Lydia Patton

Associate Professor, Philosophy, Virginia Tech.

Specialization Philosophy of science, the history of philosophy of science, philosophy of mathematics.
See my CV [PDF].

Much of my recent work and work in progress centers on “heuristic reasoning”: developing and generating models and hypotheses, and finding links between that development and theory building and testing.  A problem with ‘merely’ heuristic reasoning is that it seems ad hoc, and even a hidden form of double counting: we build a model to illustrate a preferred hypothesis, and use the results to confirm the hypothesis. I argue that heuristic reasoning can follow a virtuously, not a viciously, circular path.

The guiding idea is that heuristics must be put to the test. The relationship between theory and models should provide a pragmatic framework for  expanding, testing, and even breaking the theory. Another name for the approach could be ‘making and breaking theories’. The idea is to learn from the process of testing, verifying, and experimenting. If the process of heuristic reasoning is done correctly, it widens our understanding of the options available and the claims provable within a theory.

“Reconsidering Experiments” (HOPOS, PhilSciArchive, arxiv) analyzes the interplay between experimental optics and the development of special relativity. Nineteenth century ether theories were more sophisticated than is often recognized, and the Michelson-Morley experiment was not a direct falsification of all of those theories. Only once Einstein had constructed a theory that eliminated matter-ether interaction from electrodynamics and optics altogether was it possible to make a substantive argument, appealing to the Michelson-Morley experiments, that “ether” was no longer a meaningful variable in those theories.

“Experiment and Theory Building” (Synthese; PhilSciArchive) takes up Kuhn’s and Lakatos’s questions about the epistemic choices available to scientists when experiments are in conflict with accepted theory – when anomalies begin to accumulate. I argue that there is an available framework for decisions about the new theory available, even if the choice of a novel theory is not univocally determined a priori. In particular, as I also argue in “Reconsidering Experiments”, the falsifying experiments themselves can provide hints for the structure of a new theory.

These analyses raise the question of whether there can be an over-arching account of theory construction that deliberately takes into account the heuristic process of theory testing and (inevitable) revision.   “Methodological Realism and Modal Resourcefulness” (PhilSciArchiveSynthese) and “Kuhn, Pedagogy, and Practice” (PhilSciArchive; Thomas Kuhn’s Image of Science) set out an initial approach, systematically and historically, respectively. The first paper builds on Laura Ruetsche’s Interpreting Quantum Theories, especially Ruetsche’s defense of “a theoretical virtue I will call ‘modal resourcefulness’: that a theory be able to function as a guide in varying modal contexts, without requiring a unifying physical interpretation of the theory as a depiction of reality”.   “Kuhn, Pedagogy, and Practice” emphasizes the local, practical features of Kuhn’s account in Structure, especially his account of how scientists are trained in a way of approaching the phenomena. That training goes beyond traditional semantic analyses of the confirmation of a theory, to include practical approaches to testing theories or conjectures, and broader capacities, including Polany’s “tacit knowledge” and Fleck’s “vademecum science”.

The focus on heuristic, exploratory reasoning unifies systematic work in philosophy of science with work on the development of science and philosophy of science.  Work in progress begins to apply the methods developed above to contemporary scientific theories, especially fluid dynamics and research into black holes. Fluid dynamics and black hole mergers share a feature: the partial differential equations of the background theory (Einstein’s linearized field equations, the Navier-Stokes equations) can’t be solved analytically in many domains of interest. Heuristic reasoning is not only helpful, but necessary, in these cases. Initial results of this research have been presented at the Joint Meetings of the American Mathematical Society, at the MidWest Philosophy of Mathematics Workshop at Notre Dame, at Cambridge University, at the MCMP, and at the inaugural Black Hole Initiative conference.

“Time-frequency Methods for Parameter Estimation Using Gravitational Waves,” American Mathematical Society Joint Mathematics Meetings. 4 January 2017.

“Fishbones, Wheels, Eyes, and Butterflies: Is There a Unified Account of Mathematical and Physical Modeling?”  Midwest Philosophy of Mathematics Workshop 17, University of Notre Dame, 12-13 November 2016. Abstract.

“How Does the LIGO Detection of Gravitational Waves Test General Relativity?” Colloquium at the Munich Center for Mathematical Philosophy, 13 June 2016. MCMP_Abstract

Black Hole Initiative

Session 8: Philosophy
Session Chair: Peter Galison

Lydia Patton: Listening to the Chirps: Estimating Black Hole Parameters Using the LIGO Results  |  Slides
Erik Curiel: Classical Black Holes Are Hot |  Slides
David Wallace: Questions for Black Hole Evaporation from Quantum Statistical Mechanics  |  Slides
Jeroen van Dongen: History and Philosophy of the Black Hole Information Paradox  |  Slides

Note: Heuristic Reasoning was the focus of an eponymous collection edited by Emiliano Ippoliti in 2015 (Springer): link here.  My own, related use of ‘heuristic’ comes from Einstein’s discussions of relativity.

 

Researchgate

PhilPapers

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The image in the background is of a portable electrostatic machine, on display at the Museo Galileo in Florence. Click here for information. Photograph (c) Lydia Patton 2014.