used. The PACS maps, similar to the SPIRE maps, have been background-subtracted, so we 
assumed that there is effectively zero background. 
SPIRE sources falling outside the PACS maps have PACS fluxes set to  -1.

APERTURES - Two sets of aperture radii were used: firstly a `point source' flux density was
found using 11.4 and 13.7 arcsec radii apertures at 100 and 160 microns respectively
(the assumed FWHM of the beams). 
If these were measured at the SPIRE positions, we multiplied these by factors of 1.05 and 
1.1 at 100 and 160 microns, respectively, to allow for the uncertainties in the SPIRE 
positions (Valiante et al. 2016).
Next, additional aperture flux densities were measured for positions where a PACS source 
has an optical ID, using an aperture radius
r_ap = sqrt(FWHM^2 + ISOA_R_ARCSEC^2)
where ISOA_R_ARCSEC is the SDSS size parameter ISOA_R converted to arcsec. Since we did 
not have values of ISOA_R for the NGP and SGP, we estimated the values of ISO_R_ARCSEC 
from the alternative size parameters that do exist for these fields (see above).
If the source had a customised aperture for the SPIRE photometry (see above), we used this 
aperture in preference to the one calculated from the equation.

We made aperture corrections to the fluxes using the Encircled Energy Function described 
by Valiante et al. (2016) and we calculated flux errors using equations 5 and 6 in Paper I. 

We used the aperture flux densities in the final catalogue if they are significantly higher 
than the point-source fluxes. Paper II gives further detail of the photometry.

**********************************************************************
A calibration error of 7% should be added in quadrature to all errors
for all the PACS fluxes
quoted in this catalogue.
********************************************************************

------------------------------------------
4.4. Optical IDs from SDSS DR10 (NGP only)
------------------------------------------
IDs are sought via a Likelihood-Ratio analysis of optical candidates within 10 arcsec of 
all SPIRE sources with S/N>=4 at 250mum (defined as F250/E250 in the matched-filter 
catalogues). The data release main catalogue (HATLAS_NGP_DR2_CATALOGUE.FITS) contains only 
the 'best' candidate ID to each SPIRE source (where available). Most users will find in this 
catalogue everything they will need for their science purposes. A second catalogue is also
available (HATLAS_NGP_DR2_CATALOGUE_ALLIDS.FITS), which contains all possible counterparts 
within the search radius of each SPIRE source, and provides the full LR 
statistics so that these may be independently analysed as the user wishes. To select only 
sources which have reliable optical IDs, we recommend applying a cut of Reliability>=0.8, 
although other cuts on Reliability or LR may be suitable for different purposes as 
discussed in Bourne et al. (2016). The flags 'R' and 'M' in the ID_FLAG column indicate 
that the reliability has been modified for sources which are resolved in SPIRE ('R') or 
which have a merger ID ('M') which caused the reliability of a genuine counterpart to be 
underestimated by the formula. Note that in the catalogue of all potential counterparts
(HATLAS_NGP_DR2_CATALOGUE_ALLIDS.FITS), in a small number of cases it is possible for a 
source to have two reliable IDs if it is a merger ('M' flag).

Positions:
----------
The optical catalogue is based primarily on SDSS DR10 primary object IDs with 
MODELMAG_R<22.4, obtained from CASJOBS. 
SDSS positions (OPTICALRA and OPTICALDEC) and SDSS_OBJIDs are included in the table to 
facilitate matching back to the CAS databases. Due to the length of SDSS_OBJIDs, these 
must be stored in a 64-bit integer.  

Positions with SDSS deblend flags have been eyeballed, leading to the removal of a number 
of erroneously deblended SDSS galaxies, which had been shredded into multiple sources by 
the SDSS source extraction.

Redshifts:
----------
Spectroscopic redshifts are obtained from SDSS DR10 and CfA Redshift Survey.  
Given the lack of quality flag in the CfA catalogue, for objects that have redshift in 
both surveys, the CfA redshift is used in preference only if there is a redshift warning 
flag for the  object in the SDSS DR10.
The source of each redshift in the catalogue is given by Z_SOURCE. Codes are as follows:
1    SDSS DR10
2    CfA Redshift Survey

The quality flag is Z_QUAL. SDSS redshifts with spectroscopic flags (ZWARNING) have been 
flagged as follows:
Z_QUAL=2:	Z_FITLIMIT (chi-squared minimum at edge of the redshift fitting range(Z_ERR 
			set to -1))
Z_QUAL=3:	MANY_OUTLIERS (fraction of points more than 5 sigma away from best model is 
			too large (> 0.05))
          	or NEGATIVE_EMISSION (a QSO line exhibits negative emission, triggered only in 
          	QSO spectra, if C_IV, C_III, Mg_II, H_beta, or H_alpha has 
          	LINEAREA + 3 * LINEAREA_ERR < 0)
Z_QUAL=0:	Any other spectra flag.
Z_QUAL=5:	No spectra flags.
For more details of the SDSS spectroscopic flags see 
http://www.sdss3.org/dr10/algorithms/bitmask_zwarning.php

Only spectroscopic redshifts with Z_QUAL>=3 are recommended to be reliable. Photometric 
redshifts have been obtained from SDSS DR10 (see Csabai et al. 2007 for full details).

Star-galaxy Separation:
-----------------------
The SDSS positions and modelmags are matched to UKIDSS LAS (DR9) from which we use 
aperture magnitudes in J and K bands to assist with star-galaxy separation. Galaxies and 
stars were discriminated using a g-i/J-K colour-colour diagram in addition to r-band 
PSF/model magnitude criteria (see Paper III). To avoid contamination from quasars, 
anything classified as a star which had a spectroscopic redshift z>0.001 (with Z_QUAL>=3), 
was reclassified as a quasar. 

The GSQ_FLAG column contains the star-galaxy separation results as follows:
0 = galaxy
1 = star
2 = quasar (point-like source with spec-z>0.001)

For the purposes of LR statistics, all extragalactic sources (GSQ_FLAG!=1) are treated 
together, while stars are treated separately, as described in Paper III. 

Likelihood ratio analysis:
--------------------------
Likelihood ratios are calculated for every optical object within 10 arcsec of each SPIRE 
source, following the procedure described in detail in Paper III. The procedure 
consists of three stages: 
i) The first quantity to define is Q0, which is the underlying true fraction of SPIRE 
sources which exist in the SDSS catalogue (i.e. which have r magnitude <22.4). Q0 is 
measured using the blanks-counting technique from Fleuren et al. 2012 for the 
galaxies+quasars sample, and for all candidates, thus providing an estimate for stars from 
the difference. This is the same as in H-ATLAS DR1, but differs from the method used in 
SDP, as discussed in Bourne et al. 2016. 
ii) The r-band magnitude dependence is calculated based on the normalised magnitude 
distributions of real counterparts [q(m)] and of background objects [n(m)]; this is 
estimated separately for stars and extragalactic sources respectively. At bright 
magnitudes (m<13.5 for galaxies; m<21.5 for stars), the Poisson noise is too large to 
estimate this reliably and the distribution q(m)/n(m) is assumed flat and is given by the 
average across all magnitudes 10<m<13.5. This assumption differs from that in catalogues 
previous to DR1 H-ATLAS catalogues, in which the q(m)/n(m) for brighter galaxies was 
simply fixed at the brightest bin where it could be measured; and for stars a constant 
q(m) was assumed rather than constant q(m)/n(m). The reasons for these decisions and the 
effects on the results are discussed in Bourne et al. 2016.
iii) The positional offset distribution is used to describe the probability f(r) of a true 
counterpart having a given radial offset r. This is estimated from blue SPIRE sources only, 
as a function of 250mum SNR (F250/E250, based on the matched-filter catalogue). Red sources 
(F250/F350<2.4) are excluded from this analysis in order to avoid the bias due to lensing 
described in Bourne et al. 2014, interpretation which is supported by the results from 
Gonzalez-Nuevo et al. 2017. The functional fit measured from blue SPIRE sources (and 
applied to all SPIRE/SDSS pairs, regardless of colour) is
sigma_pos/arcsec = 1.99*(SNR/5)^(-0.84)
This defines the width of the Gaussian f(r). This empirical fit gives results very close 
to the theoretical 0.6*FWHM/SNR (Ivison et al. 2007), although note the weaker SNR 
dependence which may be explained by the increased positional errors of bright sources 
which are more likely to be (marginally) resolved by SPIRE.
Additionally, for all sources we impose a floor of 1 arcsec on sigma_pos since smaller 
positional errors are considered unrealistic.

Combining these elements, the Likelihood ratio of each SDSS counterpart is given by
LR = f(r) q(m,c)/n(m,c)
where c indicates stars/extragalactic objects in SDSS, whose magnitude dependence is 
treated independently. The reliability of each potential match then depends on the 
likelihoods of all possible matches to a given SPIRE source, in addition to the 
probability that the true counterpart is absent from SDSS (1-Q0):
R_i = LR_i / [Sum_j{LR_j} + (1-Q0)]
Reliabilities given by this formula range from 0 - 1; we consider R>0.8 to be reliable 
(although this cut is somewhat arbitrary; see Bourne et al. 2016 for more details). Note 
that some reliabilities in the catalogue have been modified following by-eye validation, as 
described below (under Flags), and these will fall outside of this range. In these cases 
the reliability has been set to R+1, so that matches deemed reliable by eye will satisfy a 
cut of R>0.8. 

Flags:
------
The column ID_FLAG contains flags assigned during post-processing. The brightest 1300 SPIRE 
sources were examined by eye after the completion 
of the LR analysis in order to validate automated results in these special cases where 
they are most likely to fail. In addition, the positions of bright stars from the Tycho 
catalogue were eyeballed to ensure that their IDs were not missed and that they had not 
been misclassified. 
As a result, the following flags were assigned in the ID_FLAG column:
R 	= Resolved SPIRE source where the counterpart was missed or appeared unreliable due to 
		a large optical-SPIRE separation. The reliability was fixed manually after visual 
		inspection (R_new=R_formula+1) to ensure the ID meets the reliability cut.
M	= SPIRE source with merger ID(s), which caused the reliability to 
		be underestimated. The reliability was fixed manually after visual inspection 
		(R_new=R_formula+1) thus ensuring the ID meets the reliability cut. Note that in a 
		small number of cases two 'reliable' IDs were given to a single SPIRE source where 
		it was obvious that the emission was roughly equally shared between the two 
		merging galaxies.
V	= Visible galaxy in optical image but missing from SDSS DR10, for example because the 
		galaxy falls under a bright star mask. No optical ID given in catalogue, but the 
		flag indicates that it is visible in the optical.

----------------------------------------------------------------
----------------------------------------------------------------
5. SUMMARY OF CHANGES FROM THE DR1
----------------------------------------------------------------

1. Completely new reduction of the SPIRE maps with revised noise estimates.

2. Optical catalogue used for cross-correlation is SDSS DR10.