Influence of antisymmetric exchange interaction on quantum tunneling of magnetization in a dimeric molecular magnet Mn6

We present magnetization measurements on the single molecule magnet Mn6, revealing various tunnel transitions inconsistent with a giant-spin description. We propose a dimeric model of the molecule with two coupled spins S=6, which involves crystal-field anisotropy, symmetric Heisenberg exchange interaction, and antisymmetric Dzyaloshinskii-Moriya exchange interaction. We show that this simplified model of the molecule explains the experimentally observed tunnel transitions and that the antisymmetric exchange interaction between the spins gives rise to tunneling processes between spin states belonging to different spin multiplets.Comment: 5 pages, 4 figure

Solar-like oscillations in red giants observed with Kepler: comparison of global oscillation parameters from different methods

The large number of stars for which uninterrupted high-precision photometric timeseries data are being collected with \textit{Kepler} and CoRoT initiated the development of automated methods to analyse the stochastically excited oscillations in main-sequence, subgiant and red-giant stars. Aims: We investigate the differences in results for global oscillation parameters of G and K red-giant stars due to different methods and definitions. We also investigate uncertainties originating from the stochastic nature of the oscillations. Methods: For this investigation we use Kepler data obtained during the first four months of operation. These data have been analysed by different groups using already published methods and the results are compared. We also performed simulations to investigate the uncertainty on the resulting parameters due to different realizations of the stochastic signal. Results: We obtain results for the frequency of maximum oscillation power (nu_max) and the mean large separation () from different methods for over one thousand red-giant stars. The results for these parameters agree within a few percent and seem therefore robust to the different analysis methods and definitions used here. The uncertainties for nu_max and due to differences in realization noise are not negligible and should be taken into account when using these results for stellar modelling.Comment: 11 pages, 9 Figures and 7 tables, accepted for publication in Astronomy and Astrophysic

Modelling a high-mass red giant observed by CoRoT

The G6 giant HR\,2582 (HD\,50890) was observed by CoRoT for approximately 55 days. Mode frequencies are extracted from the observed Fourier spectrum of the light curve. Numerical stellar models are then computed to determine the characteristics of the star (mass, age, etc...) from the comparison with observational constraints. We provide evidence for the presence of solar-like oscillations at low frequency, between 10 and 20\,$\mu$Hz, with a regular spacing of $(1.7\pm0.1)\mu$Hz between consecutive radial orders. Only radial modes are clearly visible. From the models compatible with the observational constraints used here, We find that HR\,2582 (HD\,50890) is a massive star with a mass in the range (3--\,5\,$M_{\odot}$), clearly above the red clump. It oscillates with rather low radial order ($n$ = 5\,--\,12) modes. Its evolutionary stage cannot be determined with precision: the star could be on the ascending red giant branch (hydrogen shell burning) with an age of approximately 155 Myr or in a later phase (helium burning). In order to obtain a reasonable helium amount, the metallicity of the star must be quite subsolar. Our best models are obtained with a mixing length significantly smaller than that obtained for the Sun with the same physical description (except overshoot). The amount of core overshoot during the main-sequence phase is found to be mild, of the order of 0.1\,$H_{\rm p}$.Comment: Accepted in A&

Galactic Archaeology with CoRoT and APOGEE: Creating mock observations from a chemodynamical model

In a companion paper, we have presented the combined asteroseismic-spectroscopic dataset obtained from CoRoT lightcurves and APOGEE infra-red spectra for 678 solar-like oscillating red giants in two fields of the Galactic disc (CoRoGEE). We have measured chemical abundance patterns, distances, and ages of these field stars which are spread over a large radial range of the Milky Way's disc. Here we show how to simulate this dataset using a chemodynamical Galaxy model. We also demonstrate how the observation procedure influences the accuracy of our estimated ages.Comment: 5 pages, 6 figures. To appear in Astronomische Nachrichten, special issue "Reconstruction the Milky Way's History: Spectroscopic surveys, Asteroseismology and Chemo-dynamical models", Guest Editors C. Chiappini, J. Montalb\'an, and M. Steffe

E´ chelle diagrams and period spacings of g modes in: Doradus stars from four years of Kepler observations

We use photometry from the Kepler Mission to study oscillations in Doradus stars. Some stars show remarkably clear sequences of g modes and we use period ´echelle diagrams to measure period spacings and identifyrotationally split multiplets with ` = 1 and ` = 2.We find small deviations from regular period spacings that arise from the gradient in the chemical composition just outside the convective core. We also find stars for which the period spacing shows a strong linear trend as a function of period, consistent with relatively rapid rotation. Overall, th

Preparation of Kepler lightcurves for asteroseismic analyses

The Kepler mission is providing photometric data of exquisite quality for the asteroseismic study of different classes of pulsating stars. These analyses place particular demands on the pre-processing of the data, over a range of timescales from minutes to months. Here, we describe processing procedures developed by the Kepler Asteroseismic Science Consortium (KASC) to prepare light curves that are optimized for the asteroseismic study of solar-like oscillating stars in which outliers, jumps and drifts are corrected.Comment: Accepted for publication in MNRAS. 5 pages, 2 figure

Atmospheric parameters and chemical properties of red giants in the CoRoT asteroseismology fields

A precise characterisation of the red giants in the seismology fields of the CoRoT satellite is a prerequisite for further in-depth seismic modelling. High-resolution FEROS and HARPS spectra were obtained as part of the ground-based follow-up campaigns for 19 targets holding great asteroseismic potential. These data are used to accurately estimate their fundamental parameters and the abundances of 16 chemical species in a self-consistent manner. Some powerful probes of mixing are investigated (the Li and CNO abundances, as well as the carbon isotopic ratio in a few cases). The information provided by the spectroscopic and seismic data is combined to provide more accurate physical parameters and abundances. The stars in our sample follow the general abundance trends as a function of the metallicity observed in stars of the Galactic disk. After an allowance is made for the chemical evolution of the interstellar medium, the observational signature of internal mixing phenomena is revealed through the detection at the stellar surface of the products of the CN cycle. A contamination by NeNa-cycled material in the most massive stars is also discussed. With the asteroseismic constraints, these data will pave the way for a detailed theoretical investigation of the physical processes responsible for the transport of chemical elements in evolved, low- and intermediate-mass stars.Comment: Accepted for publication in A&A, 25 pages, 13 colour figures (revised version after language editing

Reconstruction of three-dimensional porous media using generative adversarial neural networks

To evaluate the variability of multi-phase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a novel method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image datasets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that GANs can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.Comment: 21 pages, 20 figure