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Formation of the First Supermassive Black Holes in the Early Universe

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High Performance Computing in Science and Engineering, Garching/Munich 2007

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Abstract

To explain the formation of the first supermassive black holes in the universe, we present a scenario based on direct collapse of baryonic gas in massive halos at high redshift. We test this scenario with the adaptive mesh refinement (AMR) code Enzo using the computational facilities of the LRZ. We have performed first simulations on the direct collapse problem which demonstrate that such an AMR code can be successfully used to examine this collapse. Based on these results, we plan to resolve collapse to smaller scales and include deuterium chemistry, as the HD molecule gives important cooling contributions at the temperatures found in our simulation. Understanding black hole formation in the early universe will help to predict the evolution of the black hole population and lead to more accurate predictions for the gravitational wave interferometer LISA.

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Authors and Affiliations

  1. Landessternwarte Heidelberg, Institute of Theoretical Astrophysics/ZAH, Königstuhl 12, 69117, Heidelberg, Germany

    Dominik Schleicher & Max Camenzind

Authors
  1. Dominik Schleicher
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  2. Max Camenzind
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Correspondence to Dominik Schleicher .

Editor information

Editors and Affiliations

  1. Institut für Aerodynamik und Gasdynamik, Universität Stuttgart, Pfaffenwaldring 21, 70550, Stuttgart, Germany

    Siegfried Wagner

  2. Astrophysikalisches Institut Potsdam, An der Sternwarte 16, 14482, Potsdam, Germany

    Matthias Steinmetz

  3. Lehrstuhl für Rechnertechnik und Rechnerorganisation, Technische Universität München, Boltzmannstr. 3, 85748, Garching b. München, Germany

    Arndt Bode

  4. Leibniz-Rechenzentrum, Boltzmannstr. 1, 85748, Garching b. München, Germany

    Matthias Brehm

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Schleicher, D., Camenzind, M. (2009). Formation of the First Supermassive Black Holes in the Early Universe. In: Wagner, S., Steinmetz, M., Bode, A., Brehm, M. (eds) High Performance Computing in Science and Engineering, Garching/Munich 2007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69182-2_6

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