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In the near future, projects like LISA and Pulsar Timing Arrays are expectedto detect gravitational waves from mergers between supermassive black holes,and it is crucial to precisely model the underlying merger populations now tomaximize what we can learn from this new data. Here we characterize expectedhigh-redshift (z > 2) black hole mergers using the very large volume Astridcosmological simulation, which uses a range of seed masses to probe down tolow-mass BHs, and directly incorporates dynamical friction so as to accuratelymodel the dynamical processes which bring black holes to the galaxy centerwhere binary formation and coalescence will occur. The black hole populationsin Astrid include black holes down to 10$^{4.5}$ M$_\odot$, and remain broadlyconsistent with the TNG simulations at scales > 10$^6$ M$_\odot$ (the seed massused in TNG). By resolving lower-mass black holes, the overall merger rate is~5x higher than in TNG. However, incorporating dynamical friction delaysmergers compared to a recentering scheme, reducing the high-z merger ratemass-matched mergers by a factor of ~2x. We also calculate the expected LISASignal-to-Noise values, and show that the distribution peaks at high SNR(>100), emphasizing the importance of implementing a seed mass well belowLISA's peak sensitivity (10$^6$ M$_\odot$) to resolve the majority of LISA's GWdetections.

High-redshift supermassive black hole mergers in simulations with dynamical friction modelling