Expected geoneutrino signal at JUNO using local integrated 3-D refined crustal model

TL;DR

This paper presents JULOCI, a new 3-D crustal model for JUNO that improves geoneutrino signal predictions by integrating seismic, gravity, and heat flow data, aiding Earth's compositional studies.

Contribution

Introduction of JULOCI, a refined 3-D crustal model for JUNO, enhancing geoneutrino signal prediction accuracy over previous models.

Findings

JULOC-I predicts elevated uranium and thorium in southern China.

The model enables JUNO to test mantle models with improved precision.

JULOC-I improves understanding of Earth's crustal composition.

Abstract

Geoneutrinos serve as a potent tool for comprehending the radiogenic power and composition of Earth. Although geoneutrinos have been observed in prior experiments, the forthcoming generation of experiments,such as JUNO, will be necessary for fully harnessing their potential. Precise prediction of the crustal contribution is vital for interpreting particlephysics measurements in the context of geo-scientific inquiries. Nonetheless, existing models such as JULOC and GIGJ have limitations in accurately forecasting the crustal contribution. This paper introduces JULOCI, the novel 3-D integrated crustal model of JUNO, which employs seismic, gravity, rock sample, and heat flow data to precisely estimate the geoneutrino signal of the lithosphere. The model indicates elevated concentrations of uranium and thorium in southern China, resulting in unexpectedly strong geoneutrino signals.The accuracy of JULOC-I, coupled with a decade of experimental data, affords JUNO the opportunity to test multiple mantle models. Once operational, JUNO can validate the model predictions and enhance the precision of mantle measurements. All in all, the improved accuracy ofJULOC-I represents a substantial stride towards comprehending the geochemical distribution of the South China crust, offering a valuable tool for investigating the composition and evolution of the Earth through geoneutrinos.