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PSF Photometry for Kepler and K2 Data

Zé Vinícius
November 06, 2017

PSF Photometry for Kepler and K2 Data

Talk given at the PSF Photometry and Software Workshop, Space Telescope Science Institute, Baltimore, 2017.

Zé Vinícius

November 06, 2017
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  1. PSF Photometry for Kepler/K2 data Geert Barentsen Z´ e Vin´

    ıcius http://keplerscience.arc.nasa.gov Space Telescope Science Institute, Baltimore November 6, 2017
  2. K2 Guest Observer Office + Ben Montet Geert Barentsen Michael

    Gully Ann Marie Cody Christina Hedges Z´ e Vin´ ıcius Ben Montet 1
  3. PSF Photometry of Multiple Overlapping Stars • Data: single image,

    time-series of images, etc... • Parameters: θ(1) = x(1) 0 , y(1) 0 , F(1), B ... θ(K) = x(K) 0 , y(K) 0 , F(K), B That’s a total of 3K + 1 parameters! 2
  4. PSF Photometry of Multiple Overlapping Stars • Data: single image,

    time-series of images, etc... • Parameters: θ(1) = x(1) 0 , y(1) 0 , F(1), B ... θ(K) = x(K) 0 , y(K) 0 , F(K), B That’s a total of 3K + 1 parameters! • Model: PSF x, y, θ(k) = F(k)h x − x(k), y − y(k) + B K 2
  5. PSF Photometry of Multiple Overlapping Stars • Data: single image,

    time-series of images, etc... • Parameters: θ(1) = x(1) 0 , y(1) 0 , F(1), B ... θ(K) = x(K) 0 , y(K) 0 , F(K), B That’s a total of 3K + 1 parameters! • Model: PSF x, y, θ(k) = F(k)h x − x(k), y − y(k) + B K • Objective: θ = arg min θ∈Θ x,y dataxy − k PSF x, y, θ(k) 2 2
  6. DAOPHOT-like PSF Photometry stars = find(image) // DAOFIND while len(stars)

    > 0: groups = group(stars) // DBSCAN fitted_groups = fit(groups, model) 3
  7. DAOPHOT-like PSF Photometry stars = find(image) // DAOFIND while len(stars)

    > 0: groups = group(stars) // DBSCAN fitted_groups = fit(groups, model) residual = subtract(image, fitted_groups) 3
  8. DAOPHOT-like PSF Photometry stars = find(image) // DAOFIND while len(stars)

    > 0: groups = group(stars) // DBSCAN fitted_groups = fit(groups, model) residual = subtract(image, fitted_groups) stars = find(residual) 3
  9. DAOPHOT-like PSF Photometry stars = find(image) // DAOFIND while len(stars)

    > 0: groups = group(stars) // DBSCAN fitted_groups = fit(groups, model) residual = subtract(image, fitted_groups) stars = find(residual) 3