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. 

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