Combining evolutionary strategies and novelty detection to go beyond the alignment limit of the
Z3
3HDM
Jorge Crispim Romão,
Miguel Crispim Romão
Abstract:We present a novel artificial intelligence approach for beyond the Standard Model parameter space scans by augmenting an evolutionary strategy with novelty detection. Our approach leverages the power of evolutionary strategies, previously shown to quickly converge to the valid regions of the parameter space, with a novelty reward to continue exploration once converged. Taking the Z3 3HDM as our physics case, we show how our methodology allows us to quickly explore highly constrained multidimensional parameter … Show more
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