Beyond the best-fit parameter: new insight on galaxy structure decomposition from GALPHAT

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dc.creatorYoon, Ilsang
dc.creatorWeinberg, Martin
dc.creatorKatz, Neal
dc.date2009-02-04
dc.date.accessioned2026-07-07T12:38:10Z
dc.date.available2026-07-07T12:38:10Z
dc.descriptionWe introduce a novel image decomposition package, GALPHAT, that provides robust estimates of galaxy surface brightness profiles using Bayesian Markov Chain Monte Carlo. The GALPHAT-determined posterior distribution of parameters enables us to assign rigorous statistical confidence intervals to maximum a posteriori estimates and to test complex galaxy formation and evolution hypotheses. We describe the GALPHAT algorithm, assess its performance using test image data, and demonstrate that it has sufficient speed for production analysis of a large galaxy sample. Finally we briefly introduce our ongoing science program to study the distribution of galaxy structural properties in the local universe using GALPHAT.
dc.descriptionTo appear in the proceedings of "Galaxy Evolution: Emerging Insights and Future Challenges", Shardha Jogee, Lei Hao, Guillermo Blanc, Irina Marinova, eds., ASP Conference Series
dc.identifierhttps://arxiv.org/abs/0902.0816
dc.identifierhttp://arxiv.org/abs/0902.0816
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/218664
dc.subjectCosmology and Nongalactic Astrophysics
dc.subjectInstrumentation and Methods for Astrophysics
dc.titleBeyond the best-fit parameter: new insight on galaxy structure decomposition from GALPHAT
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