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Describe the process of "detection", or finding objects in individual PanSTARRS exposures, and the quantities associated with a detection. Detections are combined into "objects" by spatial matching across different exposures and filters.
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Definition - what is a "detection"?
In PanSTARRS lingo, a detection is a source found in a specific exposure. Detections are matched across exposures to define "objects".
Detections are identified through a standard peak-finding algorithm. The image is convolved with an approximation of the PSF and then divided by a smoothed version of the variance image to define the significance image. Peaks are defined as locations where the significance image exceeds a target threshold, representing the square of the desired signal-to-noise ratio. Peaks are then ordered in decreasing significance, and peaks are retained only if a significant valley separates them from brighter nearby peaks.
The process of identifying detections is complex and involves multiple steps.
- Smooth Image with PSF (or guess in first pass)
- Smooth Variance with PSF2
- (Actually, I cheat & use a 1D Gaussian with FWHM matching PSF)
- much faster, marginal difference
- if the difference matters, image is quite poor quality
- Significance image by dividing image2 / variance
- Find all peaks above target S/N (squared)
- Footprint analysis
- generate isophotal footprint outlines (N sigma above sky)
- assign peaks to their containing footprints
- cull insignificant peaks
- cull in descending brightness order
- valid peak must be separated from a brighter peak by a significant valley
- recent fix : on second pass, cull on the unsubtracted image
PSF Photometry
PSF fitting
Photometric zero points
Aperture Photometry
Kron Photometry
image smoothing, sky level, measuring moments, aperture size, iterations
Forced Photometry
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