Eric Winsberg

Simulations (both digital and analog) and experiments share many features. But what essential features distinguish them? I discuss two proposals in the literature. On one proposal, experiments investigate nature directly, while simulations merely investigate models. On another proposal, simulations differ from experiments in that simulationists manipulate objects that bear only a formal (rather than material) similarity to the targets of their investigations. Both of these proposals are rejected. I argue that simulations fundamentally differ from experiments with regard to the background knowledge that is invoked to argue for the “external validity” of the investigation.

One of the most interesting things about science and engineering at the nanoscale, from the point of view of the philosophy of science, is the frequent use they make of models constructed out of theories belonging to different levels of description. We usually take it for granted that every level of description falls under the domain of its own theory. For example, we generally presume there is some fundamental level of description. And with that presumption comes the hope that we will be able to find a general theory of how things work at that level. But we also often take it for granted that at every other level of description that interests us—whether it be at the level of subatomic particles, atoms, fundamental theory molecules, fluids or mechanical solids—there will be some non-fundamental theory available to us that will be practically serviceable for explaining, predicting, and controlling the various phenomena that live at that level of description.

Using an example of a computer simulation of the convective structure of a red giant star, this paper argues that simulation is a rich inferential process, and not simply a "number crunching" technique. The scientific practice of simulation, moreover, poses some interesting and challenging epistemological and methodological issues for the philosophy of science. I will also argue that these challenges would be best addressed by a philosophy of science that places less emphasis on the representational capacity of theories (and ascribes that capacity instead to models) and more emphasis on the role of theory in guiding (rather than determining) the construction of models