Complex matrix to Block Matrix

AI Thread Summary
To redefine a complex matrix as a block matrix, it is essential to separate the real and imaginary parts, allowing for the application of solvers that only handle real matrices. The matrix M is expressed as M = A + iB, where A and B represent the real and imaginary components, respectively. Finding eigenvalues and eigenvectors requires careful consideration of the normalization of A and B, as altering one may disrupt the other. The complexity of the calculations can often yield more eigenvalues than real matrices, making complex representations advantageous. Ultimately, the challenge lies in maintaining the integrity of both components while transforming the matrix.
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How can I redefine my Complex matrix to a Block matrix, similar as matrix representation of complex number.
I need a Real an Imaginary part as real numbers, to find eigenvalues and eigenvectors with my solver, which works only with Real matrices.

My matrix element is:
M_{mn}=\int^{tk}_{0} -i Exp[i E_{mn} t] V_{mn}(t) dt
The integrals are easy to write, but are complex.
I want to write matrix M as new matrix of dimension 2N to find eigenvectors and eigenvalues of that matrix, which are also complex.
 
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We basically have the situation ##M=A+iB##. In order to diagonalize ##M## or to use some normal form, we need to know something about the components ##A## and ##B##. If we find a normalization for ##A##, it could well ruin the structure of ##B## and vice versa. So in any case, the question isn't answerable in this generality. Moreover, complex calculations are usually better than real ones, since we have more eigenvalues available.
 
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