![]() Well, the difference I am talking/writing about is nothing very deep and complicated, it is just that while in Julia you are computing eigenvalues for a sequence/array of matrices, and you obtain a sequence of vectors of eigenvalues, in Matlab you are computing eigenvalues for a function of a single parameter, at which, lucky you, Symbolic toolbox succeeded, and you get a vector of five functions. I may have a look at it, but I am not quite fluent with symbolics in Julia unfortunately. to generate the Laplacian matrix and its eigenvalues and eigenvectors. An example of the eigenvalue and singular value decompositions of a small square matrix is provided by one of the test matrices from the Matlab gallery. plot energy (eigenvalue) as a function of position. The Essentials - Functions required to run nearly every subsequent MATLAB script. ![]() Therefore, rather than investigating the issue of possibly different ordering of eigenvalues in Julia compared to Matlab, you may have to think about how to compute eigenvalues of a matrix parameterized by a single (symbolic) parameter eps in Julia, which is what you did in Matlab. MATLAB is excellent handling matrices and vectors operations. Strict Matlab equivalent of your Julia code is mu = 57.88e-3 Į(:,i)=eig(A) %energy levels (eigenvalues) The linewidth argument to the plot command tells MATLAB to plot these lines with a thickness of 3 points so that they are more visible. It is rather that in Matlab you solve the problem much differently than in Julia. Strictly speaking, this is not much about ordering of eigenvalues in Matlab vs ordering of eigenvalues in Julia. I will be tweaking the parameters so ideally don’t want to have to go back in and adjust it every time the points of intersection change. A real n by n matrix A has n eigenvalues (counting multiplicities) which are either real or occur in complex conjugate pairs. 2 Answers Sorted by: 1 I have found where your problem is : your eigenvectors are not orthogonal due to a sign error: the matrix of eigenvectors should be: 0.7351 0.6778 0.7351 0.6778 +0. So essentially I want to replicate the ordering Matlab’s eig function uses without switching the eigenvalues after the fact. The points of intersection are important and unfortunately, I lose them in the Julia code because of the ascending order.
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