Blind Detection of Ultrafaint Streaks with a Maximum Likelihood … · Real GEO Data: PSF convolved...
Transcript of Blind Detection of Ultrafaint Streaks with a Maximum Likelihood … · Real GEO Data: PSF convolved...
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LLNL-PRES-692194 This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. Lawrence Livermore National Security, LLC
Blind Detection of Ultrafaint Streaks with a Maximum Likelihood MethodCASIS
Dawson (LLNL), Schneider (LLNL), and Kamath (LLNL)
18 May 2016
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Real Data GEO
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Real GEO Data: PSF convolved detection seems to work very well.
• Consistently detects streaks and stars
• Star/streak separation based off multivariate Gaussian fit
Three streaks.
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Real Data LEO
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PSF convolved detection worked in some cases
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Failed on some LEO data
• Shorter exposures = lower SNR = detection “issues”
• Many fainter streaks that could be seen by eye were not detected
Failed to detect this streak.
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Maximum Likelihood Detection
lnL (x, ✓) = � 12 [d(x)�m(x, ✓)]T ⌃�1 [d(x)�m(x, ✓)] + C
m(x, ✓) =
Zs(x, ✓)�(x)dx
m(x, ✓) = ↵µ(x,⇥)
�(x,⇥) = µ(x,⇥)T⌃�1µ(x,⇥)
(x,⇥) = d(x)T⌃�1µ(x,⇥)
Work with Jim Bosch and Michael Schneider
@lnL@↵
= ↵�(x,⇥)� (x,⇥) = 0 ↵ML = (x,⇥)
�(x,⇥)lnLML =
2(x,⇥)
2�(x,⇥)⌫(x,⇥) =
(x,⇥)p�(x,⇥)
source model convolved with PSF
Log likelihood
separate the flux from the other model parameters
noise weighted model auto-correlation
noise weighted data-model cross-correlation
Significance
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Faint Source Pipeline: Tests on Simulated Data
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Testing detection pipeline on faint simulated streakStreak just to left of black line.• Create simulated image with 4 high SNR stars
and one faint streak.
• Convolve image with initial PSF guess. This creates image
• Estimate (currently constant across image), and combine with for
• Detect sources in image above a SNR threshold (footprints)
• Star/streak separation, estimate PSF, repeat above with more accurate PSF.
• Mask detected footprints in image
• Convolve image with streak model (i.e. line), and repeat detection process. ( )
�PSF
⌫PSF
PSF
PSF
PSF
PSF ⌫PSF
⌫streaki
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Testing detection pipeline on faint simulated streak• Create simulated image with 4 high SNR stars
and one faint streak.
• Convolve image with initial PSF guess. This creates image
• Estimate (currently constant across image), and combine with for
• Detect sources in image above a SNR threshold (footprints)
• Star/streak separation, estimate PSF, repeat above with more accurate PSF.
• Mask detected footprints in image
• Convolve image with streak model (i.e. line), and repeat detection process. ( )
�PSF
⌫PSF
PSF
PSF
PSF
PSF ⌫PSF
⌫streaki
Can just start to make out streak.
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Testing detection pipeline on faint simulated streak• Create simulated image with 4 high SNR stars
and one faint streak.
• Convolve image with initial PSF guess. This creates image
• Estimate (currently constant across image), and combine with for
• Detect sources in image above a SNR threshold (footprints)
• Star/streak separation, estimate PSF, repeat above with more accurate PSF.
• Mask detected footprints in image
• Convolve image with streak model (i.e. line), and repeat detection process. ( )
�PSF
⌫PSF
PSF
PSF
PSF
PSF ⌫PSF
⌫streaki
Point sources detected at high significance but streak below
threshold, SRN < 5.
Sign
al to
Noi
se R
atio
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Testing detection pipeline on faint simulated streak• Create simulated image with 4 high SNR stars
and one faint streak.
• Convolve image with initial PSF guess. This creates image
• Estimate (currently constant across image), and combine with for
• Detect sources in image above a SNR threshold (footprints)
• Star/streak separation, estimate PSF, repeat above with more accurate PSF.
• Mask detected footprints in image
• Convolve image with streak model (i.e. line), and repeat detection process. ( )
�PSF
⌫PSF
PSF
PSF
PSF
PSF ⌫PSF
⌫streaki
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Testing detection pipeline on faint simulated streak• Create simulated image with 4 high SNR stars
and one faint streak.
• Convolve image with initial PSF guess. This creates image
• Estimate (currently constant across image), and combine with for
• Detect sources in image above a SNR threshold (footprints)
• Star/streak separation, estimate PSF, repeat above with more accurate PSF.
• Mask detected footprints in image
• Convolve image with streak model (i.e. line), and repeat detection process. ( )
�PSF
⌫PSF
PSF
PSF
PSF
PSF ⌫PSF
⌫streaki
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Iteratively determine the Maximum Likelihood Model (major room for computational optimization but fundamental method solid)
Streak now detected at high significance!
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Faint Source Pipeline: Tests on Real Data
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After worked on real data with faint streaks we ran it on an image with no apparent streak.
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Nothing in the PSF convolved image.⌫PSF No “footprints” with SNR > 5
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After running iterative maximum likelihood search… found a very faint but significant streak!⌫PSF
Detected FootprintSignificant Streak