Abstract

There is a complex interplay between the models in dark matter detection experiments that have led to a difficulty in interpreting the results of the experiments and ascertain whether we have detected the particle or not. The aim of this paper is to categorise and explore the different models used in said experiments, by emphasizing the distinctions and dependencies among different types of models used in this field. With a background theory, models are categorised into four distinct types: background theory, theoretical, phenomenological, experimental and data. This taxonomy highlights how each model serves a unique purpose and operates under varying degrees of independence from their respective frameworks. A key focus is on the experimental model, which is shown to rely on constraints from both data and phenomenological ones. The article argues that while theoretical models provide a backdrop for understanding the nature of dark matter, the experimental models must stand independently, particularly in their methodological approaches. This is done via a discussion of the inherent challenges in dark matter detection, such as inconsistent results and difficulties in cross-comparison, stemming from the diverse modelling approaches.