Six Forward and Inverse Models in HeFTy Everyone Should Perform Before Interpreting Real Cooling Ages

Abstract:

Most low-temperature thermochronologic studies rely on numerical thermal history (time-temperature, tT) modeling to aid in the interpretation of cooling ages. HeFTy (Ketcham, 2005), along with QTQt, is one of several commonly used tools for both forward and inverse tT modeling. However, these modeling tools currently lack clear and accessible entry-points for all users—experienced and new thermochronologists alike—and thus for many geoscientists, there is a substantial barrier to the modeling, interpretation, and publication of thermochronologic datasets. Here, we present a suite of simple forward and inverse models that we recommend everyone perform before embarking on tT modeling in HeFTy for the first time (see parallel QTQt poster by Abbey et al., 2020). This suite not only illustrates the fundamental behavior of thermochronologic systems but also guides the user through examples of efficient and robust strategies for tackling data interpretation. At the core of the exercises are the five different tT paths used by Wolf et al. (1998) to illustrate the partial-retention behavior of the apatite He system. By forward modeling these paths in HeFTy, users learn how to predict cooling ages and explore the effects of variable grain size and [eU] composition. Then, users input the predicted (synthetic) ages from the forward models into HeFTy as data for inverse models, which are designed to retrieve—to the best of our ability—the known tT history. During even this simple modeling effort, the user experiences most of the challenges and opportunities common to thermal history modeling, including: how to enter data; error handling; the role of geologic constraints; the non-unique nature of cooling ages; the power of grain size and eU variability; the limitations on a model’s ability to resolve the ‘right’ rock thermal history; and how to use sensitivity testing to evaluate model results. The models we present are designed to leverage partial-retention behavior of the AHe system, but a similar suite of models could be developed for other thermochronometers.