Distinguishing Dynamical Dark Matter at the LHC
Keith R. Dienes, Shufang Su, Brooks Thomas

TL;DR
This paper explores how to identify and distinguish dynamical dark matter ensembles at the LHC by analyzing unique invariant-mass distributions of Standard-Model particles produced alongside heavy fields, highlighting features that differ from traditional dark-matter models.
Contribution
It introduces methods to detect and differentiate dynamical dark matter ensembles at colliders, emphasizing their unique invariant-mass distribution signatures compared to traditional models.
Findings
Invariant-mass distributions have unique features in DDM scenarios.
It is often possible to distinguish DDM from traditional dark matter models.
Results are applicable to other Standard Model extensions with multiple neutral particles.
Abstract
Dynamical dark matter (DDM) is a new framework for dark-matter physics in which the dark sector comprises an ensemble of individual component fields which collectively conspire to act in ways that transcend those normally associated with dark matter. Because of its non-trivial structure, this DDM ensemble --- unlike most traditional dark-matter candidates --- cannot be characterized in terms of a single mass, decay width, or set of scattering cross-sections, but must instead be described by parameters which describe the collective behavior of its constituents. Likewise, the components of such an ensemble need not be stable so long as lifetimes are balanced against cosmological abundances across the ensemble as a whole. In this paper, we investigate the prospects for identifying a DDM ensemble at the LHC and for distinguishing such a dark-matter candidate from the candidates…
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