Characterizing tidal features around galaxies in cosmological simulations

A. Khalid, S. Brough, G. Martin, L. C. Kimmig, C. D.P. Lagos, R. S. Remus, C. Martinez-Lombilla

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Tidal features provide signatures of recent mergers and offer a unique insight into the assembly history of galaxies. The Vera C. Rubin Observatory's Le gac y Surv e y of Space and Time (LSST) will enable an unprecedentedly large surv e y of tidal features around millions of galaxies. To decipher the contributions of mergers to galaxy evolution it will be necessary to compare the observed tidal features with theoretical predictions. Therefore, we use cosmological hydrodynamical simulations NEWHORIZON, EAGLE, ILLUSTRISTNG, and MAGNETICUM to produce LSST-like mock images of z ~0 galaxies (z ~0.2 for NEWHORIZON ) with M∗,30 pkpc ≥109.5 M⊙. We perform a visual classification to identify tidal features and classify their morphology. We find broadly good agreement between the simulations regarding their overall tidal feature fractions: fNEWHORIZON = 0.40 ±0.06, fEAGLE = 0.37 ±0.01, fTNG = 0.32 ±0.01, and fMAGNETICUM = 0.32 ±0.01, and their specific tidal feature fractions. Furthermore, we find e xcellent agreement re garding the trends of tidal feature fraction with stellar and halo mass. All simulations agree in predicting that the majority of central galaxies of groups and clusters exhibit at least one tidal feature, while the satellite members rarely show such features. This agreement suggests that gravity is the primary driver of the occurrence of visually identifiable tidal features in cosmological simulations, rather than subgrid physics or hydrodynamics. All predictions can be verified directly with LSST observations.

Original languageEnglish
Pages (from-to)4422-4445
Number of pages24
JournalMonthly Notices of the Royal Astronomical Society
Volume530
Issue number4
DOIs
Publication statusPublished - 1 Jun 2024

Funding

FundersFunder number
ARC Australian Research Council CE170100013, DP190101943

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