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The best fit redshift dependence parameters for the scaling relations defines in Eq. 14 and Eq. 15

The best fit redshift dependence parameters for the scaling relations defines in Eq. 14 and Eq. 15

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Figure 7. XGBoost predictions (y-axis) as a function of cluster mass, í...
Lists of selected DM-only features for the different targets after...
The best fit redshift dependence parameters for the scaling relations...
Machine Learning methods to estimate observational properties of galaxy clusters in large volume cosmological N-body simulations
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  • Apr 2022
In this paper we study the applicability of a set of supervised machine learning (ML) models specifically trained to infer observed related properties of the baryonic component (stars and gas) from a set of features of dark matter only cluster-size halos. The training set is built from THE THREE HUNDRED project which consists of a series of zoomed...
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... this new parametrization we apply a non-linear least square fitting model to fit the function described by equations (11), (12) and (13) updated with equations (14) and (15). The best-fitting parameters are shown in Table 3 and Table 4. Note that we have used the mass corresponding to the N-body simulation (the feature variable í µí±€ 500í µí± (2) as the mass of the cluster) As a general result, the fitting parameters are in agreement among the three different N-body simulations and are slightly different from The300 hydrodynamical simulation. ...