Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction. / Hovis-Afflerbach, Beryl; Steinhardt, Charles L.; Masters, Daniel; Salvato, Mara.

In: Astrophysical Journal, Vol. 908, No. 2, 148, 02.2021.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Hovis-Afflerbach, B, Steinhardt, CL, Masters, D & Salvato, M 2021, 'Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction', Astrophysical Journal, vol. 908, no. 2, 148. https://doi.org/10.3847/1538-4357/abd329

APA

Hovis-Afflerbach, B., Steinhardt, C. L., Masters, D., & Salvato, M. (2021). Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction. Astrophysical Journal, 908(2), [148]. https://doi.org/10.3847/1538-4357/abd329

Vancouver

Hovis-Afflerbach B, Steinhardt CL, Masters D, Salvato M. Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction. Astrophysical Journal. 2021 Feb;908(2). 148. https://doi.org/10.3847/1538-4357/abd329

Author

Hovis-Afflerbach, Beryl ; Steinhardt, Charles L. ; Masters, Daniel ; Salvato, Mara. / Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction. In: Astrophysical Journal. 2021 ; Vol. 908, No. 2.

Bibtex

@article{541e3e6420a4464d856577b1c86abcd4,
title = "Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction",
abstract = "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.",
keywords = "Astronomy data analysis, Redshift surveys, High-redshift galaxies, Photometry, Dimensionality reduction, Galaxy properties",
author = "Beryl Hovis-Afflerbach and Steinhardt, {Charles L.} and Daniel Masters and Mara Salvato",
year = "2021",
month = feb,
doi = "10.3847/1538-4357/abd329",
language = "English",
volume = "908",
journal = "Astrophysical Journal",
issn = "0004-637X",
publisher = "Institute of Physics Publishing, Inc",
number = "2",

}

RIS

TY - JOUR

T1 - Identifying and Repairing Catastrophic Errors in Galaxy Properties Using Dimensionality Reduction

AU - Hovis-Afflerbach, Beryl

AU - Steinhardt, Charles L.

AU - Masters, Daniel

AU - Salvato, Mara

PY - 2021/2

Y1 - 2021/2

N2 - 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.

AB - 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.

KW - Astronomy data analysis

KW - Redshift surveys

KW - High-redshift galaxies

KW - Photometry

KW - Dimensionality reduction

KW - Galaxy properties

U2 - 10.3847/1538-4357/abd329

DO - 10.3847/1538-4357/abd329

M3 - Journal article

VL - 908

JO - Astrophysical Journal

JF - Astrophysical Journal

SN - 0004-637X

IS - 2

M1 - 148

ER -

ID: 259107258