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Hi @h-OUS-e

  1. I'm a bit confused. Every time you have an intersection, you can just save si.p to some normal Python list. In addition, of course, you'll want to save a mask to know which rays are still active.

Note: You'll most likely want to use a recorded loop (mi.Loop) for performance which is incompatible with what I mentioned above about visualizations. So you can either use a normal Python loop, or not save ray paths during optimization or even have a separate code path just for the visualizations.

  1. As long as you keep Mitsuba/DrJit types it will remain a differentiable computation. However I'm uncertain if your specific optimization would require more advances techniques to handle …

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