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Arxiv: Reconciling PTA and JWST and preparing for LISA with POMPOCO: a Parametrisation Of the Massive black hole POpulation for Comparison to Observations Published: 10/23/2024 5:34:15 PM Updated: 11/19/2024 12:26:22 AM
Paper abstract: We develop a parametrised model to describe the formation and evolution ofmassive black holes, designed for comparisons with both electromagnetic andgravitational wave observations. Using an extended Press-Schechter formalism,we generate dark matter halo merger trees. We then seed and evolve massiveblack holes through parameterised prescriptions. This approach, which avoidssolving differential equations, is computationally efficient, enabling us toanalyse observational data and infer the parameters of our model in a fullyBayesian framework. We find that observations of the black hole luminosityfunction are compatible with the nHz gravitational wave signal (likely)measured by PTAs, provided we allow for an increased luminosity function athigh redshift (4-7), as recently suggested by JWST observations. Our modelcan simultaneously reproduce the bulk of the M_*-M_{\rm BH} relation atz-0, as well as its outliers, something cosmological simulations struggle todo. The inferred model parameters are consistent with expectations fromobservations and more complex simulations: They favour heavier black hole seedsand short delays between halo and black hole mergers, while requiringsupper-Edington accretion episodes lasting a few tens of million years, whichin our model are linked to galaxy mergers. We find accretion to be suppressedin the most massive black holes below z~eq 2.5, consistently with theanti-hierarchical growth hypothesis. Finally, our predictions for LISA,although fairly broad, are in agreement with previous models. Our model offersa new perspective on the apparent tensions between the black hole luminosityfunction and the latest JWST and PTA results. Its flexibility makes it ideal tofully exploit the potential of future gravitational wave observations ofmassive black hole binaries with LISA.