Project description
Advanced data analysis technique could shed light on dark matter’s true nature
The standard model of particle physics has successfully predicted many experimental results. However, it still cannot explain some intriguing phenomena, such as the large excess of unobservable dark matter in the universe. Funded by the European Research Council, the DARKJETS project will explore whether dark matter may consist of particles created during proton-proton collisions at CERN’s Large Hadron Collider (LHC). In their search for signals indicating the presence of dark matter particles, researchers will use a novel real-time data analysis technique and a new search signature to overcome data storage limitations. As the LHC will soon resume operations, DARKJETS presents a unique opportunity to significantly enhance our understanding of dark matter.
Objective
The Standard Model of Particle Physics describes the fundamental components of ordinary matter and their interactions. Despite its success in predicting many experimental results, the Standard Model fails to account for a number of interesting phenomena. One phenomenon of particular interest is the large excess of unobservable (Dark) matter in the Universe. This excess cannot be explained by Standard Model particles. A compelling hypothesis is that Dark Matter is comprised of particles that can be produced in the proton-proton collisions from the Large Hadron Collider (LHC) at CERN.
Within this project, I will build a team of researchers at Lund University dedicated to searches for signals of the presence of Dark Matter particles. The discovery strategies employed seek the decays of particles that either mediate the interactions between Dark and Standard Model particles or are produced in association with Dark Matter. These new particles manifest in detectors as two, three, or four collimated jets of particles (hadronic jets).
The LHC will resume delivery of proton-proton collisions to the ATLAS detector in 2015. Searches for new, rare, low mass particles such as Dark Matter mediators have so far been hindered by constraints on the rates of data that can be stored. These constraints will be overcome through the implementation of a novel real-time data analysis technique and a new search signature, both introduced to ATLAS by this project. The coincidence of this project with the upcoming LHC runs and the software and hardware improvements within the ATLAS detector is a unique opportunity to increase the sensitivity to hadronically decaying new particles by a large margin with respect to any previous searches. The results of these searches will be interpreted within a comprehensive and coherent set of theoretical benchmarks, highlighting the strengths of collider experiments in the global quest for Dark Matter.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdata science
- natural sciencescomputer and information sciencessoftware
- natural sciencesphysical sciencestheoretical physicsparticle physicsparticle accelerator
- natural sciencesphysical sciencesastronomyastrophysicsdark matter
- natural sciencesphysical sciencestheoretical physicsparticle physicsphotons
Programme(s)
Topic(s)
Funding Scheme
ERC-STG - Starting GrantHost institution
22100 Lund
Sweden