Speaker
Andrew Fowlie
(Nanjing Normal University)
Description
We propose (2105.13923) a novel method for computing $p$-values based on nested sampling (NS). The computational cost of NS scales as $\log^2{1/p}$, which compares favorably to the $1/p$ scaling for Monte Carlo (MC) simulations. For significances greater than about $4\sigma$ in both a toy problem and a simplified resonance search, we show that NS requires orders of magnitude fewer simulations than ordinary MC estimates. This is particularly relevant for high-energy physics, which adopts a $5\sigma$ gold standard for discovery.
Authors
Andrew Fowlie
(Nanjing Normal University)
Sebastian Hoof
(Georg-August-Universität Göttingen)
Will Handley
(University of Cambridge)
