Speaker
Description
Differentiability in detector simulation can enable efficient and effective detector optimisation. We are developing an AD-enabled detector simulation of a liquid argon time projection chamber to facilitate simultaneous detector calibration through gradient-based optimisation. This approach allows us to account for the correlations of the detector modeling parameters comprehensively and avoid biases introduced by segmented measurements. The implementation in JAX enhances the computational performances, demonstrating the efficiency of our optimisation framework. We will present the detector calibration using real data(-like) samples and discuss practical considerations for deploying this method in experimental settings. This differentiable detector simulation also has the potential to be applied to uncertainty quantification, inverse problem solving, and detector design optimisation.
