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It's not practical to simply insert autodiff variables, aka var into algorithms like lanczos. What's generally done is to implicitly calculate those derivatives using the derivatives of coefficient matrices. See https://jackd.github.io/posts/generalized-eig-jvp/. In that case, one can use AD for coefficient matrix derivatives.
Is it possible to use this library for standard/general eigenvalue problems?
I have an application for quantum chemistry in mind which requires the iterative solution of an general eigenvalue problem.
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