Presentazione di PowerPoint

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VODIA VST OmegaCAM Difference Image Analysis
Silvio Leccia AW-OAC team
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Overview Original DIA
The DIA is a software written by P.R.Wozniak
based on the Alard Lupton optimal PSF matching
algorithm
Cross_regrid Registration and correction of input images
mstack Creation of the reference image with best seeing frames
getpsf Global PSF on REF (used in getvar and phot steps)
Aga Creates difference images
Getvar Finds variable candidates
Phot Light Curve with PSF and aperture photometry on the difference images
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AGA step Image Subtraction

• Once the REFerence frame is created it is
  convoluted with a kernel (spatially variable in
  general) in order to match as close as possible
  each image. This convoluted image is then
  subtracted to the current frame, producing a
  serie of subtracted images.

• The Algorithm
• A list of objects is found on the REF (domains)
• A list of objects is found on the single image
  (domains)
• It matchs the domains and calculates the kernels
  (3 Gaussians of costant widths multipied by
  polynomials)
• It produces the difference image

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Getvar step variable objects detection

• The program starts by rejecting some fraction of
  the frames with the worst seeing (in our case
  10)
• The pixel is declared as variable if one of these
  two conditions are met
• 1. There are at least 3 consecutive points
  departing at least 3s from the base line in the
  same direction (up or down), or
• 2. There are at least 10 points in total
  departing at least 4s from the base line in the
  same direction, not necessarily consecutive.

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Phot Step Photometry

• For each variable object the program performs
  both profile and aperture photometry on
  difference images keeping the centroid fixed
• The format of the catalog is
• Flux profile photometry
• Flux error profile photometry
• Flux aperture photometry
• Flux error aperture photometry
• Background
• FWHW of the PSF profile

• Where
• Pi is PSF for pixel i
• fi flux for pixel i on differece images
• fi,0 flux for pixel on original images
• G is Gain and

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VODIA new functionalities

• Added in Aga
• Mask for each input image
• The kernel can be calculated using an external
  list of objects
• Added in Getvar
• Ascii catalogs of variable objects
• Psf image is created and saved (QC check)
• VAR images are saved
• Added in Phot
• Ascii light curves
• Errors now include also read-out noise

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VODIA how it works on the BEOWULF
Software
Hardware
MASTER
storage
wcs2pix
prepare
Network SWITCH
mstack
Node 1
BeoRunner
getpsf
Node 2
aga
getvar
phot
Node n
lc
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Step 1 cut all images using the astrometric
solution
MASTER
storage
wcs2pix
prepare
Network SWITCH
mstack
Node 1
BeoRunner
getpsf
Node 2
aga
getvar
phot
Node n
lc
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Step 2 split the images in sub frames and copy
them on nodes
MASTER
storage
wcs2pix
prepare
Network SWITCH
mstack
Node 1
BeoRunner
getpsf
Node 2
aga
getvar
phot
Node n
lc
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Step 3 mstack the subframes indipendently on the
nodes
MASTER
storage
wcs2pix
prepare
Network SWITCH
mstack
Node 1
BeoRunner
getpsf
Node 2
aga
getvar
phot
Node n
lc
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• TESTs
• 69 Images VLT-FORS GC 2kx2k B Band
• 46 Images WFI Carina 8kx9k B Band
• 15 Images WFI OACDF 7kx7k V Band

Beo2 1 Master 16 nodes
Beo0/1 2 Master 8 nodes
69 2kx2k 15 7kx7k 46 8kx9k
wcs2pix 1m 14m
prepare 1m 3m 21m
mstack 3s 10s 1m10s
getpsf 2s 5s 10s
aga 3m 3m50s 19m31s
Getvar 10s 14s 1m37s
Phot 3s 10s 1m7s
Lc 8s 12s 1m
TOTAL 4m26s 8m42s 59m35s
69 2kx2k 15 7kx7k
wcs2pix 1m15s
prepare 2m 8m
mstack 10s 37s
getpsf 7s 12s
aga 4m20s 5m23s
Getvar 1m11s 1m59
Phot 59s 1m32
Lc 2m 1m
TOTAL 6m47s 19m58
it depends from the threshold in Getvar
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VLT-FORS Images
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VLT-FORS Image
VLT-FORS difference Image
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Testing VODIA and comparing the results with
other methods (redVODIA, blackALLFRAME,
cyanMunich IS)
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Testing VODIA and comparing the results
with other methods (redVODIA,
blackALLFRAME, cyanMunich IS)
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Testing VODIA and comparing the results
with other methods (redVODIA,
blackALLFRAME, cyanMunich IS)
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Testing with Simulated Images
Aobs/Aorig?1.05
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Exercise

• 68 images 500x500 pixel
• Run VODIA in the AWE
• Second part
• Change parameters of getvar and run only the
  final steps of VODIA (getvar and phot) in order
  to try to have different (better?) results.