We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure [email protected]
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
In recent years, the discovery of massive quasars at $z\sim7$ has provided a striking challenge to our understanding of the origin and growth of supermassive black holes in the early Universe. Mounting observational and theoretical evidence indicates the viability of massive seeds, formed by the collapse of supermassive stars, as a progenitor model for such early, massive accreting black holes. Although considerable progress has been made in our theoretical understanding, many questions remain regarding how (and how often) such objects may form, how they live and die, and how next generation observatories may yield new insight into the origin of these primordial titans. This review focusses on our present understanding of this remarkable formation scenario, based on the discussions held at the Monash Prato Centre from November 20 to 24, 2017, during the workshop ‘Titans of the Early Universe: The Origin of the First Supermassive Black Holes’.
We present TreeFrog, a massively parallel halo merger tree builder that is capable comparing different halo catalogues and producing halo merger trees. The code is written in c++11, use the MPI and OpenMP API’s for parallelisation, and includes python tools to read/manipulate the data products produced. The code correlates binding energy sorted particle ID lists between halo catalogues, determining optimal descendant/progenitor matches using multiple snapshots, a merit function that maximises the number of shared particles using pseudo-radial moments, and a scheme for correcting halo merger tree pathologies. Focusing on VELOCIraptor catalogues for this work, we demonstrate how searching multiple snapshots spanning a dynamical time significantly reduces the number of stranded halos, those lacking a descendant or a progenitor, critically correcting poorly resolved halos. We present a new merit function that improves the distinction between primary and secondary progenitors, reducing tree pathologies. We find FOF accretion rates and merger rates show similar mass ratio dependence. The model merger rates from Poole, et al. [2017, 472, 3659] agree with the measured net growth of halos through mergers.