Catalog Service: Emission-line strengths for 129 galaxies
Description
We propose a method to substantially increase the flexibility and power of template fitting-based photometric redshifts by transforming a large number of galaxy spectral templates into a corresponding collection of 'fuzzy archetypes' using a suitable set of perturbative priors designed to account for empirical variation in dust attenuation and emission-line strengths. To bypass widely separated degeneracies in parameter space (e.g. the redshift-reddening degeneracy), we train self-organizing maps (SOMs) on large 'model catalogues' generated from Monte Carlo sampling of our fuzzy archetypes to cluster the predicted observables in a topologically smooth fashion. Subsequent sampling over the SOM then allows full reconstruction of the relevant probability distribution functions (PDFs). This combined approach enables the multimodal exploration of known variation among galaxy spectral energy distributions with minimal modelling assumptions. We demonstrate the power of this approach to recover full redshift PDFs using discrete Markov chain Monte Carlo sampling methods combined with SOMs constructed from Large Synoptic Survey Telescope ugrizY and Euclid YJH mock photometry.
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Publisher: CDSivo://CDS[Pub. ID]
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This resource was registered on: 2020 Apr 21 15:23:44ZThis resource description was last updated on: 2021 Oct 21 00:00:00Z
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This is service that does not comply with any IVOA standard but instead provides access to special capabilities specific to this resource.
This is a standard IVOA service that takes as input an ADQL or PQL query and returns tabular data.
This is a standard IVOA service that takes as input a position in the sky and a radius and returns catalog records with positions within that radius.
Cone search capability for table J/MNRAS/469/1186/tablea1 (Emission-line strengths for the 129 Brown et al. (2014, Cat. J/ApJS/212/18) templates)
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Developed with the support of the National Science Foundation under Cooperative Agreement AST0122449 with the Johns Hopkins University The NAVO project is a member of the International Virtual Observatory Alliance
This NAVO Application is hosted by the Space Telescope Science Institute