sampling

Interactive High-Quality Visualization of Large-Scale Particle Data

Mohamed Ibrahim, Postdoctoral Research Fellow, Computer Science

Nov 5, 14:00 - 15:00

B2 L5 R5209

visualization high-quality rendering large-scale simulation particle data aliasing artifact sampling visible particles

Large-scale particle data sets, such as those computed in molecular dynamics (MD) simulations, are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulations with 10 million particles or more, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry.

Stochastic Optimal Control with Exercise Rate Optimization and Markovian Projections: Pricing American Options and Importance Sampling Applications

Raul Tempone, Professor, Applied Mathematics and Computational Sciences

Oct 31, 15:30 - 17:00

B5 L5 R5209

sampling Markovian projection

This talk begins with the problem of pricing American basket options in a multivariate setting. In high dimensions, nonlinear PDE methods for solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation become expensive due to the curse of dimensionality.