Browsing by Autor "Ying Liu"

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Dissecting a Zombie: Shallow Volcanic Structure Revealed by Multiple Geophysical Data Sets at Uturuncu Volcano, Bolivia
(2021) Patricia MacQueen; Joachim Gottsmann; M. E. Pritchard; Nicola Young; Faustino Ticona J.; Ruben Tintaya; Thomas Hudson; Ying Liu; J. M. Kendall; Matthew J. Comeau
Uturuncu volcano in southern Bolivia is something of a “zombie” volcano – presumed dead, but showing signs of life. The volcano has not erupted in 250 kyr, but is exhibiting unrest in the form of ground deformation, seismicity, and active fumaroles. Elucidating the subsurface structure of the volcano is key for interpreting this recent unrest. Magnetotelluric measurements revealed alternating high and low resistivity anomalies at depths <10 km beneath the volcano, with a low-resistivity anomaly directly beneath Uturuncu. A key question is, what is the nature of this anomaly? To what extent is it partial melt, a hydrothermal brine reservoir, or a mature ore body? Knowing the density of this anomaly could distinguish between these scenarios, but existing density models of the area lack sufficient resolution. To address this issue, we collected additional gravity measurements on the Uturuncu edifice with 1.5 km spacing in November 2018. Gradient analysis and geophysical inversion of these data revealed several features: a 5 km diameter, high density anomaly beneath the summit of Uturuncu (1 – 3 km elev.), a 20 km diameter ring-shaped negative density anomaly around the volcano (-3 – 4 km elev.), a NNE trending, positive density anomaly northwest of the volcano (0 – 4 km elev.), and a NW trending, negative density anomaly to the southeast. These structures often (but not always) align with resistivity anomalies, features in new seismic tomography models, and relocated earthquake hypocenters. Based on a joint analysis of these data, we interpret the positive density anomaly as a crystallizing dacite pluton, and the negative density ring anomaly as a zone of hydrothermal alteration. Earthquakes around the edges of the crystallizing pluton may represent escaping fluids as the magma cools. The high density anomaly to the northwest likely represents a solidified pluton, and the low density anomaly to the southeast may represent a fractured fault zone. We posit that the alternating zones of high and low resistivity anomalies represent zones of low and high fluid/brine content, respectively. Based on this analysis we suggest that the unrest at Uturuncu is unlikely to be pre-eruptive. This study shows the value of joint analysis of multiple types of geophysical data in evaluating volcanic subsurface structure.
Single-view cone-beam x-ray luminescence optical tomography based on Group_YALL1 method
(IOP Publishing, 2019) Xin Liu; Xueli Tang; Yuexia Shu; Lili Zhao; Ying Liu; Tianyang Zhou
Single-view cone beam x-ray luminescence optical tomography (CB-XLOT) has the merit of short data acquisition time, which is important for resolving fast biological processes in vivo. However, challenges remain in the reconstruction of single-view CB-XLOT. In our previous work, by using the sparsity-based reconstruction method, we have demonstrated the feasibility of single-view CB-XLOT. But, when the imaging conditions become complicated (e.g. multiple adjacent nanophosphors (NPs) contained in imaged object), it is difficult to resolve each NP by the previous method. To solve the problem, we hereby present a sparsity reconstruction method based on group information, termed Group_YALL1. The imaging performance of single-view CB-XLOT can be further improved by utilizing the group sparsity characteristic of NPs as a priori knowledge of reconstruction constraint. To assess the capability of the method, we used a customized CB-XLOT/XCT system to perform the numerical simulation and physical phantom experiments. The experimental results demonstrate that compared with the former sparse reconstruction method (e.g. YALL1), the proposed Group_YALL1 method can accurately resolve the NPs embedded in the object, even if they are close to each other. The acquired location error is less than 1 mm. Hence, this method has the potential to greatly reduce the data acquisition time while preserving a high imaging quality.