I am interested in computing a small proportion (between 3 and 10% of the matrix size) of the eigenvalues of a matrix with extended precision. As a toy example, let’s take the matrix A define by: T = Complex{Float128} N = 64 A = Tridiagonal(rand(T, N - 1), rand(T, N), rand(T, N - 1)) The following…

I think what you need in addition is using GenericSchur. At least this is what allows one to use ArnoldiMethod.jl with arbitrary float types. julia> using ArnoldiMethod, GenericSchur, DoubleFloats julia> T = Complex{Double64} Complex{Double64} julia> N = 64 64 julia> A = Tridiagonal(rand(T, N - …

Eigenvalues and extended precision

Specific Domains Numerics

rveltz September 14, 2021, 8:53am 9

You should open an issue because it should be type agnostic

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Eigenvalues and extended precision

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