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A deep learning approach to halo merger tree construction
A key ingredient for semi-analytic models (SAMs) of galaxy formation is the mass assembly history of haloes, encoded in a tree structure.
A Halo Merger Tree Generation and Evaluation Framework
Our aim is to provide a new framework for halo merger tree generation that takes advantage of the results of large volume simulations, with a modest computational cost.
The Power of Genetic Algorithms: what remains of the pMSSM?
Genetic Algorithms (GAs) are explored as a tool for probing new physics with high dimensionality.
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