Table 4.
LISA detection rates obtained by several other groups and methods.
| Reference | Type | Basis | Seeds [M⊙] | Binary evolution | Detection rate [1/yr] |
|---|---|---|---|---|---|
| This work | SAM | SURFs | 103−5 | None | ∼7−68 |
| Barausse et al. (2020) | SAM | ePS | 300, 105 | DF, SH, G, Tri, GW | ∼4−322 |
| Dayal et al. (2019) | SAM | SAM | 150, 103−5 | None | ∼3−6 |
| Sesana et al. (2011) | SAM | ePS | 100, 104 | None | ∼25 |
| Bonetti et al. (2019) | SAM | ePS | 300, 105 | DF, SH, G, Tri, GW | ∼12−75 |
| Salcido et al. (2016) | HD | EAGLE | 104−5 | GAL | ∼2 |
| Katz et al. (2020) | HD | Illustris | 105 | DF, SH, G, GW | ∼0.5−1 |
Notes. In Dayal et al. (2019) rates are calculated only for mergers at z > 4. Bonetti et al. (2019) and Barausse et al. (2020) use the same formalism for seed formation, i.e., defining the instability of protogalactic disks given the Toomre parameter QC, but using a different threshold value (QC equal to either 2.5 or 3, respectively, where a higher value corresponds to more seeds being produced). Binary evolution models: DF (dynamical friction), SH (stellar hardening), G (gas induced migration), Tri (triple interactions), GAL (galaxy gas properties), GW (gravitational waves). The third column lists types of used DM merger trees: ePS (Extended Press-Schechter algorithm; Press & Schechter 1974; Parkinson et al. 2008, EAGLE Crain et al. 2015; Schaye et al. 2015, Illustris Vogelsberger et al. 2014). Each cited work uses a different set of prescriptions for BH growth and feedback, but we do not include all references in the summary as such comparison is beyond the scope of this paper.
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