End-to-end Differentiable Calibration and Reconstruction for Optical Particle Detectors

TL;DR

This paper introduces the first end-to-end differentiable simulator for optical particle detectors, enabling unified calibration and reconstruction with gradient-based optimization, improving efficiency and accuracy in particle physics experiments.

Contribution

It presents a novel differentiable framework that unifies simulation, calibration, and tracking in optical detectors, facilitating easier and more accurate analysis.

Findings

Achieves smooth, physically meaningful gradients across all detector stages.

Matches or surpasses traditional methods in accuracy and speed.

Flexible and adaptable to various detector geometries and materials.

Abstract

Large-scale homogeneous detectors with optical readouts are widely used in particle detection, with Cherenkov and scintillator neutrino detectors as prominent examples. Analyses in experimental physics rely on high-fidelity simulators to translate sensor-level information into physical quantities of interest. This task critically depends on accurate calibration, which aligns simulation behavior with real detector data, and on tracking, which infers particle properties from optical signals. We present the first end-to-end differentiable optical particle detector simulator, enabling simultaneous calibration and reconstruction through gradient-based optimization. Our approach unifies simulation, calibration, and tracking, which are traditionally treated as separate problems, within a single differentiable framework. We demonstrate that it achieves smooth and physically meaningful gradients across all key stages of light generation, propagation, and detection while maintaining computational efficiency. We show that gradient-based calibration and reconstruction greatly simplify existing analysis pipelines while matching or surpassing the performance of conventional non-differentiable methods in both accuracy and speed. Moreover, the framework's modularity allows straightforward adaptation to diverse detector geometries and target materials, providing a flexible foundation for experiment design and optimization. The results demonstrate the readiness of this technique for adoption in current and future optical detector experiments, establishing a new paradigm for simulation and reconstruction in particle physics.