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Unveiling stellar-mass black holes in globular clusters with dynamical models.

Peuten, Miklos (2019) Unveiling stellar-mass black holes in globular clusters with dynamical models. Doctoral thesis, University of Surrey.

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The recent discovery of a gravitational wave produced by two merging stellar-mass black holes started a search for environments where two stellar mass black holes can become a binary and merge. One favourable environment could be globular clusters, but the evolution of black holes in them is still widely debated.

In this thesis, I present a method, based on isotropic lowered isothermal multimass models with which stellar mass black hole populations in globular clusters can be dynamically inferred and the main properties of the cluster can be estimated. In the models, I am using an improved stellar evolution code from Balbinot and Gieles (2018) to which I added black hole evolution. Before applying the multimass models to data, I made a detailed comparison between the properties of multimass models and collisional N-body simulations. I find that all dynamical stages are well described by the models and that a stellar mass black hole population reduces mass segregation.

For the Milky Way globular cluster NGC 6101, I run three N-body simulations to show that the observed lack of observable mass segregation could be explained by a stellar mass black hole population. To differentiate this explanation from others, I create different multimass models and find that measuring the cluster's velocity dispersion could help to prove the black hole population.

In the final chapter I follow-up on this prediction, and present new line-of-sight velocities of NGC 6101's velocities with the ESO MUSE instrument, I find, applying my method, that the cluster has 86+30-23 black holes, which could explain its currently observed lack of mass segregation. This thesis is concluded by a discussion on how to improve dynamical detections of BH populations with future observations and models.

Item Type: Thesis (Doctoral)
Divisions : Theses
Authors : Peuten, Miklos
Date : 28 June 2019
Funders : European Research Council (ERC)
DOI : 10.15126/thesis.00851890
Grant Title : ERC-StG-335936, CLUSTERS
Contributors :
Depositing User : Miklos Peuten
Date Deposited : 03 Jul 2019 07:56
Last Modified : 03 Jul 2019 07:56

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