Multiband Probabilistic Cataloging: A Joint Fitting Approach to Point Source Detection and Deblending. (arXiv:1907.04929v1 [astro-ph.IM])

Multiband Probabilistic Cataloging: A Joint Fitting Approach to Point Source Detection and Deblending. (arXiv:1907.04929v1 [astro-ph.IM])
<a href="http://arxiv.org/find/astro-ph/1/au:+Feder_R/0/1/0/all/0/1">Richard M. Feder</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Portillo_S/0/1/0/all/0/1">Stephen K. N. Portillo</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Daylan_T/0/1/0/all/0/1">Tansu Daylan</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Finkbeiner_D/0/1/0/all/0/1">Douglas Finkbeiner</a>

Probabilistic cataloging (PCAT) outperforms traditional cataloging methods on
single-band optical data in crowded fields (Portillo et al. 2017). We extend
our work to multiple bands, achieving greater sensitivity ($sim$ 0.4 mag) and
greater speed (500x) compared to previous single-band results. We demonstrate
the effectiveness of multiband PCAT on mock data, both in terms of recovering
accurate posteriors in the catalog space, and in directly deblending sources.
When applied to Sloan Digital Sky Survey (SDSS) observations of M2, taking
Hubble Space Telescope data as truth, our joint fit on $r$ and $i$ band data
goes $sim0.4$ mag deeper than single-band probabilistic cataloging and has a
false discovery rate less than 20% for F606W$leq 20$. Compared to DAOPHOT,
the two-band SDSS catalog fit goes nearly 1.5 magnitudes deeper using the same
data, and maintains a lower false discovery rate down to F606W$sim 20.5$.
Given recent improvements in computational speed, multiband PCAT shows promise
in application to large-scale surveys and is a plausible framework for joint
analysis of multi-instrument observational data.

Probabilistic cataloging (PCAT) outperforms traditional cataloging methods on
single-band optical data in crowded fields (Portillo et al. 2017). We extend
our work to multiple bands, achieving greater sensitivity ($sim$ 0.4 mag) and
greater speed (500x) compared to previous single-band results. We demonstrate
the effectiveness of multiband PCAT on mock data, both in terms of recovering
accurate posteriors in the catalog space, and in directly deblending sources.
When applied to Sloan Digital Sky Survey (SDSS) observations of M2, taking
Hubble Space Telescope data as truth, our joint fit on $r$ and $i$ band data
goes $sim0.4$ mag deeper than single-band probabilistic cataloging and has a
false discovery rate less than 20% for F606W$leq 20$. Compared to DAOPHOT,
the two-band SDSS catalog fit goes nearly 1.5 magnitudes deeper using the same
data, and maintains a lower false discovery rate down to F606W$sim 20.5$.
Given recent improvements in computational speed, multiband PCAT shows promise
in application to large-scale surveys and is a plausible framework for joint
analysis of multi-instrument observational data.

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