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