Search for Dark Matter with Long Lived Particles at the LHC
Selected within the context of the ANR "Appel à projets générique 2021, Projet de Recherche Collaborative"
Long-lived particles are predicted in many dark matter models, including two emerging categories which are the focus of this project: axion-like particles (ALPs) and dark hadrons. These currently have limited coverage at colliders: there is hence an opportunity to gain access to completely new regions of the new physics parameter space. For the ALP, we will focus on its decay into a photon pair either promptly or inside the calorimeters. For the dark hadrons, the peculiar characteristics of their jets will be exploited: different number of tracks, jet substructure, development of the shower in the calorimeters that could come from the late decay of long-lived dark sector hadrons,... These searches will not only be developed within ATLAS, but theoretical aspects allowing to link phenomenology to underlying theory parameters will be addressed.
These searches use photons and jets, which both interact with matter as a particle shower governed by stochastic processes, even if with different underlying physics. Advanced neural network techniques will be developed to use the shower constituent information to improve on the performances; to improve training the uncertainties on input variables will also be considered. By building such tools based on low-level information (from the photon and jet constituents) rather than high-level information (from the photons and jets directly), we aim to improve significantly the precision of the measurement of energy, direction and mass with respect to existing techniques. For the same reasons, such tools will allow for better identification of signal photons and jets and better background rejection.
A final aim of this project will be to make it possible to reinterpret the results of the searches described above in terms of as many other models as possible. Setting up a collaboration between theorists and experimentalists from the beginning of the inception of the analyses will allow for the most general possible interpretation of the results. This includes an optimal choice of benchmarks, and will at the same time allow for gathering all of the necessary information to reinterpret the results. To achieve this, we will develop an appropriate software framework in the initial stages of the proposal, and test it by recasting existing ATLAS long-lived particle analyses.
LPSC Grenoble: Marie-Hélène GENEST, Guillaume ALBOUY, Pierre-Antoine DELSART, Jean-Baptiste DE VIVIE DE REGIE, Nathan LALLOUÉ, Ana Paula PEREIRA PEIXOTO
LPNHE Paris: Bertrand LAFORGE, Bogdan MALAESCU, José OCARIZ, Lydia ROOS
LPTHE Paris: Benjamin FUKS, Mark GOODSELL, Filippo SALA
Scientific leader of each lab, Project coordinator
[to be confirmed] April 12-13th 2022 Kick-off meeting in Paris.