Zeeman-Tomography of the Solar Photosphere -- 3-Dimensional Surface Structures Retrieved from Hinode Observations

AIMS :The thermodynamic and magnetic field structure of the solar photosphere is analyzed by means of a novel 3-dimensional spectropolarimetric inversion and reconstruction technique. METHODS : On the basis of high-resolution, mixed-polarity magnetoconvection simulations, we used an artificial neural network (ANN) model to approximate the nonlinear inverse mapping between synthesized Stokes spectra and the underlying stratification of atmospheric parameters like temperature, line-of-sight (LOS) velocity and LOS magnetic field. This approach not only allows us to incorporate more reliable physics into the inversion process, it also enables the inversion on an absolute geometrical height scale, which allows the subsequent combination of individual line-of-sight stratifications to obtain a complete 3-dimensional reconstruction (tomography) of the observed area. RESULTS : The magnetoconvection simulation data, as well as the ANN inversion, have been properly processed to be applicable to spectropolarimetric observations from the Hinode satellite. For the first time, we show 3-dimensional tomographic reconstructions (temperature, LOS velocity, and LOS magnetic field) of a quiet sun region observed by Hinode. The reconstructed area covers a field of approximately 12000 by 12000 km and a height range of 510 km in the photosphere. An enormous variety of small and large scale structures can be identified in the 3-D reconstructions. The low-flux region (B_{mag} = 20G) we analyzed exhibits a number of "tube-like" magnetic structures with field strengths of several hundred Gauss. Most of these structures rapidly loose their strength with height and only a few larger structures can retain a higher field strength to the upper layers of the photosphere.Comment: accepted for A&A Letter

A fast method for Stokes profile synthesis -- Radiative transfer modeling for ZDI and Stokes profile inversion

The major challenges for a fully polarized radiative transfer driven approach to Zeeman-Doppler imaging are still the enormous computational requirements. In every cycle of the iterative interplay between the forward process (spectral synthesis) and the inverse process (derivative based optimization) the Stokes profile synthesis requires several thousand evaluations of the polarized radiative transfer equation for a given stellar surface model. To cope with these computational demands and to allow for the incorporation of a full Stokes profile synthesis into Doppler- and Zeeman-Doppler imaging applications as well as into large scale solar Stokes profile inversions, we present a novel fast and accurate synthesis method for calculating local Stokes profiles. Our approach is based on artificial neural network models, which we use to approximate the complex non-linear mapping between the most important atmospheric parameters and the corresponding Stokes profiles. A number of specialized artificial neural networks, are used to model the functional relation between the model atmosphere, magnetic field strength, field inclination, and field azimuth, on one hand and the individual components (I,Q,U,V) of the Stokes profiles, on the other hand. We performed an extensive statistical evaluation and show that our new approach yields accurate local as well as disk-integrated Stokes profiles over a wide range of atmospheric conditions. The mean rms errors for the Stokes I and V profiles are well below 0.2% compared to the exact numerical solution. Errors for Stokes Q and U are in the range of 1%. Our approach does not only offer an accurate approximation to the LTE polarized radiative transfer it, moreover, accelerates the synthesis by a factor of more than 1000.Comment: A&A, in pres

Adjusting Bioactive Functions of Dairy Products via Processing

Milk is known for its high nutrient content that helps to maintain important body functions. In this regard, bioactive peptides that are encrypted in milk proteins and get released during processing and/or digestion might play a role. These peptides are able to inhibit enzymes, influence cell growth, or target specific receptors. The peptide profile that arises after protein digestion in the jejunum before the absorption into the blood takes place includes these bioactive peptides. The composition of the peptide profile is influenced strongly via processing and a modification in processing might target specific functionalities. Thermal, chemical, biochemical, and physical treatments affect protein digestion mainly by changing the protein structure for example via denaturation or protease actions. Parameters influencing this are external ones, like the matrix of the product, and internal ones, like specific enzyme deficiencies. However, considering all the important aspects that are involved, there might be the possibility in the future to adjust a bioactive function via processing

Understanding Marine Microbes, the Driving Engines of the Ocean

When you hear the word microbes, what comes to your mind? Something much too small to see and that makes you fall ill? Just because some microbes cause diseases that does not mean they are all evil. For example, in the marine (ocean) environment, the vast majority of microbes are good ones. They are the “driving engines” of the ocean and are essential for the health of our whole planet. Unfortunately, most of the marine microbes and their interactions with the marine environment are poorly understood. So, it is important to get an idea of which microbes are helping us and how they are doing this. These data will provide scientists with the knowledge to fight against big global challenges, such as climate change and environmental pollution. Unfortunately, it is very hard to study marine microbes due to their microscopic size, huge diversity, and their big home – the ocean. Therefore, we would like to engage “citizen scientists” in this project to help us to sample marine microbes so that we can identify them

Constraints on fluid flow processes in the Hellenic Accretionary Complex (eastern Mediterranean Sea) from numerical modeling

The dynamics of accretionary convergent margins are severely influenced by intense deformation and fluid expulsion. To quantify the fluid pressure and fluid flow velocities in the Hellenic subduction system, we set up 2-D hydrogeological numerical models following two seismic reflection lines across the Mediterranean Ridge. These profiles bracket the along-strike variation in wedge geometry: moderate compression and a >4 km thick underthrust sequence in the west versus enhanced compression and <1 km of downgoing sediment in the center. Input parameters were obtained from preexisting geophysical data, drill cores, and new geotechnical laboratory experiments. A permeability-porosity relationship was determined by a sensitivity analysis, indicating that porosity and intrinsic permeability are small. This hampers the expulsion of fluids and leads to the build up of fluid overpressure in the deeper portion of the wedge and in the underthrust sediment. The loci of maximum fluid pressure are mainly controlled by the compactional fluid source, which generally decreases toward the backstop. However, pore pressure is still high at the decollement level at distances <100 km from the deformation front, either by the incorporation of low permeability evaporites or additional compaction of the wedge sediments in the two profiles. In the west, however, formation of a wide accretionary complex is facilitated by high pore pressure zones. When compared to other large accretionary complexes such as Nankai or Barbados, our results not only show broad similarities but also that near-lithostatic pore pressures may be easier to maintain in the Hellenic Arc because of accentuated collision, some underthrust evaporates, and a thicker underthrust sequence

Semantically Guided Depth Upsampling

We present a novel method for accurate and efficient up- sampling of sparse depth data, guided by high-resolution imagery. Our approach goes beyond the use of intensity cues only and additionally exploits object boundary cues through structured edge detection and semantic scene labeling for guidance. Both cues are combined within a geodesic distance measure that allows for boundary-preserving depth in- terpolation while utilizing local context. We model the observed scene structure by locally planar elements and formulate the upsampling task as a global energy minimization problem. Our method determines glob- ally consistent solutions and preserves fine details and sharp depth bound- aries. In our experiments on several public datasets at different levels of application, we demonstrate superior performance of our approach over the state-of-the-art, even for very sparse measurements.Comment: German Conference on Pattern Recognition 2016 (Oral