Why Trust a Simulation? Models, Parameters, and Robustness in Simulation-Infected Experiments

British Journal for the Philosophy of Science (forthcoming)
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Abstract

Computer simulations are nowadays often directly involved in the generation of experimental results. Given this dependency of experiments on computer simulations, that of simulations on models, and that of the models on free parameters, how do researchers establish trust in their experimental results? Using high-energy physics (HEP) as a case study, I will identify three different types of robustness that I call conceptual, methodological, and parametric robustness, and show how they can sanction this trust. However, as I will also show, simulation models in HEP themselves fail to exhibit a type of robustness I call inverse parametric robustness. This combination of robustness and failures thereof is best understood by distinguishing different epistemic capacities of simulations and different senses of trust: Trusting simulations in their capacity to facilitate credible experimental results can mean accepting them as means for generating belief in these results, while this need not imply believing the models themselves in their capacity to represent an underlying reality.

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Florian J. Boge
Bergische Universität Wuppertal

Citations of this work

Convergence strategies for theory assessment.Elena Castellani - 2024 - Studies in History and Philosophy of Science Part A 104 (C):78-87.
The Positive Argument Against Scientific Realism.Florian J. Boge - 2023 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 54 (4):535-566.

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