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The conventional signal model of confocal sensors is well established and has proven to be exceptionally robust especially when measuring rough surfaces. Its physical derivation however is explicitly based on plane surfaces or point like objects, respectively. Here we show experimental results of a confocal point sensor measurement of a surface standard. The results illustrate the rise of severe artifacts when measuring curved surfaces. On this basis, we present a systematic extension of the conventional signal model that is proven to be capable of qualitatively explaining these artifacts.

Ray tracing still is the workhorse in optical design and simula- tion. Its basic principle, propagating light as a set of mutually independent rays, implies a linear dependency of the computational effort and the num- ber of rays involved in the problem. At the same time, the mutual independ- ence of the light rays bears a huge potential for parallelization of the computational load. This potential has recently been recognized in the visualization community, where graphics processing unit (GPU)-acceler- ated ray tracing is used to render photorealistic images. However, preci- sion requirements in optical simulation are substantially higher than in visualization, and therefore performance results known from visualization cannot be expected to transfer to optical simulation one-to-one. In this contribution, we present an open-source implementation of a GPU-accel- erated ray tracer, based on nVidias acceleration engine OptiX, that traces in double precision and exploits the massively parallel architecture of modern graphics cards. We compare its performance to a CPU-based tracer that has been developed in parallel. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. (DOI: 10.1117/1.OE.52.5.053004) Subject terms: ray tracing; graphics processing unit-accelerated computing; optical simulation.