Conveners
Contributed Talks III
- Henning Kirschenmann (Helsinki Institute of Physics (FI))
In gamma-ray astronomy typically only the direct photon component is considered as signal when searching for annihilating WIMPS. This means that only photons that are produced during the WIMP annihilation and the consecutive hadronisation are taken into account. There is however also a non-negligible contribution to the gamma-ray signal that arises from the electrons that are produced in the...
We revisit the possibility that Dark Matter is composed of stable scalar glueballs of a confining dark ${\rm SU}(3)$ gauge theory coupled only to gravity. The relic abundance of dark glueballs is studied for the first time in a thermal effective theory accounting for strong-coupling dynamics. An important ingredient of our analysis is the use of an effective potential for glueballs that is...
Høgskulen på Vestlandet (HVL) has over the last couple of years built up a strong group working on machine learning (ML) for data analysis in collider experiments.
With the project “Use Artificial Intelligence to pinpoint Dark Matter at the LHC”, financed by the Research Council of Norway, we focus on dark matter searches in the tau lepton sector of the LHC phase space in ATLAS data...
Modern machine learning (ML) methods are widely used in LHC analyses, but considerably more time is invested in training ML models, than in understanding them. We present a small review of interpretation and explanation techniques relevant to ML classifiers used in collider experiments, and motivate why they should be consulted. Further, we present ongoing work on the related topic that is...
The application of machine learning has become popular in high energy physics within recent years. In addition to standard cut-based analyses, more and more effort is put to develop new strategies. One of a highly effective and widely recognised machine learning ensemble method are gradient boosted decision trees. This talk presents the current implementation of an optimized gradient boosting...
