VIZ@CINT

Contacts: A. Balatsky (avb@lanl.gov), J. Haraldsen (jasonh@lanl.gov), M. Graf (graf@lanl.gov)

At the CINT Gateway at Los Alamos National Laboratory Theory thrust scientists have access to advanced active stereo three-dimensional visualization tools. By bringing visualization tools and a stereo visualization laboratory in close proximity, CINT is empowering the individual researcher in materials science and nanoscience with unprecedented capabilities to explore and analyze complex or multi-dimensional datasets

In nanoscience, materials science and condensed matter physics researchers are more and more often overwhelmed by the amount or complexity of data produced in table-top experiments or numerical computations. Our understanding of collected or calculated data is sometimes limited by the means of how well we can visualize or present it. Visualization enhances our ability to see unexpected patterns, phenomena or correlations in measurements and simulations. The lack of proper visualization can be responsible for our failure to understand the true meaning of our data. This becomes especially important when dealing with a large parameter space of unknowns in experiment or theory, or when quantifying differences between datasets and images.

A layman's explination:

"What is visualization?" [excerpt from the article by M.J. Graf et al, SciDAC 10, 32 (Dec. 2008) http://www.scidacreview.org/0804/html/cint.html

Visualization is the process of creating a visual representation of scientific results in order to enhance our understanding. Two major steps are involved in visualization:

  1. A visualization step, that means applying a visualization algorithm that creates a visual representation.
  2. A rendering step, that means the display of this visual representation.

Different algorithms can highlight different aspects of a scientific result. For example, a contouring algorithm shows the relationship between a given value in a dataset. A cut plane operation produces a plane containing the data where it intersects the dataset, the resultant plane dataset can have further visualization operations performed on it. When presenting a complex relationship in a dataset, it can be helpful to use the many visual cues, including spatial dimensions (1,2, or 3 dimensions), color, depth, shading and evolution in time.

Interactivity, the ability to quickly manipulate and dynamically explore a dataset by rotating, panning and zooming, is very useful to understand a dataset's internal structure and relationships. Rendering is the simulation of the physics of light interacting on a collection of objects. Scientific visualization algorithms create these geometric objects. It is important to provide depth cues in order to understand three dimensional datasets, objects and their structure.

In the real world, we get depth cues by having a different image come to each eye (stereoscopic viewing). These images are processed by the brain to form a three-dimensional model of the scene we are viewing. A similar process is possible using stereo technology. Passive stereo techniques use static lens/filters to present a different image to each eye. An example of this is red-blue stereo, in which a user wears a pair of glasses with a red and a blue lens. When rendering, each image is a composite of a left eye image in blue and a right eye image in red. The red filter removes the red data, showing a left-eye perspective (i.e. blue image content) to the left eye. Using a blue filter, a right-eye perspective (i.e. red image content) is shown to the right eye. Active stereo techniques use shutters that alternate showing left eye and right eye views blocking one eye from viewing while the other eye views the scene from their perspective. CINT has chosen an active stereo solution for their visualization laboratory. We have installed a stereo rear-projection system connected to a high-end graphics workstation in parallel with desktop 3D viewing.

Collected together, visualization and rendering algorithms form a visualization tool. There are a number of commercial and open-source visualization tools available. For CINT, we use primarily ParaView (www.paraview.org) and VisIt (www.llnl.gov/VisIt), because both offer a full suite of visualization and rendering capabilities and are freely available under an open-source license.

 

Visualization projects