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 differentiating 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.

中文翻译：

---

为什么要相信模拟？模拟感染实验中的模型、参数和稳健性

如今，计算机模拟通常直接参与实验结果的产生。鉴于实验对计算机模拟、模型模拟以及模型对自由参数的依赖，研究人员如何建立对他们实验结果的信任？使用高能物理 (HEP) 作为案例研究，我将确定三种不同类型的稳健性，我称之为概念稳健性、方法稳健性和参数稳健性，并展示它们如何认可这种信任。然而，正如我还将展示的那样，HEP 中的仿真模型本身未能表现出一种我称之为逆参数鲁棒性的鲁棒性。通过区分模拟的不同认知能力和不同的信任感，可以最好地理解这种稳健性和失败的组合：