Both ecologists and statistical physicists use a variety of highly idealized models to study active matter and self-organizing critical phenomena. In this paper, I show how universality classes play a crucial role in justifying the application of highly idealized ‘minimal’ models to explain and understand the critical behaviors of active matter systems across a wide range of scales and scientific fields. Appealing to universality enables us to see why the same minimal models can be used to explain and understand behaviors (...) across these different systems despite drastic differences in the causes and mechanisms responsible for the behaviors of interest. After analyzing these cases in detail, I argue that accounts that focus on identifying common causes or mechanisms in order to explain patterns are unable to accommodate these cases. In contrast, I argue that the justification for using these minimal models is that they are within the same universality class as real systems whose causes and mechanisms are known to be different. I also use these cases to identify several different kinds of explanatory autonomy that have important implications for how scientists ought to approach the modeling of multiscale phenomena. (shrink)

I critically examine some recent work on the philosophy of scientific fictions, focusing on the work of Winsberg. By considering two case studies in fracture mechanics, the strip yield model and the imaginary crack method, I argue that his reliance upon the social norms associated with an element of a model forces him to remain silent whenever those norms fail to clearly match the characteristic of fictions or non-fictions. In its place, I propose a normative epistemology of fictions which clarifies (...) a model's ontological commitments when the community of scientists lack any clear, shared norms of use. Specifically, I will introduce a variational account of fictions as an extension of Laymon's monotonic improvability account of idealizations. I will conclude by connecting this variational account of fictions to didactic fictions in general. (shrink)

This paper starts by looking at the coincidence of surprising behavior on the nanolevel in both matter and simulation. It uses this coincidence to argue that the simulation approach opens up a pragmatic mode of understanding oriented toward design rules and based on a new instrumental access to complex models. Calculations, and their variation by means of explorative numerical experimentation and visualization, can give a feeling for a model's behavior and the ability to control phenomena, even if the model itself (...) remains epistemically opaque. Thus, the investigation of simulation in nanoscience provides a good example of how science is adapting to a new instrument: computer simulation. (shrink)

I propose that a sociological and historical examination of nanotechnologists can contribute more to an understanding of nanotechnology than an ontological definition. Nanotechnology emerged from the convergent evolution of numerous "technical knowledge communities"-networks of tightly-interconnected people who operate between disciplines and individual research groups. I demonstrate this proposition by sketching the co-evolution of computational chemistry and computational nanotechnology. Computational chemistry arose in the 1950s but eventually segregated into an ab initio, basic research, physics-oriented flavor and an industry-oriented, molecular modeling and (...) visualization, biochemical flavor. Computational nanotechnology arose in the 1990s as a synthesis of these two subgroups, infused by people and practices from computational materials science, engineering, computer science, and elsewhere. I show that to understand the aims and outcomes of computational nanotechnology-and nanotechnology more generally-we need to understand relationships between different, but related, nano knowledge communities and their dependence on particular practices, artifacts, and theories. (shrink)