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Published September 2022 | public
Journal Article

The observability of galaxy merger signatures in nearby gas-rich spirals

Abstract

Galaxy mergers are crucial to understanding galaxy evolution, therefore we must determine their observational signatures to select them from large IFU galaxy samples such as MUSE and SAMI. We employ 24 high-resolution idealized hydrodynamical galaxy merger simulations based on the 'Feedback In Realistic Environment' (FIRE-2) model to determine the observability of mergers to various configurations and stages using synthetic images and velocity maps. Our mergers cover a range of orbital configurations at fixed 1:2.5 stellar mass ratio for two gas rich spirals at low redshift. Morphological and kinematic asymmetries are computed for synthetic images and velocity maps spanning each interaction. We divide the interaction sequence into three: (1) the pair phase; (2) the merging phase; and (3) the post-coalescence phase. We correctly identify mergers between first pericentre passage and 500 Myr after coalescence using kinematic asymmetry with 66 per cent completeness, depending upon merger phase and the field of view of the observation. We detect fewer mergers in the pair phase (40 per cent) and many more in the merging and post-coalescence phases (97 per cent). We find that merger detectability decreases with field of view, except in retrograde mergers, where centrally concentrated asymmetric kinematic features enhances their detectability. Using a cut-off derived from a combination of photometric and kinematic asymmetry, we increase these detections to 89 per cent overall, 79 per cent in pairs, and close to 100 per cent in the merging and post-coalescent phases. By using this combined asymmetry cut-off we mitigate some of the effects caused by smaller fields of view subtended by massively multiplexed integral field spectroscopy programmes.

Additional Information

RM acknowledges and pays respect to the Gadigal people of the Eora Nation, upon whose unceded, sovereign, ancestral lands the University of Sydney is built; and the traditional owners of the land on which the University of Queensland is situated, the Turrbal and Jagera people. We pay respects to their Ancestors and descendants, who continue cultural and spiritual connections to Country. RM and SC acknowledge the support of the Australian Research Council [Grant ID: DP190102714]. RM also acknowledges the support of a University of Queensland Postdoctoral Fellowship. The computations in this paper were partly run on the Odyssey cluster supported by the FAS Division of Science, Research Computing Group at Harvard University. CB acknowledges support from the Natural Science and Engineering Council of Canada (NSERC) [funding reference number PDF-546234-2020]. MHH gratefully acknowledges support from the William and Caroline Herschel Postdoctoral Fellowship fund. Support for JM is provided by the National Science Foundation (NSF) (AST Award Number 1516374), and by the Harvard Institute for Theory and Computation, through their Visiting Scholars Program. The computations in this paper were run on the Odyssey cluster supported by the FAS Division of Science, Research Computing Group at Harvard University. Support for JM is provided by the NSF (AST Award Number 1516374), the Grace Steele Foundation, and Downing College. RF acknowledges financial support from the Swiss National Science Foundation (grant no 194814). BH greatly appreciates financial support from the Deutsche Forschungsgemeinschaft (DFG) via grant GE625/17-1. CCH acknowledges that the Flatiron Institute is supported by the Simons Foundation.

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023