Kavli Affiliate: Philip J. Marshall
| First 5 Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
| Summary:
We present STARRED, a Point Spread Function (PSF) reconstruction, two-channel
deconvolution, and light curve extraction method designed for high-precision
photometric measurements in imaging time series. An improved resolution of the
data is targeted rather than an infinite one, thereby minimizing deconvolution
artifacts. In addition, STARRED performs a joint deconvolution of all available
data, accounting for epoch-to-epoch variations of the PSF and decomposing the
resulting deconvolved image into a point source and an extended source channel.
The output is a deep sharp frame combining all data, and the photometry of all
point sources in the field of view as a function of time. Of note, STARRED also
provides exquisite PSF models for each data frame. We showcase three
applications of STARRED in the context of the imminent LSST survey and of JWST
imaging: i) the extraction of supernovae light curves and the scene
representation of their host galaxy, ii) the extraction of lensed quasar light
curves for time-delay cosmography, and iii) the measurement of the spectral
energy distribution of globular clusters in the "Sparkler", a galaxy at
redshift z=1.378 strongly lensed by the galaxy cluster SMACS J0723.3-7327.
STARRED is implemented in JAX, leveraging automatic differentiation and GPU
acceleration. This enables rapid processing of large time-domain datasets,
positioning the method as a powerful tool for extracting light curves from the
multitude of lensed or unlensed variable and transient objects in the
Rubin-LSST data, even when blended with intervening objects.
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