The ATESP survey consists of 16
radio mosaics with spatial resolution
.
The survey was
designed so as to provide uniform sensitivity over the whole region
(
sq. degrees) of the ESP redshift survey.
To achieve this goal a larger
area was observed, but we have excluded from the analysis the external
regions (where the noise is not uniform and increases radially).
In the region with uniform sensitivity the noise level
varies from 69
Jy to
88
Jy, depending on the radio mosaic, with an average of 79
Jy
(see
values reported in Table 3 of Paper I and repeated
also in Table B1 of Appendix B,
at the end of
this paper). For consistency
with Paper I, in the following such
sensitivity average values are denoted by the symbol
.
This means
that sensitivity values have been defined as the full width at
half maximum (FWHM) of the Gaussian that fits the pixel flux density
distribution in each mosaic (see Paper I for more details).
A number of source detection and parameterization algorithms are available, which were developed for deriving catalogues of components from radio surveys. We decided to use the algorithm Image Search and Destroy (IMSAD) available as part of the Multichannel Image Reconstruction, Image Analysis and Display (MIRIAD) package (Sault & Killeen 1995), as it is particularly suited to images obtained with the ATCA.
IMSAD selects all the connected regions of pixels (islands)
above a given flux
density threshold. The islands are the sources (or the source
components) present in the image above a certain flux limit. Then IMSAD
performs a two-dimensional
Gaussian fit of the island flux distribution and
provides the following parameters: position of the
centroid (right ascension, ,
and declination,
),
peak flux density (
), integrated flux density (
),
fitted angular size (major,
,
and minor,
,
FWHM axes, not deconvolved for the beam) and position angle (PA).
IMSAD proved to have an average
success rate of
down to very faint flux levels (see below).
Since IMSAD attempts to fit a single Gaussian to each island, it
obviously tends to fail (or to provide very poor source parameters)
when fitting complex (i.e. non-Gaussian) shapes.
We used IMSAD to extract and parameterize
all the sources and/or components in the uniform sensitivity region of
each mosaic.
As a first step, a preliminary list containing all detections
with
(where
is the average mosaic
rms flux density) was extracted. Detection thresholds vary from 0.3 mJy
to 0.4 mJy, depending on the radio mosaic.
We visually inspected all islands ()
detected, in order
to check for obvious failures and/or possibly poor parameterization, that
need further analysis.
Problematic cases were classified as follows:
![]() |
Figure 1:
Peak flux density distribution for all the ATESP radio sources
(or source components) with
![]() |
For the first three groups listed above ad hoc procedures were attempted aimed at improving the fit.
Single-component fits were considered satisfactory whenever positions and flux densities satisfy the tolerance criteria defined above.
In a few cases Gaussian fits were able to provide good values for positions
and peak flux densities, but did fail in
determining the integrated flux densities. This happens typically at faint
fluxes ().
Gaussian sources with a poor
value are
flagged in the catalogue (see Sect. 3.4).
The islands successfully split in two or three components are 67 in total (64 with two components and 3 with three components).
For non-Gaussian sources we adopted as parameters the reference
positions and flux densities defined above. The source position angle
was determined by
the direction in which the source is most extended and the source axes
were defined as largest angular sizes (las), i.e. the maximum
distance between two opposite points belonging to the
flux density
contour along (major axis) and perpendicular to (minor axis) the same
direction.
All the non-Gaussian sources are flagged in the catalogue
(see Sect. 3.4).
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