The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...) philosophy of measurement: it is epistemological, coherentist, practice oriented, and model based. (shrink)

Reports of quantitative experimental results often distinguish between the statistical uncertainty and the systematic uncertainty that characterize measurement outcomes. This article discusses the practice of estimating systematic uncertainty in high-energy physics. The estimation of systematic uncertainty in HEP should be understood as a minimal form of quantitative robustness analysis. The secure evidence framework is used to explain the epistemic significance of robustness analysis. However, the empirical value of a measurement result depends crucially not only on the resulting systematic uncertainty estimate, (...) but on the learning aims for which that result will be used. Important conceptual and practical questions regarding systematic uncertainty assessment call for further investigation. _1_ Introduction _2_ Systematic Uncertainty: The Very Idea _3_ Systematic Uncertainty in High-Energy Physics _4_ Methodological Debates in High-Energy Physics _5_ The Secure Evidence Framework _6_ Systematic Uncertainty Assessment as Robustness Analysis _7_ Security and Sensitivity _8_ Conclusion Appendix. (shrink)

Many decades ago Patrick Suppes argued rather convincingly that theoretical hypotheses are not confronted with the direct, raw results of an experiment, rather, they are typically compared with models of data. What exactly is a data model however? And how do the interactions of particles at the subatomic scale give rise to the huge volumes of data that are then moulded into a polished data model? The aim of this paper is to answer these questions by presenting a detailed case (...) study of the construction of data models at the LHCb for testing Lepton Flavour Universality in rare decays of B-mesons. The close examination of the scientific practice at the LHCb leads to the following four main conclusions: raw data in their pure form are practically useless for the comparison of experimental results with theory, and processed data are in some cases epistemically more reliable, real and simulated data are involved in the co-production of the final data model and cannot be easily distinguished, theory-ladenness emerges at three different levels depending on the scope and the purpose for which background theory guides the overall experimental process and the overall process of acquiring and analysing data in high energy physics is too complicated to be fully captured by a generic methodological description of the experimental practice. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.

This paper provides an account of the nature of creativity in high-energy physics experiments through an integrated historical and philosophical study of the current and planned attempts to measure the self-coupling of the Higgs boson by two experimental collaborations at the Large Hadron Collider and the planned High Luminosity Large Hadron Collider. A notion of creativity is first identified broadly as an increase in the epistemic value of a measurement outcome from an unexpected transformation, and narrowly as a condition for (...) knowledge of the measurement of the self-coupling of the Higgs. Drawing upon Tal’s model-based epistemology of measurement this paper shows how without change to ‘readings’ a transformation to the model of the measurement process can increase the epistemic value of the measurement outcome. Such transformations are attributed to the creativity of the experimental collaboration. Creativity, in this context, is both a product, a creative and improved model, and the distributed collaborative process of transformation to the model of the measurement process. For the case of the planned measurements at the HL-LHC, where models of the measurement process perform the epistemic function of prediction, creativity is included in the models of the measurement process, both as projected quantified creativity and as an assumed property of the future collaborations. (shrink)