Autotunes splits event generator parameter spaces into correlated subspaces and assigns automatic observable weights, enabling iterative Professor-based tuning in higher dimensions than the standard approach.
Here, we require tree sub-tunes and performed four iterations
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High dimensional parameter tuning for event generators
Autotunes splits event generator parameter spaces into correlated subspaces and assigns automatic observable weights, enabling iterative Professor-based tuning in higher dimensions than the standard approach.