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Investigate error propagation with JAX autodiff #30

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redeboer opened this issue Jun 1, 2022 · 1 comment
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Investigate error propagation with JAX autodiff #30

redeboer opened this issue Jun 1, 2022 · 1 comment
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redeboer commented Jun 1, 2022

It would be great if JAX autodiff could be applied to the polarization functions in order to get an idea of sensitivity to the parameter uncertainties with error propagation. See here for an example how to do this with JAX. See also ComPWA/tensorwaves#442.

That said, I tried to compute the Jacobian for $\alpha_x$ and ran out of memory for only a tiny Dalitz plot sample. Even differentiating to just one coupling parameter, I could compute that differential only for 10x10 points without running into memory problems.
@redeboer redeboer self-assigned this Jun 1, 2022
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redeboer commented Jun 4, 2022

Boot-strapping will be used instead

@redeboer redeboer closed this as not planned Won't fix, can't repro, duplicate, stale Jun 4, 2022
@redeboer redeboer modified the milestone: 0.0.1 Sep 3, 2022
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