Importance Sampling and Adjoint Hybrid Methods in Monte Carlo Transport with Reflecting Boundaries

Details Importance Sampling and Adjoint Hybrid Methods in Monte Carlo Transport with Reflecting Boundaries Importance Sampling and Adjoint Hybrid Methods in Monte Carlo Transport with Reflecting Boundaries

2011-04-13

arxiv.org/abs/1104.2550v1

Physics

Mathematical Physics

Scientific paper

Adjoint methods form a class of importance sampling methods that are used to accelerate Monte Carlo (MC) simulations of transport equations. Ideally, adjoint methods allow for zero-variance MC estimators provided that the solution to an adjoint transport equation is known. Hybrid methods aim at (i) approximately solving the adjoint transport equation with a deterministic method; and (ii) use the solution to construct an unbiased MC sampling algorithm with low variance. The problem with this approach is that both steps can be prohibitively expensive. In this paper, we simplify steps (i) and (ii) by calculating only parts of the adjoint solution. More specifically, in a geometry with limited volume scattering and complicated reflection at the boundary, we consider the situation where the adjoint solution "neglects" volume scattering, whereby significantly reducing the degrees of freedom in steps (i) and (ii). A main application for such a geometry is in remote sensing of the environment using physics-based signal models. Volume scattering is then incorporated using an analog sampling algorithm (or more precisely a simple modification of analog sampling called a heuristic sampling algorithm) in order to obtain unbiased estimators. In geometries with weak volume scattering (with a domain of interest of size comparable to the transport mean free path), we demonstrate numerically significant variance reductions and speed-ups (figures of merit).

Affiliated with

Also associated with

No associations

Rating

Importance Sampling and Adjoint Hybrid Methods in Monte Carlo Transport with Reflecting Boundaries does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Importance Sampling and Adjoint Hybrid Methods in Monte Carlo Transport with Reflecting Boundaries, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Importance Sampling and Adjoint Hybrid Methods in Monte Carlo Transport with Reflecting Boundaries will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-219728