The imprint of massive black hole formation models on the LISA data stream

Astronomy and Astrophysics – Astrophysics

Scientific paper

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7 pages, 5 figures, minor changes, accepted for publication in MNRAS

Scientific paper

10.1111/j.1365-2966.2007.11734.x

The formation, merging, and accretion history of massive black holes along the hierarchical build--up of cosmic structures leaves a unique imprint on the background of gravitational waves at mHz frequencies. We study here, by means of dedicated simulations of black hole build--up, the possibility of constraining different models of black hole cosmic evolution using future gravitational wave space--borne missions, such as LISA. We consider two main scenarios for black hole formation, namely, one where seeds are light (~10^2 \msun, remnant of Population III stars), and one where seeds are heavy (>~10^4 \msun, direct collapse). In all the models we have investigated, massive black hole binary coalescences do not produce a stochastic GW background, but rather, a set of individual resolved events. Detection of several hundreds merging events in 3 year LISA mission will be the sign of a heavy seed scenario with efficient formation of black hole seeds in a large fraction of high redshift halos. On the other extreme, a low event rate, about few tens in 3 years, is peculiar of scenarios where either the seeds are light, and many coalescences do not fall into the LISA band, or seeds are massive, but rare. In this case a decisive diagnostic is provided by the shape of the mass distribution of detected events. Light binaries (m<10^4\msun) are predicted in a fairly large number in Population III remnants models, but are totally absent in direct collapse models. Finally, a further, helpful diagnostic of black hole formation models lies in the distribution of the mass ratios in binary coalescences. While heavy seed models predict that most of the detected events involve equal mass binaries, in the case of light seeds, mass ratios are equally distributed in the range 0.1-1.

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