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Register a new userDetecting and quantifying palaeoseasonality in stalagmites using geochemical and modelling approaches
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Stalagmites are an extraordinarily powerful resource for the reconstruction of climatological palaeoseasonality. Here, we provide a comprehensive review of different types of seasonality preserved by stalagmites and methods for extracting this information. A new drip classification scheme is introduced, which facilitates the identification of stalagmites fed by seasonally responsive drips and which highlights the wide variability in drip types feeding stalagmites. This hydrological variability, combined with seasonality in Earth atmospheric processes, meteoric precipitation, biological processes within the soil, and cave atmosphere composition means that every stalagmite retains a different and distinct (but correct) record of environmental conditions. Replication of a record is extremely useful but should not be expected unless comparing stalagmites affected by the same processes in the same proportion. A short overview of common microanalytical techniques is presented, and suggested best practice discussed. In addition to geochemical methods, a new modelling technique for extracting meteoric precipitation and temperature palaeoseasonality from stalagmite d18O data is discussed and tested with both synthetic and real-world datasets. Finally, world maps of temperature, meteoric precipitation amount, and meteoric precipitation oxygen isotope ratio seasonality are presented and discussed, with an aim of helping to identify regions most sensitive to shifts in seasonality.
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Regional characterization of the continental crust has classically been performed through either geologic mapping, geochemical sampling, or geophysical surveys. Rarely are these techniques fully integrated, due to limits of data coverage, quality, and/or incompatible datasets. We combine geologic observations, geochemical sampling, and geophysical surveys to create a coherent 3-D geologic model of a 50 x 50 km upper crustal region surrounding the SNOLAB underground physics laboratory in Canada, which includes the Southern Province, the Superior Province, the Sudbury Structure and the Grenville Front Tectonic Zone. Nine representative aggregate units of exposed lithologies are geologically characterized, geophysically constrained, and probed with 109 rock samples supported by compiled geochemical databases. A detailed study of the lognormal distributions of U and Th abundances and of their correlation permits a bivariate analysis for a robust treatment of the uncertainties. A downloadable 3D numerical model of U and Th distribution defines an average heat production of 1.5$^{+1.4}_{-0.7}$$mu$W/m$^{3}$, and predicts a contribution of 7.7$^{+7.7}_{-3.0}$TNU (a Terrestrial Neutrino Unit is one geoneutrino event per 10$^{32}$ target protons per year) out of a crustal geoneutrino signal of 31.1$^{+8.0}_{-4.5}$TNU. The relatively high local crust geoneutrino signal together with its large variability strongly restrict the SNO+ capability of experimentally discriminating among BSE compositional models of the mantle. Future work to constrain the crustal heat production and the geoneutrino signal at SNO+ will be inefficient without more detailed geophysical characterization of the 3D structure of the heterogeneous Huronian Supergroup, which contributes the largest uncertainty to the calculation.
The dissolution of porous media in a geologic formation induced by the injection of massive amounts of CO2 can undermine the mechanical stability of the formation structure before carbon mineralization takes place. The geomechanical impact of geologic carbon storage is therefore closely related to the structural sustainability of the chosen reservoir as well as the probability of buoyancy driven CO2 leakage through caprocks. Here we show, with a combination of ex situ nanotomography and in situ microtomography, that the presence of dissolved CO2 in water produces a homogeneous dissolution pattern in natural chalk microstructure. This pattern stems from a greater apparent solubility of chalk and therefore a greater reactive subvolume in a sample. When a porous medium dissolves homogeneously in an imposed flow field, three geomechanical effects were observed: material compaction, fracturing and grain relocation. These phenomena demonstrated distinct feedbacks to the migration of the dissolution front and severely complicated the infiltration instability problem. We conclude that the presence of dissolved CO2 makes the dissolution front less susceptible to spatial and temporal perturbations in the strongly coupled geochemical and geomechanical processes.
Quantum entanglement is a key resource in quantum technology, and its quantification is a vital task in the current Noisy Intermediate-Scale Quantum (NISQ) era. This paper combines hybrid quantum-classical computation and quasi-probability decomposition to propose two variational quantum algorithms, called Variational Entanglement Detection (VED) and Variational Logarithmic Negativity Estimation (VLNE), for detecting and quantifying entanglement on near-term quantum devices, respectively. VED makes use of the positive map criterion and works as follows. Firstly, it decomposes a positive map into a combination of quantum operations implementable on near-term quantum devices. It then variationally estimates the minimal eigenvalue of the final state, obtained by executing these implementable operations on the target state and averaging the output states. Deterministic and probabilistic methods are proposed to compute the average. At last, it asserts that the target state is entangled if the optimized minimal eigenvalue is negative. VLNE builds upon a linear decomposition of the transpose map into Pauli terms and the recently proposed trace distance estimation algorithm. It variationally estimates the well-known logarithmic negativity entanglement measure and could be applied to quantify entanglement on near-term quantum devices. Experimental and numerical results on the Bell state, isotropic states, and Breuer states show the validity of the proposed entanglement detection and quantification methods.
Experimental microstylolites have been observed at stressed contacts between quartz grains loaded for several weeks in the presence of an aqueous silica solution, at 350 8C and 50 MPa of differential stress. Stereoscopic analysis of pairs of SEM images yielded a digital elevation model of the surface of the microstylolites. Fourier analyses of these microstylolites reveal a self-affine roughness (with a roughness exponent H of 1.2). Coupled with observations of close interactions between dissolution pits and stylolitic peaks, these data illustrate a possible mechanism for stylolite formation. The complex geometry of stylolite surfaces is imposed by the interplay between the development of dissolution peaks in preferential locations (fast dissolution pits) and the mechanical properties of the solid-fluid-solid interfaces. Simple mechanical modeling expresses the crucial competition that could rule the development of microstylolites: (i) a stress-related process, modeled in terms of the stiffness of springs that activate the heterogeneous dissolution rates of the solid interface, promotes the deflection. In parallel, (ii) the strength of the solid interface, modeled in terms of the stiffness of a membrane, is equivalent to a surface tension that limits the deflection and opposes its development. The modeling produces stylolitic surfaces with characteristic geometries varying from conical to columnar when both the effect of dissolution-rate heterogeneity and the strength properties of the rock are taken into account. A self-affine roughness exponent (Hz1.2) measured on modeled surfaces is comparable with natural stylolites at small length scale and experimental microstylolites.
In countries with a moderate seismic hazard, the classical methods developed for strong motion prone countries to estimate the seismic behaviour and subsequent vulnerability of existing buildings are often inadequate and not financially realistic. The main goals of this paper are to show how the modal analysis can contribute to the understanding of the seismic building response and the good relevancy of a modal model based on ambient vibrations for estimating the structural deformation under moderate earthquakes. We describe the application of an enhanced modal analysis technique (Frequency Domain Decomposition) to process ambient vibration recordings taken at the Grenoble City Hall building (France). The frequencies of ambient vibrations are compared with those of weak earthquakes recorded by the French permanent accelerometric network (RAP) that was installed to monitor the building. The frequency variations of the building under moderate earthquakes are shown to be slight (~2%) and therefore ambient vibration frequencies are relevant over the elastic domain of the building. The modal parameters extracted from ambient vibrations are then used to determine the 1D lumped-mass model in order to reproduce the inter-storey drift under weak earthquakes and to fix a 3D numerical model that could be used for strong earthquakes. The correlation coefficients between data and synthetic motion are close to 80% and 90% in horizontal directions, for the 1D and 3D modelling, respectively.
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