Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction

Research output: Contribution to journalJournal articlepeer-review

Our understanding of galaxy evolution is derived from large surveys designed to maximize efficiency by only observing the minimum amount needed to infer properties for a typical galaxy. However, for a few percent of galaxies in every survey, these observations are insufficient and derived properties can be catastrophically wrong. Further, it is currently difficult or impossible to determine which objects have failed, so that these contaminate every study of galaxy properties. We develop a novel method to identify these objects by combining the astronomical codes that infer galaxy properties with the dimensionality reduction algorithm t-SNE, which groups similar objects to determine which inferred properties are out of place. This method provides an improvement for the COSMOS catalog, which already uses existing techniques for catastrophic error removal, and therefore should improve the quality of large catalogs and any studies that are sensitive to large redshift errors.

Original languageEnglish
Article number148
JournalAstrophysical Journal
Volume908
Issue number2
Number of pages8
ISSN0004-637X
DOIs
Publication statusPublished - Feb 2021

    Research areas

  • Astronomy data analysis, Redshift surveys, High-redshift galaxies, Photometry, Dimensionality reduction, Galaxy properties

Links

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