Paper detail

A Physical Approach to the Identification of High-z Mergers: Morphological Classification in the Stellar Mass Domain

At z>1, the distinction between merging and 'normal' star-forming galaxies based on single band morphology is often hampered by the presence of large clumps which result in a disturbed, merger-like appearance even in rotationally supported disks. In this paper we discuss how a classification based on canonical, non-parametric structural indices measured on resolved stellar mass maps, rather than on single-band images, reduces the misclassification of clumpy but not merging galaxies. We calibrate the mass-based selection of mergers using the MIRAGE hydrodynamical numerical simulations of isolated and merging galaxies which span a stellar mass range of $10^{9.8}$-$10^{10.6}M_{sun}$ and merger ratios between 1:1-1:6.3. These simulations are processed to reproduce the typical depth and spatial resolution of observed HUDF data. We test our approach on a sample of real z~2 galaxies with kinematic classification into disks or mergers and on ~100 galaxies in the HUDF field with photometric/spectroscopic redshift between 1.5$\leqslant z \leqslant$3 and $M>10^{9.4}M_{sun}$. We find that a combination of the asymmetry $A_{MASS}$ and $M_{20, MASS}$ indices measured on the stellar mass maps can efficiently identify real (major) mergers with $\lesssim$20% contamination from clumpy disks in the merger sample. This mass-based classification cannot be reproduced in star-forming galaxies by $H-$band measurements alone, which instead result in a contamination from clumpy galaxies that can be as high as 50%. Moreover, we find that the mass-based classification always results in a lower contamination from clumpy galaxies than an $H-$band classification, regardless of the depth of the imaging used (e.g., CANDELS vs. HUDF).

preprint2015arXivOpen access

Signal facts

What is known right now

Open access9 authors2 topics

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.