Clasts in the CM2 carbonaceous chondrite Lonewolf Nunataks 94101: evidence for aqueous alteration prior to complex mixing

Clasts in the CM2 carbonaceous chondrite Lonewolf Nunataks (LON) 94101 have been characterized using scanning and transmission electron microscopy and electron microprobe analysis to determine their degrees of aqueous alteration, and the timing of alteration relative to incorporation of clasts into the host. The provenance of the clasts, and the mechanism by which they were incorporated and mixed with their host material are also considered. Results show that at least five distinct types of clasts occur in LON 94101, of which four have been aqueously altered to various degrees and one is largely anhydrous. The fact that they have had different alteration histories implies that the main part of aqueous activity occurred prior to the mixing and assimilation of the clasts with their host. Further, the presence of such a variety of clasts suggests complex mixing in a dynamic environment involving material from various sources. Two of the clasts, one containing approximately 46 vol% carbonate and the other featuring crystals of pyrrhotite up to approximately 1 mm in size, are examples of unusual lithologies and indicate concentration of chemical elements in discrete areas of the parent body(ies), possibly by flow of aqueous solutions

Spatially Dependent Parameter Estimation and Nonlinear Data Assimilation by Autosynchronization of a System of Partial Differential Equations

Given multiple images that describe chaotic reaction-diffusion dynamics, parameters of a PDE model are estimated using autosynchronization, where parameters are controlled by synchronization of the model to the observed data. A two-component system of predator-prey reaction-diffusion PDEs is used with spatially dependent parameters to benchmark the methods described. Applications to modelling the ecological habitat of marine plankton blooms by nonlinear data assimilation through remote sensing is discussed

A New Timescale for Period Change in the Pulsating DA White Dwarf WD 0111+0018

We report the most rapid rate of period change measured to date for a pulsating DA (hydrogen atmosphere) white dwarf (WD), observed in the 292.9 s mode of WD 0111+0018. The observed period change, faster than 10^{-12} s/s, exceeds by more than two orders of magnitude the expected rate from cooling alone for this class of slow and simply evolving pulsating WDs. This result indicates the presence of an additional timescale for period evolution in these pulsating objects. We also measure the rates of period change of nonlinear combination frequencies and show that they share the evolutionary characteristics of their parent modes, confirming that these combination frequencies are not independent modes but rather artifacts of some nonlinear distortion in the outer layers of the star.Comment: 10 pages, 6 figures, accepted for publication in The Astrophysical Journa

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Neural Networks for Impact Parameter Determination

An accurate impact parameter determination in a heavy ion collision is crucial for almost all further analysis. The capabilities of an artificial neural network are investigated to that respect. A novel input generation for the network is proposed, namely the transverse and longitudinal momentum distribution of all outgoing (or actually detectable) particles. The neural network approach yields an improvement in performance of a factor of two as compared to classical techniques. To achieve this improvement simple network architectures and a 5 by 5 input grid in (p_t,p_z) space are sufficient.Comment: Phys. Rev. C in print. Postscript-file also available at http://www.th.physik.uni-frankfurt.de/~bass/pub.htm