A Multi-Code Analysis Toolkit for Astrophysical Simulation Data

The analysis of complex multiphysics astrophysical simulations presents a unique and rapidly growing set of challenges: reproducibility, parallelization, and vast increases in data size and complexity chief among them. In order to meet these challenges, and in order to open up new avenues for collaboration between users of multiple simulation platforms, we present yt (available at http://yt.enzotools.org/), an open source, community-developed astrophysical analysis and visualization toolkit. Analysis and visualization with yt are oriented around physically relevant quantities rather than quantities native to astrophysical simulation codes. While originally designed for handling Enzo's structure adaptive mesh refinement (AMR) data, yt has been extended to work with several different simulation methods and simulation codes including Orion, RAMSES, and FLASH. We report on its methods for reading, handling, and visualizing data, including projections, multivariate volume rendering, multi-dimensional histograms, halo finding, light cone generation and topologically-connected isocontour identification. Furthermore, we discuss the underlying algorithms yt uses for processing and visualizing data, and its mechanisms for parallelization of analysis tasks.Comment: 18 pages, 6 figures, emulateapj format. Resubmitted to Astrophysical Journal Supplement Series with revisions from referee. yt can be found at http://yt.enzotools.org

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes

Concentrated suspensions of Brownian beads in water: dynamic heterogeneities trough a simple experimental technique

Concentrated suspensions of Brownian hard-spheres in water are an epitome for understanding the glassy dynamics of both soft materials and supercooled molecular liquids. From an experimental point of view, such systems are especially suited to perform particle tracking easily, and, therefore, are a benchmark for novel optical techniques, applicable when primary particles cannot be resolved. Differential Variance Analysis (DVA) is one such novel technique that simplifies significantly the characterization of structural relaxation processes of soft glassy materials, since it is directly applicable to digital image sequences of the sample. DVA succeeds in monitoring not only the average dynamics, but also its spatio-temporal fluctuations, known as dynamic heterogeneities. In this work, we study the dynamics of dense suspensions of Brownian beads in water, imaged through digital video-microscopy, by using both DVA and single-particle tracking. We focus on two commonly used signatures of dynamic heterogeneities: the dynamic susceptibility, $\chi_4$, and the non-Gaussian parameter, $\alpha_2$. By direct comparison of these two quantities, we are able to highlight similarities and differences. We do confirm that $\chi_4$ and $\alpha_2$ provide qualitatively similar information, but we find quantitative discrepancies in the scalings of characteristic time and length scale on approaching the glass transition.Comment: The original publication is available at http://www.scichina.com and http://www.springerlink.com http://engine.scichina.com/publisher/scp/journal/SCPMA/doi/10.1007/s11433-019-9401-x?slug=abstrac

Ultra-long range correlations of the dynamics of jammed soft matter

We use Photon Correlation Imaging, a recently introduced space-resolved dynamic light scattering method, to investigate the spatial correlation of the dynamics of a variety of jammed and glassy soft materials. Strikingly, we find that in deeply jammed soft materials spatial correlations of the dynamics are quite generally ultra-long ranged, extending up to the system size, orders of magnitude larger than any relevant structural length scale, such as the particle size, or the mesh size for colloidal gel systems. This has to be contrasted with the case of molecular, colloidal and granular ``supercooled'' fluids, where spatial correlations of the dynamics extend over a few particles at most. Our findings suggest that ultra long range spatial correlations in the dynamics of a system are directly related to the origin of elasticity. While solid-like systems with entropic elasticity exhibit very moderate correlations, systems with enthalpic elasticity exhibit ultra-long range correlations due to the effective transmission of strains throughout the contact network.Comment: To appear in Soft Matte

Static/Dynamic Filtering for Mesh Geometry

The joint bilateral filter, which enables feature-preserving signal smoothing according to the structural information from a guidance, has been applied for various tasks in geometry processing. Existing methods either rely on a static guidance that may be inconsistent with the input and lead to unsatisfactory results, or a dynamic guidance that is automatically updated but sensitive to noises and outliers. Inspired by recent advances in image filtering, we propose a new geometry filtering technique called static/dynamic filter, which utilizes both static and dynamic guidances to achieve state-of-the-art results. The proposed filter is based on a nonlinear optimization that enforces smoothness of the signal while preserving variations that correspond to features of certain scales. We develop an efficient iterative solver for the problem, which unifies existing filters that are based on static or dynamic guidances. The filter can be applied to mesh face normals followed by vertex position update, to achieve scale-aware and feature-preserving filtering of mesh geometry. It also works well for other types of signals defined on mesh surfaces, such as texture colors. Extensive experimental results demonstrate the effectiveness of the proposed filter for various geometry processing applications such as mesh denoising, geometry feature enhancement, and texture color filtering

Smart Surrogate Widgets for Direct Volume Manipulation

Interaction is an essential aspect in volume visualization, yet common manipulation tools such as bounding boxes or clipping plane widgets provide rather crude tools as they neglect the complex structure of the underlying data. In this paper, we introduce a novel volume interaction approach based on smart widgets that are automatically placed directly into the data in a visibility-driven manner. By adapting to what the user actually sees, they act as proxies that allow for goal-oriented modifications while still providing an intuitive set of simple operations that is easy to control. In particular, our method is well-suited for direct manipulation scenarios such as touch screens, where traditional user interface elements commonly exhibit limited utility. To evaluate out approach we conducted a qualitative user study with nine participants with various backgrounds.acceptedVersio

MHD consistent cellular automata (CA) models II. Applications to solar flares

In Isliker et al. (2000b), an extended cellular automaton (X-CA) model for solar flares was introduced. In this model, the interpretation of the model's grid-variable is specified, and the magnetic field, the current, and an approximation to the electric field are yielded, all in a way that is consistent with Maxwell's and the MHD equations. Here, we reveal which relevant plasma physical processes are implemented by the X-CA model and in what form, and what global physical set-up is assumed by this model when it is in its natural state (SOC). The basic results are: (1) On large-scales, all variables show characteristic quasi-symmetries. (2) The global magnetic topology forms either (i) closed magnetic field lines, or (ii) an arcade of field lines above the bottom plane line, if the model is slightly modified. (3) In case of the magnetic topology (ii), loading can be interpreted as if there were a plasma which flows predominantly upwards, whereas in case of the magnetic topology (i), as if there were a plasma flow expanding from the neutral line. (4) The small-scale physics in the bursting phase represent localized diffusive processes. (5) The local diffusivity usually has a value which is effectively zero, and it turns locally to an anomalous value if a threshold is exceeded, whereby diffusion dominates the quiet evolution (loading). (6) Flares (avalanches) are accompanied by the appearance of localized, intense electric fields. (7) In a variant on the X-CA model, the magnitude of the current is used directly in the instability criterion. First results indicate that the SOC state persists. (8) The current-dissipation during flares is spatially fragmented into a large number of dissipative current-surfaces of varying sizes, which show a highly dynamic temporal evolution.Comment: 13 pages, 12 figures; in press at Astronomy and Astrophysics (2001