Evaluation of optimisation and Bayesian inference methods for reaction rates in atmospheric chemical mechanisms
arXiv stat.ML23h4 min read
arXiv:2609.14569v1 Announce Type: new Abstract: Constraining reaction rate coefficients is a central challenge in the development of explicit atmospheric chemical mechanisms, particularly for autoxidation systems where many reaction pathways are only indirectly observed through high-resolution mass spectrometry. In this study, we evaluate rate-coefficient optimisation methods for a toy-case autoxidation mechanism using synthetic data with known ground truth. Two complementary approaches are compared: ODE-constrained neural-network optimisation, which provides efficient point estimates of uncer
