Publications (5)
Identifying WIMP dark matter from particle and astroparticle data
Gianfranco Bertone, Nassim Bozorgnia, Jong Soo Kim +4
One of the most promising strategies to identify the nature of dark matter consists in the search for new particles at accelerators and with so-called direct detection experiments.…
Barrett: out-of-core processing of MultiNest output
Sebastian Liem
Barrett is a Python package for processing and visualising statistical inferences made using the nested sampling algorithm MultiNest. The main differential feature from competitors…
Effective Field Theory of Dark Matter: a Global Analysis
Sebastian Liem, Gianfranco Bertone, Francesca Calore +4
We present global fits of an effective field theory description of real, and complex scalar dark matter candidates. We simultaneously take into account all possible dimension 6 ope…
Accelerating the BSM interpretation of LHC data with machine learning
Gianfranco Bertone, Marc Peter Deisenroth, Jong Soo Kim +3
The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event g…
Simplified Models for Dark Matter Searches at the LHC
Jalal Abdallah, Henrique Araujo, Alexandre Arbey +94
This document outlines a set of simplified models for dark matter and its interactions with Standard Model particles. It is intended to summarize the main characteristics that thes…