The project, titled "Hierarchical Mergers of Binary Black Holes" aims to investigate the characteristics and outcomes of hierarchical black hole mergers in different star clusters. The methodology involves plotting and comparing key properties of hierarchical black holes in nuclear star clusters, globular clusters, and young star clusters. The suggested properties for comparison include black hole masses, spin magnitudes, escape velocities, total masses of the star clusters, and the number of generations involved. Additionally, the project involves applying a simple machine learning algorithm, such as a random forest, to determine the features that have the greatest impact on the fate of a binary black hole in the three types of star clusters.
To gain a deeper understanding of the hierarchical pairing process and the simulations from which the data were obtained, consult Mapelli et al., Hierarchical black hole mergers in young, globular and nuclear star clusters, Monthly Notices of the Royal Astronomical Society, Volume 505 (2021) https://arxiv.org/abs/2103.05016.
This project was developed in March 2022 by Group 14 for Laboratory of Computational Physics MOD A course (academic year: 2021-2022). The group members are:
- Cano Amaro German: https://github.com/german-cano
- Monti Sebastiano: https://github.com/MontiSebastiano
- Tonazzo Valentina: https://github.com/ValentinaTonazzo
- Zoppellari Elena: https://github.com/zoppellarielena