Jul 22 – 27, 2018
US/Eastern timezone

Dark Matter Model or Mass: Benchmark-Free Forecasting for Future Detectors

Jul 23, 2018, 3:40 PM
117 (MacMillian)



Brown University Providence, Rhode Island, USA
Talk Direct Detection 1.3 Direct Detection


Thomas Edwards (University of Amsterdam)


We systematically approach the topic of signal diversity and model discrimination for a variety of future dark matter (DM) direct detection experiments. Firstly I introduce the Euclideanized signal method which will allow for a "benchmark-model-free” discussion of optimal experimental design. Secondly, I will present an intuitive way to quantify the sensitivity of experiments in terms of the number of distinctly discriminable signals and discuss a simple way to visualise these results using Infometric Venn Diagrams. In addition, I will demonstrate the technique and display the complementarity of combining a Xenon and Argon detector using a Non-Relativistic Effective Field Theory framework as well as some selected DM models. I show, using Modern clustering algorithms, that only in a small region of the parameter space is it possible to both constrain the mass of the DM and simultaneously discriminate between standard spin independent interactions and other DM-nucleon couplings for near-future Xenon and Argon detectors. Finally, I will present recent work on attempting to systematically break down model degeneracies by accounting for inelastic contributions to the DM signal

Primary authors

Thomas Edwards (University of Amsterdam) Dr Bradley Kavanagh (GRAPPA, University of Amsterdam) Christoph Weniger (University of Amsterdam)

Presentation materials