Far-Infrared Photometric Redshifts: A New Approach to a Highly Uncertain Enterprise
arXiv:2007.11012 · doi:10.3847/1538-4357/aba528
Abstract
I present a new approach at deriving far-infrared photometric redshifts for galaxies based on their reprocessed emission from dust at rest-frame far-infrared through millimeter wavelengths. Far-infrared photometric redshifts ("FIR-") have been used over the past decade to derive redshift constraints for highly obscured galaxies that lack photometry at other wavelengths like the optical/near-infrared. Most literature FIR-z fits are performed through minimization to a single galaxy's far-infrared template spectral energy distribution (SED). The use of a single galaxy template, or modest set of templates, can lead to an artificially low uncertainty estimate on FIR-'s because real galaxies display a wide range in intrinsic dust SEDs. I use the observed distribution of galaxy SEDs (for well-constrained samples across ) to motivate a new far-infrared through millimeter photometric redshift technique called MMpz. The MMpz algorithm asserts that galaxies are most likely drawn from the empirically observed relationship between rest-frame peak wavelength, , and total IR luminosity, L; the derived photometric redshift accounts for the measurement uncertainties and intrinsic variation in SEDs at the inferred L, as well as heating from the CMB at . The MMpz algorithm has a precision of , similar to single-template fits, while providing a more accurate estimate of the FIR- uncertainty with reduced chi-squared of order , compared to alternative far-infrared photometric redshift techniques (with ).
12 pages, 4 figures; accepted for publication in ApJ. For associated code, see http://www.as.utexas.edu/~cmcasey/mmpz.html
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