The Toomre Sequence Revisited with HST/NICMOS: Nuclear Brightness Profiles and Colors of Interacting and Merging Galaxies
Joern Rossa (University of Florida), Seppo Laine (Spitzer Science, Center, Caltech), Roeland P. van der Marel (STScI), J. Christopher Mihos, (CWRU), John E. Hibbard (NRAO), Torsten Boeker (ESA/RSSD), Ann I. Zabludoff, (University of Arizona)

TL;DR
This study uses high-resolution near-infrared imaging from HST/NICMOS to analyze the nuclear brightness profiles and colors of merging galaxies in the Toomre sequence, revealing trends in luminosity and dust dispersal related to merger stages.
Contribution
It provides new high-resolution near-infrared data on merging galaxy nuclei, showing how their brightness and color profiles evolve with merger progression, and compares these to early-type galaxies.
Findings
Nuclei become more luminous with merger stage after dust correction.
Nuclei tend to become bluer as mergers progress, indicating dust dispersal.
Most nuclei have steep, power-law brightness profiles, steeper than typical E/S0 galaxies.
Abstract
We discuss the near-infrared properties of the nuclei in the 11 merging galaxies of the Toomre sequence, based on high spatial resolution J, H, and K imaging data using NICMOS onboard the Hubble Space Telescope (HST). The observations are less affected by dust extinction than our previous HST/WFPC2 observations and offer higher spatial resolution than existing ground-based near-IR data. We see a marginal trend for the nuclei to become bluer with advancing merger stage, which we attribute to a dispersal of dust at late times in the merging process. Our data also indicate a statistically significant trend for the nuclei in the sequence to become more luminous, within an aperture of fixed physical size and after correcting for dust extinction, with advancing merger stage. We derive K-band surface brightness profiles for those nuclei for which the morphology allows a meaningful isophotal…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
