Signal detection under unknown background when only one unlabeled data is available

Music City Center 

Searches for new physics involve detecting the presence of a specific signal in data that is contaminated by a background. This is particularly challenging when a reliable description of the background is unavailable. Our aim is to develop a statistical method to test the presence of the signal in the data and estimate the signal proportion even when the background is unknown. Moreover, we carry out the signal search using a single physics dataset generated from the experiments that may or may not contain the signal of interest. Our approach relies on using orthonormal expansion to model the deviation between a proposal density and the unknown data generating density. We propose choosing the proposal density in a way that ensures a conservative estimate of the signal proportion to avoid false discovery. Reliability of this approach is demonstrated through simulation studies, application on realistic simulated data from the Fermi Large Area Telescope and on data from the ATLAS experiment. We also perform a comparative analysis of our method with the so-called "safeguard" method commonly employed in particle physics and explore cases where the latter leads to false discoveries.

signal detection

background

orthonormal expansion

false discovery

safeguard

ATLAS experiment 

Section on Physical and Engineering Sciences