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Visual and automatic search for lens candidates in the XMM-LSS and XXL fields

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Visual and automatic

search of lens candidates

in the XMM-LSS and XXL

fields

A. Elyiv, O. Melnyk, F. Finet,

A. Pospieszalska-Surdej, J. Surdej

Institut d'Astrophysique et de Géophysique

Liège University

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Search of lens candidates

Visual inspection

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optical survey in XXL-North

Depth 5σ in mag. CFHT W1: 23.6-25.5 CFHT ABC: 24.8-26.8

(4)

optical survey in XXL-South

Depth

5σ in mag.

(5)

Visual morphological

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very faint or

misclassified

Visual morphological

classification

early-type

galaxy

late-type

galaxy

merging

galaxy

point-like

source

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Coincidence of classification between two inspectors

Visual morphological

classification

(8)

Searching of lens candidates

Rank

1

Good (sure) lens candidate;

Rank

2

Probable lens candidate;

Rank

3

Possible lens candidate;

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(10)
(11)

Lens candidates

Einshtein’s ring?

Starforming galaxy

with ring?

(12)

J.F. Sygnet et al (2010)

Lens candidate

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Lens candidate

B1608+656

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Automatic searching of lens

candidates

Visual: Jackson 2008 Gravitational lenses and lens candidates identified from the COSMOS field

Automatic: Cabanac et al. 2007 - The CFHTLS strong lensing legacy survey. ARC, RING and Multiplet Detectors

More et al. 2011

Sygnet et al. 2010 A search for edge-on galaxy lenses in the CFHT Legacy Survey

Main aim of our work:

To construct the algorithm for automatic distinguish of the objects on

point-like and extended

objects with different morphology lens candidates

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Automatic identification

of the sources

CFHT image g-band Exposure 3.17 ks Seeing 0.87'' Procedure:

1. Choose the objects brighter than some flux limit.

2. Compose general PSF as accurate superposition of the selected objects. 3. Next we have fitted each object by general PSF. If χ² was larger that some limit we marked this object as "bad" and did not consider it in general PSF. 4. Repeat the steps 2 and 3 using only "good" object for the construction of general PSF.

5. After a few iterations when the number of "bad" objects became constant we stop the iterations.

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composed image residual image

Automatic identification

of the sources

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Examples:

close double system

point-like source edge-on galaxy

scale, σ units extended source (peculiar)

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Conclusions

Visually we found a few tens of good lens candidates in

XMM-LSS field which need detail spectroscopy.

We are constructing algorithm for automatic distinguish of the

objects on:

point-like and extended (for quick choice of templates at

photo-z calculations)

Références

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