GIGJ: a crustal gravity model of the Guangdong Province for predicting the geoneutrino signal at the JUNO experiment
Creators: name: Reguzzoni, M.
name: Rossi, L.
name: Baldoncini, M.
name: Callegari, I.
name: Poli, P.
name: Sampietro, D.
name: Strati, V.
name: Mantovani, F.
name: Andronico, G.
name: Antonelli, V.
name: Bellato, M.
name: Bernieri, E.
name: Brigatti, A.
name: Brugnera, R.
name: Budano, A.
name: Buscemi, M.
name: Bussino, S.
name: Caruso, R.
name: Chiesa, D.
name: Corti, D.
name: Corso, F. Dal
name: Ding, X. F.
name: Dusini, S.
name: Fabbri, A.
name: Fiorentini, G.
name: Ford, R.
name: Formozov, A.
name: Galet, G.
name: Garfagnini, A.
name: Giammarchi, M.
name: Giaz, A.
name: Grassi, M.
name: Insolia, A.
name: Isocrate, R.
name: Lippi, I.
name: Longhitano, F.
name: Presti, D. Lo
name: Lombardi, P.
name: Malyshkin, Y.
name: Marini, F.
name: Mari, S. M.
name: Martellini, C.
name: Meroni, E.
name: Mezzetto, M.
name: Miramonti, L.
name: Monforte, S.
name: Montuschi, M.
name: Nastasi, M.
name: Ortica, F.
name: Paoloni, A.
name: Parmeggiano, S.
name: Pedretti, D.
name: Pelliccia, N.
name: Pompilio, R.
name: Previtali, E.
name: Ranucci, G.
name: Re, A. C.
name: Ricci, B.
name: Romani, A.
name: Saggese, P.
name: Salamanna, G.
name: Sawy, F. H.
name: Settanta, G.
name: Sisti, M.
name: Sirignano, C.
name: Spinetti, M.
name: Stanco, L.
name: Verde, G.
name: Votano, L.
Publisher: name: arXiv
Year: 2019
Subjects: subject: Geophysics (physics.geo-ph)
subject: FOS: Physical sciences
subject: FOS: Physical sciences

description: Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3D numerical model constituted by ~46 x 10$^{3}$ voxels of 50 x 50 x 0.1 km, built by inverting gravimetric data over the 6° x 4° area centered at the Jiangmen Underground Neutrino Observatory (JUNO) experiment, currently under construction in the Guangdong Province (China). The a-priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P-wave velocity models and Moho depth maps, according to their own accuracy and spatial resolution. The inversion method allowed for integrating GOCE data with the a-priori information and regularization conditions through a Bayesian approach and a stochastic optimization. GIGJ fits the homogeneously distributed GOCE gravity data, characterized by high accuracy, with a ~1 mGal standard deviation of the residuals, compatible with the observation accuracy. Conversely to existing global models, GIGJ provides a site-specific subdivision of the crustal layers masses which uncertainties include estimation errors, associated to the gravimetric solution, and systematic uncertainties, related to the adoption of a fixed sedimentary layer. A consequence of this local rearrangement of the crustal layer thicknesses is a ~21% reduction and a ~24% increase of the middle and lower crust expected geoneutrino signal, respectively. Finally, the geophysical uncertainties of geoneutrino signals at JUNO produced by unitary uranium and thorium abundances distributed in the upper, middle and lower crust are reduced by 77%, 55% and 78%, respectively. The numerical model is available at http://www.fe.infn.it/u/radioactivity/GIGJ
description: 35 pages, 9 figures, 4 tables