Computing matrix derivatives for eigenvaule sensitivity analysis

Seems reasonable to me.

(Edited: I had read the first half of your post and started to write out exactly what you suggested.)

Note that ChainRules.jl includes rules for eigenvalue differentiation, if I recall correctly. But they are based on a dense-matrix eigen routine, so they aren’t appropriate if you are computing just one eigenvalue (and corresponding eigenvalues), e.g. by some Krylov method.

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