Taming the Uncertainty Monster: Lessons from Astrochemistry

Descripción del proyecto

Reducción de la incertidumbre de los modelos y predicciones en astroquímica

La astroquímica es un campo en rápido crecimiento dedicado al estudio de la química de las estrellas, los planetas y el medio interestelar. Los modelos de los astroquímicos se basan en datos extrapolados con mucha incertidumbre que no consiguen reproducir las observaciones, que también son incompletas e inciertas. Los astroquímicos no tienen más remedio que desarrollar métodos para evaluar sus modelos y decidir cómo las discrepancias entre las observaciones y los modelos deberían guiar el trabajo futuro. En el proyecto TUMLA, financiado por las Acciones Marie Skłodowska-Curie, se llevará a cabo un estudio sin precedentes para analizar y evaluar la fiabilidad de estos métodos. Este tipo de estudio que aborda los desafíos epistémicos provocados por las incertidumbres solo se había realizado hasta ahora en el campo de la climatología.

Objetivo

The aim of TUMLA is to provide the experienced fellow Dr. Marie Gueguen, expert in philosophy of science, additional training, skills and knowledge in the field of the philosophy of astrochemistry and model evaluation at UR1 (University of Rennes 1, France) and, through a secondment, in uncertainty management procedures in astrochemistry at the Astrophysics Laboratory of Bordeaux (LAB). This will consolidate her scientific expertise and maturity with the goal of holding a permanent academic position in France. TUMLA proposes a philosophical account of model evaluation in context of high uncertainties. The research aims to conduct an unprecedented study of the methods developed by astrochemists to assess the reliability of astrochemical models, aiming at computing the abundance of molecules in the interstellar medium or in planetary atmosphere as a function of time, despite the fact that the models and the observations against which they must be validated are highly uncertain. These uncertainties, the multiplicity of tasks that models must fill, their different phases of development—from young models that need improvement to mature ones, ready to get confronted to observations—, the strong interdisciplinarity of the field make astrochemistry unique in terms of the challenges that astrochemists must face in evaluating the accuracy of their models. Such an exceptional epistemic situation represents a huge opportunity for philosophers both to refine their understanding of model evaluation and to contribute to developing new methods for assessing the adequacy of a model. Philosophers have not addressed the epistemic challenges generated by uncertainties in science other than climate science. Considering other sciences such as astrochemistry could considerably help broaden their perspective on this topic. The aim of TUMLA is to fill this gap, such as to contribute to an overall philosophical account of model evaluation based on the contemporary practice of scientists.