Melt evolution in subarc mantle: evidence from heating experiments on spinel-hosted melt inclusions in peridotite xenoliths from the andesitic Avacha volcano (Kamchatka,Russia)

Glass-bearing inclusions hosted by Cr-spinel in harzburgite xenoliths from Avacha are grouped based on homogenization temperatures and daughter minerals into high-T (1,200°C; opx + cpx), intermediate (900–1,100°C; cpx ± amph), and low-T (900°C; amph) and are commonly accompanied by larger “melt pockets”. Unlike previous work on unheated inclusions and interstitial glass in xenoliths from Kamchatka, the homogenized glass compositions in this study are not affected by low-pressure melt fractionation during transport and cooling or by interaction with host magma. Primary melt compositions constrained for each inclusion type differ in major and trace element abundances and were formed by different events, but all are silica saturated, Ca-rich, and K-poor, with enrichments in LREE, Sr, Rb, and Ba and negative Nb anomalies. These melts are inferred to have been formed with participation of fluids produced by dehydration of slab materials. The high-T inclusions trapped liquids produced by ancient high-degree, fluid-induced melting in the mantle wedge. The low-T inclusions are related to percolation of low-T melts or hydrous fluids in arc mantle lithosphere. Melt pockets arise from localized heating and fluid-assisted melting induced by rising magmas shortly before the entrapment of the xenoliths. The “high-T” melt inclusions in Avacha xenoliths are unique in preserving evidence of ancient, high-T melting events in arc mantle, whereas the published data appear to characterize pre-eruption enrichment events.     

Magnetic Interaction Between Stars And Accretion Disks

In this review I consider modern theoretical models of coupled star–disk magnetospheres. I discuss a number of models, both stationary and time-dependent, and examine what physical conditions govern the selection of a preferred model.     

Pillars of Heaven

Sometimes the most beautiful things are the hardest to understand. Pillars like those of the Eagle Nebula form at the boundary between some of the hottest (10000~K) and coldest (10~K) gas in the Galaxy. Many physical processes come into play in the birth and growth of such gaseous pillars: hydrodynamic instability, photoionization, ablation, recombination, molecular heating and cooling, and probably magnetic fields. High-quality astronomical observations, quantitative numerical simulations, and scaled laser experiments provide a powerful combination for understanding their formation and evolution. We put our most recent hydrodynamic model to the test, by creating simulated observations from it and comparing them directly to the actual radioastronomical observations. Successfully reproducing major characteristics of the observations in this manner is an important step in designing appropriate laser experiments.     

Accurate estimators of power spectra in N-body simulations

A method to rapidly estimate the Fourier power spectrum of a point distribution is presented. This method relies on a Taylor expansion of the trigonometric functions. It yields the Fourier modes from a number of fast Fourier transforms (FFTs), which is controlled by the order N of the expansion and by the dimension D of the system. In three dimensions, for the practical value   N = 3  , the number of FFTs required is 20.
We apply the method to the measurement of the power spectrum of a periodic point distribution that is a local Poisson realization of an underlying stationary field. We derive an explicit analytic expression for the spectrum, which allows us to quantify – and correct for – the biases induced by discreteness and by the truncation of the Taylor expansion, and to bound the unknown effects of aliasing of the power spectrum. We show that these aliasing effects decrease rapidly with the order N . For   N = 3  , they are expected to be, respectively, smaller than  ∼10⁻⁴  and 0.02 at half the Nyquist frequency and at the Nyquist frequency of the grid used to perform the FFTs. The only remaining significant source of errors is reduced to the unavoidable cosmic/sample variance due to the finite size of the sample.
The analytical calculations are successfully checked against a cosmological N -body experiment. We also consider the initial conditions of this simulation, which correspond to a perturbed grid. This allows us to test a case where the local Poisson assumption is incorrect. Even in that extreme situation, the third-order Fourier–Taylor estimator behaves well, with aliasing effects restrained to at most the per cent level at half the Nyquist frequency.
We also show how to reach arbitrarily large dynamic range in Fourier space (i.e. high wavenumber), while keeping statistical errors in control, by appropriately 'folding' the particle distribution.     

Evolution model for substellar objects

A new model for the evolution of substellar objects is proposed, which enables computation of their internal structure and evolution in an adiabatic approximation without allowance for axial rotation, magnetic fields, and nuclear reactions. The basic set of differential equations in the model contains a new equation for the gradient of the electron degeneracy parameter and adiabatic coefficients of the new type. The results of numerical simulations of evolutionary sequences of hydrogen (X = 1), helium (Y = 1), and hydrogen-helium (X = 0.75, Y = 0.25) substellar objects with masses M < 0.08 M _⊙ during the evolutionary stage 10⁶ yr < t < 10¹⁰ yr are reported. Luminosity-effective temperature, mass-radius, radius-time, central temperature-central density, and central temperature-age relations are analyzed for the indicated chemical composition.     

Origin of Fe-rich lherzolites and wehrlites from Tok,SE Siberia by reactive melt percolation in refractory mantle peridotites

Lherzolite–wehrlite (LW) series xenoliths from the quaternary Tok volcanic field in the southeastern Siberian craton are distinguished from the more common lherzolite–harzburgite (LH) series by (a) low Mg numbers (0.84–0.89) at high modal olivine (66–84%) and (b) widespread replacement of orthopyroxene (0–12%) and spinel by clinopyroxene (7–22%). The LW series peridotites are typically enriched in Ca, Fe, Mn and Ti, and depleted in Si, Ni and Cr relative to refractory LH series rocks (Mg number ≥0.89), which are metasomatised partial melting residues. Numerical modelling of Fe–Mg solid/liquid exchange during melt percolation demonstrates that LW series rocks can form by reaction of host refractory peridotites with evolved (Mg numbers 0.6–0.7), silica-undersaturated silicate melts at high melt/rock ratios, which replace orthopyroxene with clinopyroxene and decrease Mg numbers. This process is most likely related to underplating and fractionation of basaltic magma in the shallow mantle, which also produced olivine–clinopyroxene cumulates found among the Tok xenoliths.     

Wavelet analysis residual kriging vs. neural network residual kriging

 This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method – wavelet analysis residual kriging (WARK) – is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.     

Application of a Bayesian Approach for Estimation of Seismic Hazard Parameters in Some Regions of the Circum-Pacific Belt

—?The maximum possible (regional) magnitude M_max and other seismic hazard parameters like β which is the slope of Gutenberg-Richter law, and λ which is the intensity (rate) of seismic activity are estimated in eight seismic regions of the west side of the circum-Pacific belt. The Bayesian approach, as described by (Pisarenko et?al., 1996; Pisarenko and Lyubushin, 1997, 1999) is a straightforward technique of estimating the seismic hazard. The main assumptions for the method applied are a Poissonian character of seismic events flow, a frequency-magnitude law of Gutenberg-Richter's type with cutoff maximum value for the estimated parameter and a seismic catalog, which have a rather sizeable number of events. We also estimated the quantiles of the probabilistic distribution of the “apparent” M_max for future given time-length intervals.     

Application of the Theory of Extreme Events to Problems of Approximating Probability Distributions of Water Flow Peaks

Statistically treated data of long-term observational series (>30 years) for 66 rivers are used to study the character of distribution of water flow maximums during rain-induced floods in Maritime Territory, Russia. Two probability models are discussed: generalized Pareto distribution (for the domain of very large values) and generalized distribution of extremums (for the rest of the range). The issue of optimal conjunction point of these distributions is discussed. The problem of increasing the accuracy of distribution parameter estimates through data grouping is considered.