Can I read Resonance Searches with Machine Learned Likelihood Ratios on EtoBox?

Resonance Searches with Machine Learned Likelihood Ratios by Hollingsworth, Jacob; Whiteson, Daniel is a scholarly article available to read on EtoBox.

What is Resonance Searches with Machine Learned Likelihood Ratios about?

We demonstrate the power of machine-learned likelihood ratios for resonance searches in a benchmark model featuring a heavy Z' boson. The likelihood ratio is expressed as a function of multivariate detector level observables, but rather than being calculated explicitly as in matrix-element-based approaches, it is learned from a joint likelihood ratio which depends on latent information from simulated samples. We show that bounds drawn using the machine learned likelihood ratio are tighter than those drawn using a likelihood ratio calculated from histograms.

Author

Hollingsworth, Jacob; Whiteson, Daniel

Published

2020

Language

EN