Lessons from the Large Hadron Collider for model-based experimentation: the concept of a model of data acquisition and the scope of the hierarchy of models

Abstract

According to the hierarchy of models (HoM) account of scientific experimentation developed by Patrick Suppes and elaborated by Deborah Mayo, theoretical considerations about the phenomena of interest are involved in an experiment through theoretical models that in turn relate to experimental data through data models, via the linkage of experimental models. In this paper, I dispute the HoM account in the context of present-day high-energy physics (HEP) experiments. I argue that even though the HoM account aims to characterize experimentation as a model-based activity, it does not involve a modeling concept for the process of data acquisition, and it thus fails to provide a model-based characterization of the theory-experiment relationship underlying this process. In order to characterize the foregoing relationship, I propose the concept of a model of data acquisition and illustrate it in the case of the ATLAS experiment at CERN's Large Hadron Collider, where the Higgs boson was discovered in 2012. I show that the process of data acquisition in the ATLAS experiment is performed according to a model of data acquisition that specifies and organizes the experimental procedures necessary to select the data according to a predetermined set of selection criteria. I also point out that this data acquisition model is theory-laden, in the sense that the underlying data selection criteria are determined by considering the testable predictions of the theoretical models that the ATLAS experiment is aimed to test. I take this sense of theory-ladenness to indicate that the relationship between the procedures of the ATLAS experiment and the theoretical models of the phenomena of interest is first established, prior to the formation of data models, through the data acquisition model of the experiment, thus not requiring the intermediary of other types of models as suggested by the HoM account. I therefore conclude that in the context of present-day HEP experiments, the HoM account does not consistently extend to the process of data acquisition so as to include models of data acquisition.

What is a data model?

“…If the data is not in a comparable form with a theory, then this task cannot be accomplished. 4 Leonelli's third objection is very similar to an objection raised by Karaca (2018), regarding the lack of a modelling concept for the data acquisition process in Suppes' account. Using the example of the ATLAS experiment at CERN, Karaca notes that both Suppes' and Mayo's descriptions leave out a significant aspect of the overall process of bringing together theory and experiment in HEP, which is the specification and organization of the necessary experimental procedures in order to select the required data.…”

“…Massimi (2007) is perhaps one of the few exceptions, since in her attempt to argue for her thesis that data provide evidence for unobservable phenomena in HEP, she follows van Fraassen in providing a logical reconstruction of data models as partially ordered sets. Some further work on the methodology of data processing in HEP comes fromKaraca (2018) and will be discussed in the next section.…”

What Data Get to Travel in High Energy Physics? The Construction of Data at the Large Hadron Collider

“…In these experiments, data journeys start with the process of data acquisition. Some of the philosophical aspects of this process have already been discussed in the context of the LHC experiments (see, e.g., Morrison 2015;Beauchemin 2018;Karaca 2017Karaca , 2018, and also in other contexts in this volume. In a case study concerning ocean science, Gregor Halfmann (in this volume) discusses the initial stage of data acquisition where data is first produced.…”

“…In a case study concerning astronomy, Götz Hoeppe (in this volume) discusses aspects of data acquisition concerning data interpretation. In this chapter, I will focus on the initial data journey in the ATLAS experiment that links the production of collision events at the LHC to the stage of data acquisition where usable data are constructed out of collision events detected by the LHC, prior to the stage of data analysis and modeling (Karaca 2018;Leonelli 2019;Boumans and Leonelli in this volume).…”

Scientific perspectivism in the phenomenological tradition

“…In this context, cf., e.g., Karaca 2017, 344. 27 For discussions of what kind of observation is taking place in LHC experiments, cf., e.g., Beauchemin 2017;Karaca 2017Karaca , 2018 Concerning the relationship between theory and observation, Beauchemin argues that reflection on such big data experiments "indicates that the frontier between theory and observation is blurry and that the dichotomy theory-experiment should be revised" (Beauchemin 2017, 275). Although Beauchemin stresses the theory-ladenness of LHC experiments, he does not dispute the objectivity of the corresponding empirical facts.…”