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With Wendelstein 7-X now up and running, and the construction of ITERproceeding, predicting fast-ion losses to sensitive plasma-facing componentsand detectors is gaining significant interest. A common recipe to perform suchstudies is to push a large population of marker particles along their equationsof motion, the trajectories randomized with Monte Carlo operators accountingfor Coulomb collisions, and to record possible intersections of the markertrajectories with synthetic detectors or areas of interest in the first wall.While straightforward to implement and easy to parallelize, this Forward MonteCarlo (FMC) approach tends to suffer from poor statistics and error estimationas the detector domain is often small: it is difficult to guess how to set upthe initial weights and locations of the markers for them to remainrepresentative of the source distribution, yet record enough hits to thedetector for good statistics. As an alternative, the FMC method can be replacedwith a so-called Backward Monte Carlo (BMC) algorithm. Instead of starting witha given initial marker population, one starts from the end condition at thedetector and records how the hit probability evolves backwards in time. Thescheme eliminates the statistics issue present in the FMC scheme and mayprovide more accurate and efficient simulations of fast-ion loss signals. Thepurpose of this paper is to explain the BMC recipe in the fast-ion setting andto discuss the associated nuances, especially how to negate artificialdiffusion. For illustration purposes, our numerical example considers a 1-Dstochastic harmonic oscillator as a mock-up of a charged particle.

Eliminating poor statistics in Monte-Carlo simulations of fast-ion losses to plasma-facing components and detectors