Development of a comprehensive PMT optical model for the JUNO experiment

TL;DR

This paper develops a detailed optical model for JUNO's 20-inch PMTs, accounting for non-uniformities and material variances to improve detector simulation accuracy and energy response modeling.

Contribution

It introduces a comprehensive PMT optical model that incorporates non-uniform PDE, reflectance, and material properties, surpassing simplified uniform models.

Findings

More reflectance predicted for HPK PMTs

Less reflectance for NNVT PMTs

PDE variation within a few percent

Abstract

There are 17,612 20-inch photomultiplier tubes (PMTs) installed at the Jiangmen Underground Neutrino Observatory (JUNO). Developing a precise optical model for the PMTs is crucial for enhancing the accuracy of detector simulations and refining the energy response model at JUNO. In this study, we established a comprehensive PMT optical model based on prior studies, taking into account the non-uniformity of photon detection efficiency (PDE) across the PMT surface and the variances in PDE as well as reflections among different PMTs. By collecting reflectance data from 669 PMTs and utilizing PDE data from mass testing systems, we estimated the thickness maps of the photocathode (PC) and the anti-reflective coating (ARC) for each PMT. We also determined the collection efficiency (CE) by decomposing PDE with consideration of the optical processes occurring within the PMTs. The refractive index and extinction coefficient of both the PC and ARC, along with the escape factor, were evaluated over a broad wavelength range of 300~nm to 700~nm, covering the entire spectrum of interest for JUNO. Compared to the prediction from a simplified PMT optical model, which assumes uniform PC and ARC across all PMTs of the same type, the further developed PMT optical model yields much more reflectance for HPK PMTs and less for NNVT PMTs, and the change in PDE is at the level of a few percent. This comprehensive PMT optical model also provides a valuable reference for other PMT-based applications.