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tokens: between 10 10 and 10 11 M ⊙ . McCarthy et al. ( 2020 ) also use an analytic model, but paired with SDSS observations to explore the host galaxy mass function along with other host observables. For the host galaxy mass function, our results are consistent with theirs. However, our larger range of DTDs presented in Figure 2 reveals the large spread between different assumed DTDs and the stable peak near 10 10.5 M ⊙ . Adhikari et al. ( 2020 ) also find that other host observables paired with stellar mass are necessary to obtain a better understanding where BNSs merge. Overall, we find that future explorations of this topic will need to consider a wide range of DTDs and the full range of the observable in question. While the work we present here continues our understanding of what we can learn from observations of BNS host galaxies, further investigations are necessary to fully understand how BNSs form and evolve. One example of such an investigation is to expand the set of DTDs examined using the methods in this paper. The set of DTDs we examine is broad, covering those most commonly referenced (e.g., Eldridge Stanway 2016 ; Safarzadeh Berger 2019 ), but we do not exhaustively search the full range of DTDs proposed (e.g., Dominik et al. 2012 ; Simonetti et al. 2019 ). Also, our convolution of IllustrisTNG’s SFRH with our DTDs does not include any form of natal kicks. If these kicks are strong enough to dislodge the binary from smaller galaxies, it is possible that their addition would weight the host mass functions toward higher-mass galaxies. With a greater range of DTDs examined and a more detailed convolution, we will gain a clearer picture of where BNS mergers are located, which delay times can be distinguished using the host galaxy mass function, and the most likely places they will be observed. Another way to incorporate a more complete set of DTDs would be to use a varied set of population synthesis models that cover a wide range of binary separations, kick velocities, initial mass functions, etc. Including other star formation histories could also provide a more detailed look at the spread in possible host galaxy mass functions. While IllustrisTNG is broadly consistent with the cosmic SFR density and redshift-dependent galaxy stellar mass functions (Pillepich et al. 2018a ), its accuracy should not be overinterpreted, and different simulations will surely produce somewhat varied star formation histories that could impact our results. However, we can say that up to their mass cutoff our results align with those of Artale et al. ( 2019 ), who found no significant difference when comparing results from Illustris and Eagle. The lack of variation in Artale et al. ( 2019 ) most likely indicates that—while there is some variation—the SFRHs in Illustris and EAGLE are sufficiently similar to not significantly impact the results. Thus, by adopting the SFRHs from galaxy formation simulations and assumptions about the functional form of the DTD,