Automated detection of merging galaxies at z = 0.25 − 1.0 in the CLAUDS+HSC survey using random forests

Show simple item record

dc.contributor.advisor Sawicki, Marcin, 1969-
dc.creator Thibert, Nathalie C. M.
dc.date.accessioned 2018-09-19T14:13:14Z
dc.date.available 2018-09-19T14:13:14Z
dc.date.issued 2018
dc.identifier.other QB857.5 M47 T48 2018
dc.identifier.uri http://library2.smu.ca/handle/01/27980
dc.description x, 190 leaves : colour illustrations ; 29 cm
dc.description Includes abstract and appendix.
dc.description Includes bibliographical references (leaves 135-142).
dc.description.abstract Using a sample of galaxies (M⋆ &ge; 10<sup>10.5</sup>M<sub>⊙</sub>) covering an effective area of &sim; 20 deg<sup>2</sup> in the CLAUDS+HSC survey, we apply a Random Forest Classifier to automatically identify merger candidates in deep r-band images. We identify a largely pure, &sim; 90% complete sample of mergers which we use to derive the evolution in the merger fraction from 0.25 &le; z<sub>phot</sub> &le; 1.0. We parameterize the merger fraction evolution with a power law of the form f<sub>m</sub> = f<sub>0</sub>(1+z)<sup>m</sup> . Simulating the effects of increasing redshift on the detectability of mergers, we correct our merger fractions for incompleteness to obtain a local merger fraction of f<sub>0</sub> = 1.0%&plusmn;0.2% and power-law index of m = 2.3&plusmn;0.4, which is inconsistent with the mild or non-evolving merger scenario (m &lt; 1.5) with 96.6% confidence. Finally, we estimate 0.3 merging events to occur per massive galaxy since z = 1. en_CA
dc.description.provenance Submitted by Greg Hilliard (greg.hilliard@smu.ca) on 2018-09-19T14:13:14Z No. of bitstreams: 1 Thibert_Nathalie_MASTERS_2018.pdf: 29061366 bytes, checksum: 7bcd69d3174a869a2f34f9f3e825f5b4 (MD5) en
dc.description.provenance Made available in DSpace on 2018-09-19T14:13:14Z (GMT). No. of bitstreams: 1 Thibert_Nathalie_MASTERS_2018.pdf: 29061366 bytes, checksum: 7bcd69d3174a869a2f34f9f3e825f5b4 (MD5) Previous issue date: 2018-08-23 en
dc.language.iso en en_CA
dc.publisher Halifax, N.S. : Saint Mary's University
dc.subject.lcc QB857.5.M47
dc.subject.lcsh Galaxy mergers
dc.subject.lcsh Galaxies -- Evolution
dc.title Automated detection of merging galaxies at z = 0.25 − 1.0 in the CLAUDS+HSC survey using random forests en_CA
dc.type Text en_CA
thesis.degree.name Master of Science in Astronomy
thesis.degree.level Masters
thesis.degree.discipline Astronomy and Physics
thesis.degree.grantor Saint Mary's University (Halifax, N.S.)
 Find Full text

Files in this item

 
 

This item appears in the following Collection(s)

Show simple item record