ABSTRACT:In this article, we present a new LINear Constraint Solver Ž . LINCS for molecular simulations with bond constraints. The algorithm is inherently stable, as the constraints themselves are reset instead of derivatives of the constraints, thereby eliminating drift. Although the derivation of the algorithm is presented in terms of matrices, no matrix matrix multiplications are needed and only the nonzero matrix elements have to be stored, making the method useful for very large molecules. At the same accuracy, the LINCS algorithm is three to four times faster than the SHAKE algorithm. Parallelization of the algorithm is straightforward.
Abstract-We present a technique for the illustrative rendering of 3D line data at interactive frame rates. We create depth-dependent halos around lines to emphasize tight line bundles while less structured lines are de-emphasized. Moreover, the depth-dependent halos combined with depth cueing via line width attenuation increase depth perception, extending techniques from sparse line rendering to the illustrative visualization of dense line data. We demonstrate how the technique can be used, in particular, for illustrating DTI fiber tracts but also show examples from gas and fluid flow simulations and mathematics as well as describe how the technique extends to point data. We report on an informal evaluation of the illustrative DTI fiber tract visualizations with domain experts in neurosurgery and tractography who commented positively about the results and suggested a number of directions for future work.
Molecular systems may be visualized with various degrees of structural abstraction, support of spatial perception, and ‘illustrativeness.’ In this work we propose and realize methods to create seamless transformations that allow us to affect and change each of these three parameters individually. The resulting transitions give viewers a dedicated control of abstraction in illustrative molecular visualization and, consequently, allow them to seamlessly explore the resulting abstraction space for obtaining a fundamental understanding of molecular systems. We show example visualizations created with our approach and report informal feedback on our technique from domain experts.
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