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The goal of this work is to investigate under which circumstances the tidal response of a stratified body can be approximated by that of a homogeneous body. We show that any multilayered planet model can be approximated by a homogeneous body, with the same dissipation of tidal energy as a function of the excitation frequency, as long as the rheology of the homogeneous model is sufficiently complex. Moreover we provide two straightforward methods for finding the parameters of the homogeneous rheology that would exhibit the same tidal response as the layered body. These results highlight the fact that the two models cannot be distinguished from each other only by the measurement of the second degree tidal Love number and quality factor, and that we do not need the complexity of the multilayer planet model in order to estimate its tidal dissipation. The methodology promises a great simplification of the treatment of multilayered bodies in numerical simulations because the treatment of a homogeneous body -- even with a complex rheological model -- can be computationally better handled than that of a multilayered planet., 10 pages, 11 figures, accepted for publication in MNRAS

Most theoretical descriptions of stresses induced by freezing are rooted in the (generalized) Clapeyron equation, which predicts the pressure that a solid can exert as it cools below its melting temperature. This equation is central for topics ranging beyond glaciology to geomorphology, civil engineering, food storage, and cryopreservation. However, it has inherent limitations, requiring isotropic solid stresses and conditions near bulk equilibrium. Here, we examine when the Clapeyron equation is applicable by providing a rigorous derivation that details all assumptions. We demonstrate the natural extension for anisotropic stress states, and we show how the temperature and pressure ranges for validity depend on well-defined material properties. Finally, we demonstrate how the range of applicability of the (linear) Clapeyron equation can be extended by adding higher-order terms, yielding results that are in good agreement with experimental data for the pressure melting of ice., Comment: 2 Figures

Transversely isotropic (TI) media with the frequency-independent quality-factor elements (also called “constant- Q” transverse isotropy) are often used to describe attenuation anisotropy in sedimentary rocks. The attenuation coefficients in constant- Q TI models can be conveniently defined in terms of the Thomsen-type attenuation-anisotropy parameters. Recent research indicates that not all those parameters for such constant- Q media are frequency-independent. Here, we present concise analytic formulas for the Thomsen-type attenuation parameters for Kjartansson’s constant- Q TI model and show that one of them ( δ Q) varies with frequency. The analytic expression for δ Q helps evaluate the frequency dependence of the normalized attenuation coefficients of P- and SV-waves by introducing the newly defined “dispersion factors.” These factors are frequency-independent and expressed in terms of the Thomsen and Thomsen-type parameters defined at a specified reference frequency. Viscoacoustic constant- Q transverse isotropy is also discussed as a special case, for which the elliptical condition and simplified expressions for the parameters δ Q and δ Q are derived. Our results show that, in the presence of significant absorption, the attenuation coefficients of the constant- Q model vary with frequency for oblique propagation with respect to the symmetry axis. This variation needs to be taken into account when applying the spectral-ratio method and other attenuation-analysis techniques.

Modern-day reservoir management and monitoring of geological carbon storage increasingly call for costly time-lapse seismic data collection. In this letter, we show how techniques from graph theory can be used to optimize acquisition geometries for low-cost sparse 4D seismic. Based on midpoint-offset domain connectivity arguments, the proposed algorithm automatically produces sparse non-replicated time-lapse acquisition geometries that favor wavefield recovery.

The ``big'' seismic data not only acquired by seismometers but also acquired by vibrometers installed in buildings and infrastructure and accelerometers installed in smartphones will be certainly utilized for seismic research in the near future. Since it is impractical to utilize all the seismic big data in terms of the computational cost, methods which can select observation sites depending on the purpose are indispensable. We propose an observation site selection method for the accurate reconstruction of the seismic wavefield by process-driven approaches. The proposed method selects observation sites suitable for accurately estimating physical model parameters such as subsurface structures and source information to be input into a numerical simulation of the seismic wavefield. The seismic wavefield is reconstructed by the numerical simulation using the parameters estimated based on the observed signals at only observation sites selected by the proposed method. The observation site selection in the proposed method is based on the sensitivity of each observation site candidate to the physical model parameters; the matrix corresponding to the sensitivity is constructed by approximately calculating the derivatives based on the simulations, and then, observation sites are selected by evaluating the quantity of the sensitivity matrix based on the D-optimality criterion proposed in the optimal design of experiments. In the present study, physical knowledge on the sensitivity to the parameters such as seismic velocity, layer thickness, and hypocenter location was obtained by investigating the characteristics of the sensitivity matrix. Furthermore, the effectiveness of the proposed method was shown by verifying the accuracy of seismic wavefield reconstruction using the observation sites selected by the proposed method., Comment: Accepted manuscript for publication in Geophysical Journal International

This paper evaluates the seismic fragility of a two-span reinforced concrete (RC) bridge with shape memory alloy (SMA)-restrained rocking (SRR) columns through machine learning (ML) techniques. SRR columns incorporate a combination of replaceable superelastic NiTi (SMA) links and mild steel energy-dissipating links to achieve self-centering and energy dissipation, respectively, while their rocking joints are protected against compressive concrete damage through steel jacketing. To produce seismic fragility functions, initially, multi-parameter probabilistic seismic demand models (PSDMs) are generated for various engineering demand parameters through five different ML techniques (including neural network) and considering various sources of uncertainty, and the most accurate PSDMs are selected. The selected PSDMs are then interpreted using four different methods to investigate the effects of two key SRR column design parameters (self-centering coefficient and SMA link initial strain) and ambient temperature on the seismic performance of SRR columns. Subsequently, using neural networks, the PSDMs developed earlier, and appropriate capacity models, multi-parameter fragility functions are developed for various bridge damage states. After examining the effects of the two SRR column design parameters on the seismic fragility of the bridge, its seismic fragility is compared with those of the same bridge with monolithic RC and posttensioned (PT) rocking columns. It is shown that, in general, increasing the initial strain of the SMA links and decreasing the self-centering coefficient as possible (i.e., without compromising the self-centering) reduce the overall bridge damage. In addition, even considering the ambient temperature's uncertainty, SRR columns are proven, at least, as effective as PT columns in mitigating the seismic damage of the bridges of monolithic RC columns.

We conducted a TEM study of an unusual oxide-silicate composite presolar grain (F2-8) from the unequilibrated ordinary chondrite Semarkona. The presolar composite grain is relatively large, has an amoeboidal shape, and contains Mg-rich olivine, Mg-Al spinel, and Ca-rich pyroxene. The shape and phase assemblage are reminiscent of amoeboid-olivine-aggregates and add to the growing number of TEM observations of presolar refractory inclusion-like (CAIs and AOAs) grains. In addition to the dominant components, F2-8 also contains multiple subgrains, including an alabandite-oldhamite composite grain within the olivine and several magnetite subgrains within the Mg-Al spinel. We argue that the olivine, Mg-Al spinel, and alabandite-oldhamite formed by equilibrium condensation, whereas the Ca-rich pyroxene formed by non-equilibrium condensation, all in an M-type AGB star envelope. On the other hand, the magnetite subgrains are likely the result of aqueous alteration on the Semarkona asteroidal parent body. Additional evidence of secondary processing includes Fe-enrichment in the Mg-Al spinel and olivine, elevated Al contents in the olivine, and beam sensitivity and a modulated structure for the olivine. Compound presolar grains record condensation conditions over a wide range of temperatures. Additionally, the presence of several different presolar phases in a composite grain can impart information on the relative rates and effects of post-condensation processing in a range of environments, including the interstellar medium, solar nebula, and the host asteroid parent body. The TEM observations of F2-8 provide insights across the lifetime of the grain from its formation by condensation in an M-type AGB star envelope, its transit through the interstellar medium, and aqueous alteration during its residence on Semarkona's asteroidal parent body., 36 total pages, including 6 figures, 3 supplemental figures, 4 tables, and 2 supplemental tables

SUMMARYThe rheology of rocks transitions from a cataclastic brittle behaviour to plastic flow with increasing pressure and temperature. This brittle-plastic transition is empirically observed to occur when the material strength becomes lower than the confining stress, which is termed Goetze’s criterion. Such a criterion works well for most silicates but is not universal for all materials. We aim to determine the microphysical controls and stress–strain behaviour of rocks in the brittle-plastic transition. We use a micromechanical approach due to Horii and Nemat-Nasser, and consider representative volume elements containing sliding wing-cracks and plastic zones. We find solutions for frictional slip, plastic deformation and crack opening at constant confining pressure, and obtain stress–strain evolution. We show that the brittle-plastic transition depends on the confining stress, fracture toughness and plastic yield stress but also critically on the friction coefficient on pre-existing defects. Materials with low friction are expected to be more brittle, and experience transition to fully plastic flow at higher pressure than anticipated from Goetze’s criterion. The overall success of Goetze’s criterion for the brittle-plastic transition in rocks is likely arising from the low toughness, high strength and medium friction coefficient character of most rock forming minerals.

The spatio-temporal properties of seismicity give us incisive insight into the stress state evolution and fault structures of the crust. Empirical models based on self-exciting point-processes continue to provide an important tool for analyzing seismicity, given the epistemic uncertainty associated with physical models. In particular, the epidemic-type aftershock sequence (ETAS) model acts as a reference model for studying seismicity catalogs. The traditional ETAS model uses simple parametric definitions for the background rate of triggering-independent seismicity. This reduces the effectiveness of the basic ETAS model in modelling the temporally complex seismicity patterns seen in seismic swarms that are dominated by aseismic tectonic processes such as fluid injection rather than aftershock triggering. In order to robustly capture time-varying seismicity rates, we introduce a deep Gaussian process formulation for the background rate as an extension to ETAS. Gaussian processes (GPs) are a robust non-parametric model for function spaces with covariance structure. By conditioning the lengthscale structure of a GP with another GP, we have a deep-GP: a probabilistic, hierarchical model that automatically tunes its structure to match data constraints. We show how the deep-GP-ETAS model can be efficiently sampled by making use of a Metropolis-within-Gibbs scheme, taking advantage of the branching process formulation of ETAS and a stochastic partial differential equation (SPDE) approximation for Mat\'ern GPs. We illustrate our method using synthetic examples, and show that the deep-GP-ETAS model successfully captures multiscale temporal behavior in the background forcing rate of seismicity. We then apply the results to two real-data catalogues: the Ridgecrest, CA July 5 2019 Mw 7.1 event catalogue and the 2016--2019 Cahuilla, CA earthquake swarm., Comment: Updated abstract to include more information

The properties of collisionless shocks are frequently assessed in the magnetohydrodynamics (MHD) model. Yet, in a collisionless plasma, an ambient magnetic field can sustain a stable anisotropy in the upstream or the downstream, resulting in a departure from the MHD predicted behavior. We present a model allowing to derive the downstream anisotropy, hence the shock density jump, in terms of the upstream quantities. For simplicity, the case of a parallel shock in pair plasma is considered. Contrary to previous works where the upstream was assumed isotropic, here the upstream anisotropy $A=T_\perp/T_\parallel$ is a free parameter. The strong sonic shock regime is formally identical to the isotropic upstream case. Yet, for intermediate sonic Mach numbers, a variety of behaviors appear as a result of the anisotropy of the upstream., Comment: To appear in MNRAS, 8 pages, 6 figures

Many soils and other porous media exhibit dual- or multi-porosity type features. In a previous study (Seki et al., 2022) we presented multimodal water retention and closed-form hydraulic conductivity equations for such media. The objective of this study is to show that the proposed equations are practically useful. Specifically, dual-BC (Brooks and Corey)-CH (common head) (DBC), dual-VG (van Genuchten)-CH (DVC), and KO (Kosugi)1BC2-CH (KBC) models were evaluated for a broad range of soil types. The three models showed good agreement with measured water retention and hydraulic conductivity data over a wide range of pressure heads. Results were obtained by first optimizing water retention parameters and then optimizing the saturated hydraulic conductivity (K s ) and two parameters (p, q) or (p, r) in the general hydraulic conductivity equation. Although conventionally the tortuosity factor p is optimized and (q, r) fixed, sensitivity analyses showed that optimization of two parameters (p + r, qr) is required for the multimodal models. For 20 soils from the UNSODA database, the average R 2 for log (hydraulic conductivity) was highest (0.985) for the KBC model with r = 1 and optimization of (K s , p, q). This result was almost equivalent (0.973) to the DVC model with q = 1 and optimization of (K s , p, r); both were higher than R 2 for the widely used Peters model (0.956) when optimizing (K s , p, a, ω). The proposed equations are useful for practical applications while mathematically being simple and consistent.

We apply a deep learning model to segment and identify rock characteristics based on a Structure-from-Motion orthomap and digital elevation model of a rocky fault scarp in the Volcanic Tablelands, eastern California. By post-processing the deep learning results, we build a semantic rock map and analyze rock trait distributions. The resulting semantic map contains nearly 230,000 rocks with effective diameters ranging from 2 cm to 250 cm. Rock trait distributions provide a new perspective on rocky fault scarp development and extend past research on scarp geometry including slope, height, and length. Heatmaps indicate rock size spatial distributions on the fault scarp and surrounding topographic flats. Median grain size changes perpendicular to the fault scarp trace with the largest rocks exposed on and downslope from the scarp footwall. Correlation analyses of the segmented fault scarp illustrate the relationship between rock trait statistics and fault scarp geomorphology. Local fault scarp height correlates with median grain size (R2 of 0.6), the mean grain size of the largest rocks (R2 of 0.76), and the ratio of the number of small to large rocks (R2 of 0.40). The positive correlation (R2 of 0.81) between local fault scarp height and standard deviation of grain size suggests that rocks on a higher fault scarp are less well sorted. The correlation analysis between fault scarp height and rock orientation statistics supports a particle transportation model in which locally higher fault scarps have relatively more rocks with long axes parallel to fault scarp trace because rocks have a larger distance to roll and orient the long axes. Our work demonstrates a data-driven approach to geomorphology based on rock trait distributions, promising a greater understanding of fault scarp formation, as well as many other applications for which granulometry is an indicator of process.

The development of new earthquake forecasting models is often motivated by one of the following complementary goals: to gain new insights into the governing physics and to produce improved forecasts quantified by objective metrics. Often, one comes at the cost of the other. Here, we propose a question-driven ensemble (QDE) modeling approach to address both goals. We first describe flexible epidemic-type aftershock sequence (ETAS) models in which we relax the assumptions of parametrically defined aftershock productivity and background earthquake rates during model calibration. Instead, both productivity and background rates are calibrated with data such that their variability is optimally represented by the model. Then we consider 64 QDE models in pseudoprospective forecasting experiments for southern California and Italy. QDE models are constructed by combining model parameters of different ingredient models, in which the rules for how to combine parameters are defined by questions about the future seismicity. The QDE models can be interpreted as models that address different questions with different ingredient models. We find that certain models best address the same issues in both regions, and that QDE models can substantially outperform the standard ETAS and all ingredient models. The best performing QDE model is obtained through the combination of models allowing flexible background seismicity and flexible aftershock productivity, respectively, in which the former parameterizes the spatial distribution of background earthquakes and the partitioning of seismicity into background events and aftershocks, and the latter is used to parameterize the spatiotemporal occurrence of aftershocks.

Seismic phase association connects earthquake arrival-time measurements to their causative sources. Effective association must determine the number of discrete events, their location, and origin times, and it must differentiate real arrivals from measurement artifacts. The advent of deep-learning (DL) pickers, which provide high rates of picks from closely overlapping small-magnitude earthquakes, motivates revisiting the phase association problem and approaching it using the methods of DL. We have developed a graph neural network associator that simultaneously predicts both source space–time localization, and discrete source-arrival association likelihoods. The method is applicable to arbitrary geometry, time-varying seismic networks of hundreds of stations, and is robust to high rates of sources and input picks with variable noise and quality. Our Graph Earthquake Neural Interpretation Engine (GENIE) uses one graph to represent the station set and another to represent the spatial source region. GENIE learns relationships from data in this combined representation that enable it to determine robust source and source-arrival associations. We train on synthetic data, and test our method on real data from the northern California seismic network using input generated by the PhaseNet DL phase picker. We successfully re-detect ∼96% of all events M >1 reported by the U.S. Geological Survey (USGS) during 500 random days between 2000 and 2022. Over a 100-day continuous interval of processing in 2017–2018, we detect ∼4× the number of events reported by the USGS. Our new events have small-magnitude estimates below the magnitude of completeness of the USGS catalog, and are located close to the active faults and quarries in the region. Our results demonstrate that GENIE can effectively solve the association problem under complex seismic monitoring conditions.

Some families of carbonaceous chondrites are rich in prebiotic organics that may have contributed to the origin of life on Earth and elsewhere. However, the formation and chemical evolution of complex soluble organic molecules from interstellar precursors under relevant parent body conditions has not been thoroughly investigated. In this study, we approach this topic by simulating meteorite parent body aqueous alteration of interstellar residue analogs. The distributions of amines and amino acids are qualitatively and quantitatively investigated and linked to closing the gap between interstellar and meteoritic prebiotic organic abundances. We find that the abundance trend of methylamine > ethylamine> glycine > serine > alanine > \b{eta}-alanine does not change from pre- to post-aqueous alteration, suggesting that certain cloud conditions have an influential role on the distributions of interstellar-inherited meteoritic organics. However, the abundances for most of the amines and amino acids studied here varied by about 2-fold when aqueously processed for 7 days at 125 {\deg}C, and the changes in the {\alpha}- to \b{eta}-alanine ratio were consistent with those of aqueously altered carbonaceous chondrites, pointing to an influential role of meteorite parent body processing on the distributions of interstellar-inherited meteoritic organics. We detected higher abundances of {\alpha}- over \b{eta}-alanine, which is opposite to what is typically observed in aqueously altered carbonaceous chondrites; these results may be explained by at least the lack of minerals and insoluble organic matter-relevant materials in the experiments. The high abundance of volatile amines in the non-aqueously altered samples suggests that these types of interstellar volatiles can be efficiently transferred to asteroids and comets, supporting the idea of the presence of interstellar organics in solar system objects., Comment: see overview https://www.nasa.gov/feature/goddard/2023/nasa-scientists-study-life-origins-by-simulating-a-mini-cosmic-evolution/

The interpolation and reconstruction of missing traces is a crucial step in seismic data processing, moreover it is also a highly ill-posed problem, especially for complex cases such as high-ratio random discrete missing, continuous missing and missing in fault-rich or salt body surveys. These complex cases are rarely mentioned in current works. To cope with complex missing cases, we propose Multi-Dimensional Adversarial GAN (MDA GAN), a novel 3-D GAN framework. It keeps anisotropy and spatial continuity of the data after 3D complex missing reconstruction using three discriminators. The feature stitching module is designed and embedded in the generator to retain more information of the input data. The Tanh cross entropy (TCE) loss is derived, which provides the generator with the optimal reconstruction gradient to make the generated data smoother and continuous. We experimentally verified the effectiveness of the individual components of the study and then tested the method on multiple publicly available data. The method achieves reasonable reconstructions for up to 95% of random discrete missing and 100 traces of continuous missing. In fault and salt body enriched surveys, MDA GAN still yields promising results for complex cases. Experimentally it has been demonstrated that our method achieves better performance than other methods in both simple and complex cases.https://github.com/douyimin/MDA_GAN, Comment: This work has been submitted to journal for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Seismic waveform modeling is a powerful tool for determining earth structure models and unraveling earthquake rupture processes, but it is usually computationally expensive. We introduce a scheme to vastly accelerate these calculations with a recently developed machine learning paradigm called the neural operator. Once trained, these models can simulate a full wavefield at negligible cost. We use a U-shaped neural operator to learn a general solution operator to the 2-D elastic wave equation from an ensemble of numerical simulations performed with random velocity models and source locations. We show that full-waveform modeling with neural operators is nearly two orders of magnitude faster than conventional numerical methods, and more importantly, the trained model enables accurate simulation for velocity models, source locations, and mesh discretization distinctly different from the training dataset. The method also enables convenient full-waveform inversion with automatic differentiation.

The timing of formation for the first planetesimals determines the mode of planetary accretion and their geophysical and compositional evolution. Astronomical observations of circumstellar discs and Solar System geochronology provide evidence for planetesimal formation during molecular cloud collapse, much earlier than previously estimated. Here, we present distinct observational evidence from white dwarf planetary systems for planetesimal formation occurring during the first few hundred thousand years after cloud collapse in exoplanetary systems. A significant fraction of white dwarfs have accreted planetary material rich in iron core or mantle material. In order for the exo-asteroids accreted by white dwarfs to form iron cores, substantial heating is required. By simulating planetesimal evolution and collisional evolution we show that the most likely heat source is short-lived radioactive nuclides such as Al-2 (half life of approximately 0.7 Myr). Core-rich materials in the atmospheres of white dwarfs, therefore, provide independent evidence for rapid planetesimal formation, concurrent with star formation., Comment: Accepted to Nature Astronomy

Despite its critical role in the study of earthquake processes, numerical simulation of the entire stages of fault rupture remains a formidable task. The main challenges in simulating a fault rupture process include complex evolution of fault geometry, frictional contact, and off-fault damage over a wide range of spatial and temporal scales. Here, we develop a phase-field model for quasi-dynamic fault nucleation, growth, and propagation, which features two standout advantages: (i) it does not require any sophisticated algorithms to represent fault geometry and its evolution; and (ii) it allows for modeling fault nucleation, propagation, and off-fault damage processes with a single formulation. Built on a recently developed phase-field framework for shear fractures with frictional contact, the proposed formulation incorporates rate- and state-dependent friction, radiation damping, and their impacts on fault mechanics and off-fault damage. We show that the numerical results of the phase-field model are consistent with those obtained from well-verified approaches that model the fault as a surface of discontinuity, without suffering from the mesh convergence issue in the existing continuous approaches to fault rupture (e.g. the stress glut method). Further, through numerical examples of fault propagation in various settings, we demonstrate that the phase-field approach may open new opportunities for investigating complex earthquake processes that have remained overly challenging for the existing numerical methods.

SUMMARY Reconstruction of the distribution of ground motion due to an earthquake is one of the key technologies for the prediction of seismic damage to infrastructure. Particularly, the immediate reconstruction of the spatially continuous wavefield is valuable for decision-making of disaster response decisions in the initial phase. For a fast and accurate reconstruction, utilization of prior information is essential. In fluid mechanics, full-state recovery, which recovers the full state from sparse observation using a data-driven model reduced-order model, is actively used. In this study, the framework developed in the field of fluid mechanics is applied to seismic wavefield reconstruction. A seismic wavefield reconstruction framework based on compressed sensing using the data-driven reduced-order model (ROM) is proposed and its characteristics are investigated through numerical experiments. The data-driven ROM is generated from the data set of the wavefield using the singular value decomposition. The spatially continuous seismic wavefield is reconstructed from the sparse and discrete observation and the data-driven ROM. The observation sites used for reconstruction are effectively selected by the sensor optimization method for linear inverse problems based on a greedy algorithm. The proposed framework was applied to simulation data of theoretical waveform with the subsurface structure of the horizontally stratified three layers. The validity of the proposed method was confirmed by the reconstruction based on the noise-free observation. Since the ROM of the wavefield is used as prior information, the reconstruction error is reduced to an approximately lower error bound of the present framework, even though the number of sensors used for reconstruction is limited and randomly selected. In addition, the reconstruction error obtained by the proposed framework is much smaller than that obtained by the Gaussian process regression. For the numerical experiment with noise-contaminated observation, the reconstructed wavefield is degraded due to the observation noise, but the reconstruction error obtained by the present framework with all available observation sites is close to a lower error bound, even though the reconstructed wavefield using the Gaussian process regression is fully collapsed. Although the reconstruction error is larger than that obtained using all observation sites, the number of observation sites used for reconstruction can be reduced while minimizing the deterioration and scatter of the reconstructed data by combining it with the sensor optimization method. Hence, a better and more stable reconstruction of the wavefield than randomly selected observation sites can be realized, even if the reconstruction is carried out with a smaller number of observations with observation noise, by combining it with the sensor optimization method.

Magnetic helicity is a fundamental constraint in both ideal and resistive magnetohydrodynamics. Measurements of magnetic helicity density on the Sun and other stars are used to interpret the internal behaviour of the dynamo generating the global magnetic field. In this note, we study the behaviour of the global relative magnetic helicity in three self-consistent spherical dynamo solutions of increasing complexity. Magnetic helicity describes the global linkage of the poloidal and toroidal magnetic fields (weighted by magnetic flux), and our results indicate that there are preferred states of this linkage. This leads us to propose that global magnetic reversals are, perhaps, a means of preserving this linkage, since, when only one of the poloidal or toroidal fields reverses, the preferred state of linkage is lost. It is shown that magnetic helicity indicates the onset of reversals and that this signature may be observed at the outer surface., Comment: To appear in Geophysical and Astrophysical Fluid Dynamics [Accepted 2022-10-14]

Delimiting salt inclusions from migrated images is a time-consuming activity that relies on highly human-curated analysis and is subject to interpretation errors or limitations of the methods available. We propose to use migrated images produced from an inaccurate velocity model (with a reasonable approximation of sediment velocity, but without salt inclusions) to predict the correct salt inclusions shape using a Convolutional Neural Network (CNN). Our approach relies on subsurface Common Image Gathers to focus the sediments' reflections around the zero offset and to spread the energy of salt reflections over large offsets. Using synthetic data, we trained a U-Net to use common-offset subsurface images as input channels for the CNN and the correct salt-masks as network output. The network learned to predict the salt inclusions masks with high accuracy; moreover, it also performed well when applied to synthetic benchmark data sets that were not previously introduced. Our training process tuned the U-Net to successfully learn the shape of complex salt bodies from partially focused subsurface offset images., Comment: Manuscript published at Geophysics

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., We explore experimentally possible explanations of the polarization curves of the sunlight reflected by the Barbarian asteroids. Their peculiar polarization curves are characterized by a large-inversion angle, around 30°, which could be related to the presence of FeO-bearing spinel embedded in Calcium–Aluminum inclusions. In order to test this hypothesis, we have measured the phase function and degree of linear polarization of six samples of Mg-rich olivine and spinel. For each material, we have analysed the light scattering properties of a millimeter-sized grain and of two powdered samples with size distributions in the micrometer size range. The three spinel samples show a well-defined negative polarization branch with an inversion phase angle located around 24°–30°. In contrast, in the case of the olivine samples, the inversion angle is highly dependent on particle size and tends to decrease for larger sizes. We identify the macroscopic geometries as a possible explanation for the evident differences in the polarization curves between olivine and spinel millimeter samples. Although the polarization behaviour in near backscattering of the Barbara asteroid is similar to that of our spinel mm-sized sample in random orientation, this similarity could result in part from crystal retro-reflection rather than composition. This is part of an ongoing experimental project devoted to test separately several components of CV3-like meteorites, representative of the Barbarians composition, to disentangle their contributions to the polarization behaviour of these objects. © 2022 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society., This work has been funded by the Spanish State Research Agency and Junta de Andalucía through grants LEONIDAS (RTI2018-095330-B-100) and P18-RT-1854, and the Center of Excellence Severo Ochoa award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). JC Gómez Martín and T Jardiel acknowledge financial support from the European Science Foundation (ESF) and the Ramón y Cajal Program of MICINN. Research by KM supported by the Academy of Finland grants No. 345115 and 336546.

Bayesian inference applied to microseismic activity monitoring allows the accurate location of microseismic events from recorded seismograms and the estimation of the associated uncertainties. However, the forward modelling of these microseismic events, which is necessary to perform Bayesian source inversion, can be prohibitively expensive in terms of computational resources. A viable solution is to train a surrogate model based on machine learning techniques, to emulate the forward model and thus accelerate Bayesian inference. In this paper, we substantially enhance previous work, which considered only sources with isotropic moment tensors. We train a machine learning algorithm on the power spectrum of the recorded pressure wave and show that the trained emulator allows complete and fast event locations for $\textit{any}$ source mechanism. Moreover, we show that our approach is computationally inexpensive, as it can be run in less than 1 hour on a commercial laptop, while yielding accurate results using less than $10^4$ training seismograms. We additionally demonstrate how the trained emulators can be used to identify the source mechanism through the estimation of the Bayesian evidence. Finally, we demonstrate that our approach is robust to real noise as measured in field data. This work lays the foundations for efficient, accurate future joint determinations of event location and moment tensor, and associated uncertainties, which are ultimately key for accurately characterising human-induced and natural earthquakes, and for enhanced quantitative seismic hazard assessments., Comment: 17+4 pages, 13+3 figures, 2 tables. Matches version published in GJI, including extra tests with realistic noise and network configuration. Code available at https://github.com/alessiospuriomancini/seismoML/tree/main/Piras_2022

Presolar grains are trace components in chondrite matrices. Their abundances and compositions have been systematically studied in carbonaceous chondrites but rarely in situ in other major chondrite classes. We have conducted a NanoSIMS isotopic search for presolar grains with O- and C-anomalous isotopic compositions in the matrices of the unequilibrated ordinary chondrites Semarkona, Meteorite Hills 00526, and Northwest Africa 8276. The matrices of even the most primitive ordinary chondrites have been aqueously altered and/or thermally metamorphosed, destroying their presolar grain populations to varying extents. In addition to randomly placed isotope maps, we targeted recently reported, relatively pristine Semarkona matrix areas to better explore the original inventory of presolar grains. In all samples, we found a total of 122 O-anomalous grains (silicates + oxides), 79 SiC grains, and 22 C-anomalous carbonaceous grains (organics, graphites). Average matrix-normalized abundances are 151 ppm O-anomalous grains, 53 ppm SiC grains and 56 ppm carbonaceous grains in Semarkona, 55 ppm (O-anom.), 22 ppm (SiC) and 3 ppm (carb.) in MET 00526 and 12 ppm (O-anom.), 15 ppm (SiC) and 1 ppm (carb.) in NWA 8276. In relatively pristine ordinary chondrites and in primitive carbonaceous and C-ungrouped chondrites, the O and C isotopic composition of presolar grains and their matrix-normalized abundances are similar, despite the likely differences in chondrite-formation time and nebular location. These results suggest a relatively homogenous distribution of presolar dust across major chondrite-forming reservoirs in the solar nebula. Secondary asteroidal processes are mainly responsible for differences in presolar grain abundances between and within chondrites, highlighting the need to identify and target the most pristine chondrite matrices for such studies., Published in Geochimica et Cosmochimica Acta. Main text: 36 pp with 7 figures and 1 table. Supplement: 13 pp, 2 tables, 2 figures

A systematic study of ionospheric scintillation at the low-latitudes, especially around the Equatorial Ionization Anomaly (EIA) and the magnetic equator, is essential in understanding the dynamics of ionospheric variation and related physical processes. Our study involves NavIC $S_{4_C}$ observations over Indore and Hyderabad. Additionally, GPS $S_{4_C}$ observations over Indore were analyzed, under disturbed as well as quiet time ionospheric conditions from September 2017 through 2019, falling in the declining phase of the solar cycle 24. The $S_{4_C}$ observations were further analyzed using proxy parameters: ROT and ROTI. These results have been obtained from three satellites of the NavIC constellation (PRNs 2, 5, and 6). The onset times of scintillations \textbf{were} observed to be around 19:30 LT (h) and 20:30 LT (h) for Hyderabad and Indore respectively, while the $S_{4_C}$ peak values occurred between 22:00 LT (h) and 23:00 LT (h). The reliability of NavIC was evaluated using scattering coefficients that revealed a good correlation across the pair of signals during quiet time ionospheric conditions. The observations clearly show that the amplitude scintillation of the NavIC signal follows the Nakagami-m distribution along with the $\alpha-\mu$ distribution as a depiction of the deep power fades caused by scintillation on these signals. This paper shows the impact of such systematic studies near these locations for the first time, in improving the understanding of the dynamic nature of low-latitude ionosphere under low solar activity conditions.

Funder: Albert-Ludwigs-Universität Freiburg im Breisgau (1016), The aim of this study is to understand the strength behaviour and fragment size of rocks during indirect, quasi-static and dynamic tensile tests. Four rocks with different lithological characteristics, namely: basalt, granite, sandstone, and marble were selected for this study. Brazilian disc experiments were performed over a range of strain rates from ~ 10–5 /s to 2.7 × 101 /s using a hydraulic loading frame and a split Hopkinson bar. Over the range of strain rates, our measurements of dynamic strength increase are in good agreement with the universal theoretical scaling relationship of (Kimberley et al., Acta Mater 61:3509–3521, 2013). Dynamic fragmentation during split tension mode failure has received little attention, and in the present study, we determine the fragment size distribution based on the experimentally fragmented specimens. The fragments fall into two distinct groups based on the nature of failure: coarser primary fragments, and finer secondary fragments. The degree of fragmentation is assessed in terms of characteristic strain rate and is compared with existing theoretical tensile fragmentation models. The average size of the secondary fragments has a strong strain rate dependency over the entire testing range, while the primary fragment size is less sensitive at lower strain rates. Marble and sandstone are found to generate more pulverised secondary debris when compared to basalt and granite. Furthermore, the mean fragment sizes of primary and secondary fragments are well described by a power-law function of strain rate.

The accurate and fast estimation of velocity models is crucial in seismic imaging. Conventional methods, like Tomography and Full-Waveform Inversion (FWI), obtain appropriate velocity models; however, they require intense and specialized human supervision and consume much time and computational resources. In recent years, some works investigated deep learning(DL) algorithms to obtain the velocity model directly from shots or migrated angle panels, obtaining encouraging predictions of synthetic models. This paper proposes a new flow to increase the complexity of velocity models recovered with DL. Inspired by the conventional geophysical velocity model building methods, instead of predicting the entire model in one step, we predict the velocity model iteratively. We implement the iterative nature of the process when, for each iteration, we train the DL algorithm to determine the velocity model with a certain level of precision/resolution for the next iteration; we name this process as Deep-Tomography. Starting from an initial model that roughly approaches the true model, the Deep-Tomography is able to predict an appropriate final model, even in complete unseen data, like the Marmousi model., Comment: 27 pages, 9 figures. First manuscript version submitted to Geophysical Journal International in February 2022

The Coupled Model Intercomparison Project (phase 6) (CMIP6) global circulation models (GCMs) predict equilibrium climate sensitivity (ECS) values ranging between 1.8 and 5.7 $^\circ$C. To narrow this range, we group 38 GCMs into low, medium and high ECS subgroups and test their accuracy and precision in hindcasting the mean global surface warming observed from 1980-1990 to 2011-2021 in the ERA5 T2m, HadCRUT5, GISTEMP v4, and NOAAGlobTemp v5 global surface temperature records. We also compare the GCM hindcasts to the satellite-based UAH MSU v6 lower troposphere global temperature record. We use 143 GCM ensemble averaged simulations under four slightly different forcing conditions, 688 GCM member simulations, and Monte Carlo modeling of the internal variability of the GCMs under three different model accuracy requirements. We found that the medium and high ECS GCMs run too hot up to over 95% and 97% of cases, respectively. The low ECS GCM group agrees best with the warming values obtained from the surface temperature records, ranging between 0.52 and 0.58 $^\circ$C. However, when comparing the observed and GCM hindcasted warming on land and ocean regions, the surface-based temperature records appear to exhibit a significant warming bias. If the satellite based UAH MSU lt record is accurate, actual surface warming from 1980 to 2021 may have been around 0.40 $^\circ$C (or less), i.e. up to about 30% less than what is reported by the surface based temperature records. The latter situation implies that even the low ECS models would have produced excessive warming from 1980 to 2021. These results suggest that the actual ECS may be relatively low, i.e. lower than 3 $^\circ$C or even less than 2 $^\circ$C. Therefore, the projected global climate warming over the next few decades could be moderate and probably not particularly alarming., 26 pages, 13 figures. Climate Dynamics (2022)

SUMMARY Long-term slow-slip events (LSSEs) usually occur on a fault existing at the deep, shallow parts of subducting plates and substantially relate to adjacent megathrust fault motions. The dynamics of the LSSE largely depend on the inhomogeneity of friction that occurs between the fault interfaces. Thus, it is crucial to estimate the spatial-dependent frictional features from the observations of the slip motion and subsequently identify essential parts that contribute to the principal slip motion by quantifying uncertainties involved in the estimates. Although quantifying the uncertainties of the frictional feature fields in high resolution is necessary to solve the task, conventional techniques of quantifying slow earthquake frictional features have not yet achieved such uncertainty quantification (UQ) due to the complexity of LSSE models such as the large dimensionality. We, therefore, propose a method of UQ for spatially inhomogeneous frictional features from slip motion based on a 4-D variational data assimilation technique using a second-order adjoint method. The proposed method enables us to conduct an accurate UQ even when the dimensionality is large. By combining a fault motion model that mimics slow-slip motion on an LSSE fault–megathrust fault complex in southwestern Japan and the data assimilation technique, we successfully quantified the spatial distribution of the uncertainty of the frictional features in high-resolution. The evaluated spatial distribution in high-resolution reveals the correlation between the dynamics of the slow-slip motion and the important components of the frictional features, which is a valuable information for designing observation systems. Findings from this study are expected to advance the theoretical foundation of applied seismic motion prediction techniques using slow-slip frictional features as stress metres for megaquakes, as well as to improve the understanding of the relationship between the slow-slip motion and frictional parameters of a fault.

Reciprocity theorems are established for the elastic sea level fingerprint problem including rotational feedbacks. In their simplest form, these results show that the sea level change at a location x due to melting a unit point mass of ice at x' is equal to the sea level change at x' due to melting a unit point mass of ice at x. This identity holds irrespective of the shoreline geometry or of lateral variations in elastic Earth structure. Using the reciprocity theorems, sensitivity kernels for sea level and related observables with respect to the ice load can be readily derived. It is notable that calculation of the sensitivity kernels is possible using standard fingerprint codes, though for some types of observable a slight generalisation to the fingerprint problem must be considered. These results are of use within coastal hazard assessment and have a range of potential applications within studies of modern-day sea level change., Paper submitted to Geophysical Journal International

Deep-focus earthquakes that occur at 350-660 km are theorized to be caused by strain-induced olivine-spinel phase transformation (PT). We introduce and apply dynamic rotational diamond anvil cell with rough diamond anvils to deform San Carlos olivine. While olivine was never transformed to spinel at any pressure at room temperature, we obtained olivine-ringwoodite PT under severe plastic shear at 15-28 GPa within seconds. This is conceptual proof of the difference between pressure- and plastic strain-induced PTs and that plastic straining can accelerate this PT from million years to timescales relevant for the earthquake. The PT pressure linearly reduces with increasing plastic strain, corresponding increasing dislocation density and decreasing crystallite size. The main rules of the coupled severe plastic flow, PT, and microstructure evolution are found.

We investigate the behavior of subaqueous barchans reaching dune-size obstacles by carrying out experiments where we varied the obstacle shape and size, the flow strength, and the grains' properties. We found that a subaqueous barchan can pass over or bypass a dune-size obstacle, or even be blocked, with some intermediate situations. In the bypass cases, the original barchan can split in two or more bedforms, redistributing sand in space. Finally, we propose a classification map in which the barchan behavior depends basically on two dimensionless parameters. Our results represent a step toward understanding how barchans behave in the presence of large obstacles, such as retaining walls, tubes and bridge pillars., Published under the CC BY 4.0 license. To view open-access paper, go to https://doi.org/10.1029/2023GL104125

The periodical degassing from CO2 over-pressured reservoirs may have serious consequences for the environment making urgent understanding the processes and forecasting the frequency. Prediction though needs methods that depends from temporal and spatial properties of hydro-chemical and physical reservoir characteristics that unfortunately are often lacking. We have analyzed surface emissions of CO2 attributed to over-pressured CO2-rich reservoirs in the Central Italian Apennines a zone characterized by significant periodical CO2 degassing. Here aquifers are hosted in Mesozoic limestone with high pCO2 groundwater and travertine deposits. We analyzed a 10-year temporal series and found that in the Apennines, CO2 flux and aquifer fluid composition are correlated with the lunar tides specific to the geographic zone. In particular, our study reveals that low CO2 flux corresponds with low lunar tidal potential values. We found a similar trend for dissolved calcium and water alkalinity, while pH values display a linear correlation with tidal cycles. The forces associated with tidal potentials are not capable of fracturing rock. However, they can, under certain conditions, drive the flow of fluids in over-pressured reservoirs, triggering sub-surface fluid movements that in turn modify the water-rock reactivity. In the central Apennines, these movements result in increased dolomite dissolution and an eventual return to calcite equilibrium. In this case, dolomite dissolution breaks the rock releasing calcium into ground water, which leads to calcite equilibrium and in turn to the formation of significant quantities of travertine and the concomitant release of CO2 in the atmosphere., 12 pages, 6 figures

Laser interferometry enables to remotely measure microscopical length changes of deployed telecommunication cables originating from earthquakes. Long range and compatibility with data traffic make it unique to the exploration of remote regions, as well as highly-populated areas where optical networks are pervasive, and its large-scale implementation is attractive for both Earth scientists and telecom operators. However, validation and modeling of its response and sensitivity are still at an early stage and suffer from lack of statistically-significant event catalogs and limited availability of co-located seismometers. We implemented laser interferometry on a land-based telecommunication cable and analyzed 1.5 years of continuous acquisition, with successful detections of events in a broad range of magnitudes, including very weak ones. By comparing fiber and seismometer recordings we determined relations between a cable's detection probability and the magnitude and distance of events, and showed that spectral analysis of recorded data allows considerations on the earthquake dynamics. Our results reveal that quantitative analysis is possible for this sensing technique and support the interpretation of data from the growing amount of interferometric deployments. We anticipate the high integration and scalability of laser interferometry into existing telecommunication grids to be useful for the daily seismicity monitoring, in perspective exploitable for civilian protection use.

Ice streams are major contributors to ice sheet mass loss and sea level rise. Effects of their dynamic behaviour are imprinted into seismic properties, such as wave speeds and anisotropy. Here we present results from the first Distributed Acoustic Sensing (DAS) experiment in a deep ice-core borehole in the onset region of the Northeast Greenland Ice Stream. A series of active surface sources produced clear recordings of the P and S wavefield, including internal reflections, along a 1500 m long fibre-optic cable that was lowered into the borehole. The combination of nonlinear traveltime tomography with a firn model constrained by multi-mode surface wave data, allows us to invert for P and S wave speeds with depth-dependent uncertainties on the order of only 10 m$/$s, and vertical resolution of 20--70 m. The wave speed model in conjunction with the regularly spaced DAS data enable a straightforward separation of internal upward reflections followed by a reverse-time migration that provides a detailed reflectivity image of the ice. While the differences between P and S wave speeds hint at anisotropy related to crystal orientation fabric, the reflectivity image seems to carry a pronounced climatic imprint caused by rapid variations in grain size. Currently, resolution is not limited by the DAS channel spacing. Instead, the maximum frequency of body waves below $\sim$200 Hz, low signal-to-noise ratio caused by poor coupling, and systematic errors produced by the ray approximation, appear to be the leading-order issues. Among these, only the latter has a simple existing solution in the form of full-waveform inversion. Improving signal bandwidth and quality, however, will likely require a significantly larger effort in terms of both sensing equipment and logistics., 15 pages, 14 figures

Multiple lines of evidence indicate that the 2023 Mw 7.8 Turkey earthquake started on a splay fault, then branched bilaterally onto the nearby East Anatolian Fault (EAF). This rupture pattern includes one feature deemed implausible, called backward rupture branching: rupture propagating from the splay fault onto the SW EAF segment through a sharp corner (with an acute angle between the two faults). To understand this feature, we perform 2.5-D dynamic rupture simulations considering a large set of possible scenarios. We find that both subshear and supershear ruptures on the splay fault can trigger bilateral ruptures on the EAF, which themselves can be either subshear, supershear, or a mixture of the two. In most cases, rupture on the SW segment of the EAF starts after rupture onset on its NE segment: the SW rupture is triggered by the NE rupture. Only when the EAF has initial stresses very close to failure, its SW segment can be directly triggered by the initial splay-fault rupture, earlier than the activation of the NE segment. These results advance our understanding of the mechanisms of multi-segment rupture and the complexity of rupture processes, paving the way for a more accurate assessment of earthquake hazards.

The low-latitude ionosphere is a dynamic region with a wide range of disturbances in temporal and spatial scales. The Giant Metrewave Radio Telescope (GMRT) situated in the low-latitude region has demonstrated its ability to detect various ionospheric phenomena. It can detect total electron content (TEC) variation with precision of 1 mTECU and also can measure TEC gradient with an accuracy of about $\rm7\times 10^{-4}\,TECU\,km^{-1}$. This paper describes the spectral analysis of previously calculated TEC gradient measurements and validates them by comparing their properties using two bands. The analysis tracked individual waves associated with medium-scale traveling ionospheric disturbances (MSTIDs) and smaller waves down to wavelengths of $\sim$ 10 km. The ionosphere is found to have unanticipated changes during sunrise hours, with waves changed propagation direction as the sun approached the zenith. Equatorial spread\,$F$ disturbances during sunrise hours is observed, along with smaller structures moving in the same direction., 17 pages, 2 figures, 2 Tables, accepted for publication in Geophysical Research Letters

Characterization of topology and dimensionality of spectral feature spaces provides insight into information content. The objective of this study is to characterize topology and spectral dimensionality of spectral mixing spaces representing a diversity of built environments in urban areas worldwide using both spaceborne and airborne imaging spectroscopy. Comparing complementary types of dimensionality reduction to render high dimensional spectral mixing spaces allows for characterization of both spectral dimensionality and mixing space topology. Using a diverse collection of 30 decameter-resolution urban core subscenes imaged by the EMIT spaceborne imaging spectrometer and 5 sub-decameter-resolution urban gradient flight lines imaged by the AVIRIS-NG airborne imaging spectrometer, we conduct such characterizations. Global scale topology of low order principal component-derived mixing spaces resembles the Substrate, Vegetation, Dark (SVD) triangular topology of globally diverse composite mixing spaces found in numerous earlier studies - but these spaces are also characterized by multiple (2-3) distinct substrate endmembers and a wide variety of less common spectra corresponding to synthetic anthropogenic materials. Local scale topology from 2D and 3D UMAP manifold embeddings reveals the presence of multiple spectrally distinct impervious substrate mixing continua corresponding to geographically distinct built environments., 27 pages, 13 figures

The incompleteness of the seismic data caused by missing traces along the spatial extension is a common issue in seismic acquisition due to the existence of obstacles and economic constraints, which severely impairs the imaging quality of subsurface geological structures. Recently, deep learningbased seismic interpolation methods have attained promising progress, while achieving stable training of generative adversarial networks is not easy, and performance degradation is usually notable if the missing patterns in the testing and training do not match. In this paper, we propose a novel seismic denoising diffusion implicit model with resampling. The model training is established on the denoising diffusion probabilistic model, where U-Net is equipped with the multi-head self-attention to match the noise in each step. The cosine noise schedule, serving as the global noise configuration, promotes the high utilization of known trace information by accelerating the passage of the excessive noise stages. The model inference utilizes the denoising diffusion implicit model, conditioning on the known traces, to enable high-quality interpolation with fewer diffusion steps. To enhance the coherency between the known traces and the missing traces within each reverse step, the inference process integrates a resampling strategy to achieve an information recap on the former interpolated traces. Extensive experiments conducted on synthetic and field seismic data validate the superiority of our model and its robustness to various missing patterns. In addition, uncertainty quantification and ablation studies are also investigated., 14 pages, 13 figures

Geochemical data are compositional in nature and are subject to the problems typically associated with data that are restricted to the real non-negative number space with constant-sum constraint, that is, the simplex. Geochemistry can be considered a proxy for mineralogy, comprised of atomically ordered structures that define the placement and abundance of elements in the mineral lattice structure. Based on the innovative contributions of John Aitchison, who introduced the logratio transformation into compositional data analysis, this contribution provides a systematic workflow for assessing geochemical data in an efficient way, such that significant geochemical (mineralogical) processes can be recognized and validated. The results of a workflow, called GeoCoDA and presented here in the form of a tutorial, enables the recognition of processes from which models can be constructed based on the associations of elements that reflect mineralogy. Both the original compositional values and their transformation to logratios are considered. These models can reflect rock forming processes, metamorphic, alteration and ore mineralization. Moreover, machine learning methods, both unsupervised and supervised, applied to an optimized set of subcompositions of the data, provide a systematic, accurate, efficient and defensible approach to geochemical data analysis. The workflow is illustrated on lithogeochemical data from exploration of the Star kimberlite, consisting of a series of eruptions with five recognized phases., 38 pages, 18 figures (including Supplementary Material)

Context: Tidal and rotational deformation of fluid giant extra-solar planets may impact their transit light curves, making the $k_2$ Love number observable in the upcoming years. Studying the sensitivity of $k_2$ to mass concentration at depth is thus expected to provide new constraints on the internal structure of gaseous extra-solar planets. Aims: We investigate the link between the mean polar moment of inertia $N$ of a fluid, stably layered extra-solar planet and its $k_2$ Love number, aiming at obtaining analytical relationships valid, at least, for some particular ranges of the model parameters. We also seek a general, approximate relationship useful to constrain $N$ once observations of $k_2$ will become available. Methods: For two-layer fluid extra-solar planets, we explore the relationship between $N$ and $k_2$ by analytical methods, for particular values of the model parameters. We also explore approximate relationships valid over all the possible range of two-layer models. More complex planetary structures are investigated by the semi-analytical propagator technique. Results: A unique relationship between $N$ and $k_2$ cannot be established. However, our numerical experiments show that a `rule of thumb' can be inferred, valid for complex, randomly layered stable planetary structures. The rule robustly defines the upper limit to the values of $N$ for a given $k_2$, and agrees with analytical results for a polytrope of index one and with a realistic non-rotating model of the tidal equilibrium of Jupiter., Accepted for publication on Astronomy & Astrophysics

The melting curve of pure silica (SiO$_2$) was determined using {\it ab initio} density functional theory together with the solid-liquid coexistence approach, thermodynamic integration and the Z method. The melting curves show a smooth slow increase in a large region from 50 GPa (dT/dP $\approx$ 10 K/GPa) to about 500 GPa (dT/dP $\approx$ 6 K/GPa) without any abrupt changes at around 120 GPa and 300 GPa as seen in some recent experimental and computational studies. The topography of the melting curve above 50 GPa is consistent with a gradual change in the distribution of the Si coordination numbers in the liquid state and the absence of large changes in the density following solid-solid phase transitions. The pair distribution functions show that the structural correlation in the liquid is mainly short-ranged and that the Si-O bond is stiff. The densification of the melt structure with pressure above 50 GPa is therefore due to an increase in 7- and 8-fold coordinated silicon.

Terrestrial exoplanets are of great interest for being simultaneously similar to and different from Earth. Their compositions are likely comparable to those of solar-terrestrial objects, but their internal pressures and temperatures can vary significantly with their masses/sizes. The most abundant non-volatile elements are O, Mg, Si, Fe, Al, and Ca, and there has been much recent progress in understanding the nature of magnesium silicates up to and beyond ~3 TPa. However, a critical element, Fe, has yet to be systematically included in materials discovery studies of potential terrestrial planet-forming phases at ultra-high pressures. Here, using the adaptive genetic algorithm (AGA) crystal structure prediction method, we predict several unreported stable crystalline phases in the binary Fe-Mg and ternary Fe-Mg-O systems up to pressures of 3 TPa. The analysis of the local packing motifs of the low-enthalpy Fe-Mg-O phases reveals that the Fe-Mg-O system favors a BCC motif under ultra-high pressures regardless of chemical composition. Besides, oxygen enrichment is conducive to lowering the enthalpies of the Fe-Mg-O phases. Our results extend the current knowledge of structural information of the Fe-Mg-O system to exoplanet pressures.

One of the major unresolved problems in cosmochemistry is the origin of chondrules, once molten, spherical silicate droplets with diameters of 0.2 to 2 mm. Chondrules are an essential component of primitive meteorites and perhaps of all early solar system materials including the terrestrial planets. Numerous hypotheses have been proposed for their origin. Many carbonaceous chondrites are composed of about equal amounts of chondrules and fine-grained matrix. Recent data confirm that matrix in carbonaceous chondrites has high Si/Mg and Fe/Mg ratios when compared to bulk carbonaceous chondrites with solar abundance ratios. Chondrules have the opposite signature, low Si/Mg and Fe/Mg ratios. In some carbonaceous chondrites chondrules have low Al/Ti ratios, matrix has the opposite signature and the bulk is chondritic. It is shown in detail that these complementary relationships cannot have evolved on the parent asteroid(s) of carbonaceous chondrites. They reflect preaccretionary processes. Both chondrules and matrix must have formed from a single, solar-like reservoir. Consequences of complementarity for chondrule formation models are discussed. An independent origin and/or random mixing of chondrules and matrix can be excluded. Hence, complementarity is a strong constraint for all astrophysical-cosmochemical models of chondrule formation. Although chondrules and matrix formed from a single reservoir, the chondrule-matrix system was open to the addition of oxygen and other gaseous components., 27 pages, 8 figures, with supplemental tables

Nucleosynthetic isotope anomalies in meteorites allow distinguishing between the non-carbonaceous (NC) and carbonaceous (CC) meteorite reservoirs and show that correlated isotope anomalies exist in both reservoirs. It is debated, however, whether these anomalies reflect thermal processing of presolar dust in the disk or are primordial heterogeneities inherited from the Solar System's parental molecular cloud. Here, using new high-precision 84Sr isotope data, we show that NC meteorites, Mars, and the Earth and Moon are characterized by the same 84Sr isotopic composition. This 84Sr homogeneity of the inner Solar System contrasts with the well-resolved and correlated isotope anomalies among NC meteorites observed for other elements, and most likely reflects correlated s- and (r-, p-)-process heterogeneities leading to 84Sr excess and deficits of similar magnitude which cancel each other. For the same reason there is no clearly resolved 84Sr difference between NC and CC meteorites, because in some carbonaceous chondrites the characteristic 84Sr excess of the CC reservoir is counterbalanced by an 84Sr deficit resulting from s-process variations. Nevertheless, most carbonaceous chondrites exhibit 84Sr excesses, which reflect admixture of refractory inclusions and more pronounced s-process heterogeneities in these samples. Together, the correlated variations of s-, (r-, p-)-process nuclides revealed by the 84Sr data of this study refute an origin of these isotope anomalies solely by processing of presolar dust grains, but points to primordial mixing of isotopically distinct dust reservoirs as the dominant process producing the isotopic heterogeneity of the Solar System., 18 pages 4 Figures

The Omori-Utsu law shows the temporal power-law-like decrease of the frequency of earthquake aftershocks and, interestingly, is found in a variety of complex systems/phenomena exhibiting catastrophes. Now, it may be interpreted as a characteristic response of such systems to large events. Here, hierarchical dynamics with the fast and slow degrees of freedom is studied on the basis of the Fokker-Planck theory for the load-state distribution to formulate the law as a relaxation process, in which diffusion coefficient in the space of the load state is treated as a fluctuating slow variable. The evolution equation reduced from the full Fokker-Planck equation and its Green's function are analyzed for the subdynamics governing the load state as the fast degree of freedom. It is shown that the subsystem has the temporal translational invariance in the logarithmic time, not in the conventional time, and consequently the aging phenomenon appears., 25 pages, no figures

Clay minerals are important components of sandstone rocks, due to their significant role on petrophysical properties like porosity and permeability. These minerals have a particular impact on Nuclear Magnetic Resonance measurements since the iron contained on clays generates internal gradients which directly affect the transverse relaxation. Here, we apply a methodology recently developed to a set of 20 sandstones, with varying clay content and mineralogy, in order to estimate the total clay content by using the effect of internal gradients on transverse relaxation. Based on these measurements, we propose a geochemical rock typing from quantities determined by our measurements, namely the total clay content and porosity.

The existence of magnitude dependence in earthquake triggering has been reported. Such a correlation is linked to the issue of seismic predictability and remains under intense debate whether it is physical or is caused by incomplete data due to short-term aftershocks missing. Working firstly with a synthetic catalogue generated by a numerical model that capture most statistical features of earthquakes and then with an high-resolution earthquake catalogue for the Amatrice-Norcia (2016) sequence in Italy, where for the latter case we employ the stochastic declustering method to reconstruct the family tree among seismic events and limit our analysis to events above the magnitude of completeness, we found that the hypothesis of magnitude correlation can be rejected.

Low-iron, manganese-enriched (LIME) olivine grains are found in cometary samples returned by the Stardust mission to comet 81P/Wild 2. Similar grains are found in primitive meteoritic clasts and unequilibrated meteorite matrix. LIME olivine is thermodynamically stable in a vapor of solar composition at high temperature at total pressures of a millibar to a microbar, but enrichment of solar composition vapor in a dust of chondritic composition causes the FeO/MnO ratio of olivine to increase. The compositions of LIME olivines in primitive materials indicate oxygen fugacities close to that of a very reducing vapor of solar composition. The compositional zoning of LIME olivines in amoeboid olivine aggregates is consistent with equilibration with nebular vapor in the stability field of olivine, without reequilibration at lower temperatures. A similar history is likely for LIME olivines found in comet samples and in interplanetary dust particles. LIME olivine is not likely to persist in nebular conditions in which silicate liquids are stable., 15 pages, 5 figures