One trained convolutional network predicts bump significance across mass histograms of different sizes and backgrounds, approaching the accuracy of the ideal likelihood-ratio test.
The motivation and status of two-body resonance decays after the LHC Run 2 and beyond
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abstract
Searching for two-body resonance decays is a central component of the high energy physics energy frontier research program. While many of the possibilities are covered when the two bodies are Standard Model (SM) particles, there are still significant gaps. If one or both of the bodies are themselves non-SM particles, there is very little coverage from existing searches. We review the status of two-body searches and motivate the need to search for the missing combinations. It is likely that the search program of the future will be able to cover all possibilities with a combination of dedicated and model agnostic search approaches.
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Automatizing the search for mass resonances using BumpNet
One trained convolutional network predicts bump significance across mass histograms of different sizes and backgrounds, approaching the accuracy of the ideal likelihood-ratio test.