Simulation techniques, especially those implemented on a computer, are frequently employed in natural as well as in social sciences with considerable success. There is mounting evidence that the "model-building era" (J. Niehans) that dominated the theoretical activities of the sciences for a long time is about to be succeeded or at least lastingly supplemented by the "simulation era". But what exactly are models? What is a simulation and what is the difference and the relation between a model and a simulation? (...) These are some of the questions addressed in this article. I maintain that the most significant feature of a simulation is that it allows scientists to imitate one process by another process. "Process" here refers solely to a temporal sequence of states of a system. Given the observation that processes are dealt with by all sorts of scientists, it is apparent that simulations prove to be a powerful interdisciplinarily acknowledged tool. Accordingly, simulations are best suited to investigate the various research strategies in different sciences more carefully. To this end, I focus on the function of simulations in the research process. Finally, a somewhat detailed case-study from nuclear physics is presented which, in my view, illustrates elements of a typical simulation in physics. (shrink)

Calibration, the use of a surrogate signal to standardize an instrument, is an important strategy for the establishment of the validity of an experimental result. In this paper, I present several examples, typical of physics experiments, that illustrate the adequacy of the surrogate. In addition, I discuss several episodes in which the question of calibration is both difficult to answer and of paramount importance. These episodes include early attempts to detect gravity waves, the question of the existence of a 17–keV (...) neutrino, and the question of the existence of a Fifth Force in gravity. I argue that in these more complex cases, the adequacy of calibration, in an extended sense, was both considered and established. (shrink)

This book presents the concept of “complementary science” which contributes to scientific knowledge through historical and philosophical investigations. It emphasizes the fact that many simple items of knowledge that we take for granted were actually spectacular achievements obtained only after a great deal of innovative thinking, painstaking experiments, bold conjectures, and serious controversies. Each chapter in the book consists of two parts: a narrative part that states the philosophical puzzle and gives a problem-centred narrative on the historical attempts to solve (...) the puzzle; and the analysis part which provides in-depth analyses of certain scientific, historical, and philosophical aspects of the story. (shrink)

'IRS' is our term for the logical empiricist idea that the best way to understand the epistemic bearing of observational evidence on scientific theories is to model it in terms of Inferential Relations among Sentences representing the evidence, and sentences representing hypotheses the evidence is used to evaluate. Developing ideas from our earlier work, including 'Saving the Phenomena'(Phil Review 97, 1988, p.303-52 )we argue that the bearing of observational evidence on theory depends upon causal connections and error characteristics of the (...) processes by which data is produced and used to detect features of phenomena. Neither of these depends upon, or is greatly illuminated by a consideration of, formal relations among observation and theoretical sentences or propositions. By taking causal structures and error characteristics, you too can evade the IRS. In doing so, you can gain insight into Hempel’s raven paradox, theory loading, and other issues from the standard philosophical literature on confirmation theory. (shrink)

This paper explores how data serve as evidence for phenomena. In contrast to standard philosophical models which invite us to think of evidential relationships as logical relationships, I argue that evidential relationships in the context of data-to-phenomena reasoning are empirical relationships that depend on holding the right sort of pattern of counterfactual dependence between the data and the conclusions investigators reach on the phenomena themselves.

Engages with the impact of modern technology on experimental physicists. This study reveals how the increasing scale and complexity of apparatus has distanced physicists from the very science which drew them into experimenting, and has fragmented microphysics into different technical traditions.

This paper examines the relationship between simulation and experiment. Many discussions of simulation, and indeed the term "numerical experiments," invoke a strong metaphor of experimentation. On the other hand, many simulations begin as attempts to apply scientific theories. This has lead many to characterize simulation as lying between theory and experiment. The aim of the paper is to try to reconcile these two points of viewto understand what methodological and epistemological features simulation has in common with experimentation, while at the (...) same time keeping a keen eye on simulation's ancestry as a form of scientific theorizing. In so doing, it seeks to apply some of the insights of recent work on the philosophy of experiment to an aspect of theorizing that is of growing philosophical interest: the construction of local models. (shrink)

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. (shrink)

A number of recent discussions comparing computer simulation and traditional experimentation have focused on the significance of “materiality.” I challenge several claims emerging from this work and suggest that computer simulation studies are material experiments in a straightforward sense. After discussing some of the implications of this material status for the epistemology of computer simulation, I consider the extent to which materiality (in a particular sense) is important when it comes to making justified inferences about target systems on the basis (...) of experimental results. (shrink)