English

Displaying dark matter constraints from colliders with varying simplified model parameters

High Energy Physics - Phenomenology 2022-03-24 v1 High Energy Physics - Experiment

Abstract

The search for dark matter is one of the main science drivers of the particle and astroparticle physics communities. Determining the nature of dark matter will require a broad approach, with a range of experiments pursuing different experimental hypotheses. Within this search program, collider experiments provide insights on dark matter which are complementary to direct/indirect detection experiments and to astrophysical evidence. To compare results from a wide variety of experiments, a common theoretical framework is required. The ATLAS and CMS experiments have adopted a set of simplified models which introduce two new particles, a dark matter particle and a mediator, and whose interaction strengths are set by the couplings of the mediator. So far, the presentation of LHC and future hadron collider results has focused on four benchmark scenarios with specific coupling values within these simplified models. In this work, we describe ways to extend those four benchmark scenarios to arbitrary couplings, and release the corresponding code for use in further studies. This will allow for more straightforward comparison of collider searches to accelerator experiments that are sensitive to smaller couplings, such as those for the US Community Study on the Future of Particle Physics (Snowmass 2021), and will give a more complete picture of the coupling dependence of dark matter collider searches when compared to direct and indirect detection searches. By using semi-analytical methods to rescale collider limits, we drastically reduce the computing resources needed relative to traditional approaches based on the generation of additional simulated signal samples.

Keywords

Cite

@article{arxiv.2203.12035,
  title  = {Displaying dark matter constraints from colliders with varying simplified model parameters},
  author = {Andreas Albert and Antonio Boveia and Oleg Brandt and Eric Corrigan and Zeynep Demiragli and Caterina Doglioni and Etienne Dreyer and Boyu Gao and Josh Greaves and Ulrich Haisch and Philip Harris and Greg Landsberg and Alexander Moreno and Katherine Pachal and Priscilla Pani and Federica Piazza and Tim M. P. Tait and David Yu and Felix Yu and Lian-Tao Wang},
  journal= {arXiv preprint arXiv:2203.12035},
  year   = {2022}
}
R2 v1 2026-06-24T10:22:36.366Z