Timeline for Diagonalizing a block tridiagonal matrix
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| Jul 26 at 7:37 | comment | added | Ritteraxt | Right now I am not doing any of it, Im just using scipy's standard algorithm. I was hoping that someone could suggest me a fast way to do it, not even necessarily with the quoted paper. | |
| Jul 17 at 6:56 | comment | added | Sakurai.JJ | @Ritteraxt In your suggested paper, we need to find $\lambda$ which satisfies ${\rm det}P_{K}(\lambda)=0$, right? But how did you do that? Did you find the closed form of $\lambda$? I am reading Section 3-1. | |
| Sep 6, 2022 at 9:27 | history | edited | Ritteraxt | CC BY-SA 4.0 |
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| Aug 2, 2022 at 11:54 | comment | added | Ritteraxt | Thanks for your interest! I described the exact form of the matrix including a minimal reproducible example in here: stackoverflow.com/questions/73195156/… | |
| Aug 2, 2022 at 11:02 | comment | added | Fred Hucht | Ok, then it might be helpful to get more information about the $A_i$. | |
| Aug 2, 2022 at 9:08 | comment | added | Ritteraxt | Yes, I fear that my problem does indeed require to compute the eigenvectors and eigenvalues. | |
| Aug 1, 2022 at 20:01 | comment | added | Fred Hucht | Are you sure that you need explicit eigenvalues? Often it is sufficient (or even advantageous) to work with the characteristic polynomial (cp) instead, especially if you want to calculate, e.g., the sum or product of a function of the eigenvalues, see arxiv.org/abs/2103.10776 for an example. The cp of your matrix can be calculated using the block transfer matrix method of Molinari, see arxiv.org/abs/0712.0681. | |
| S Aug 1, 2022 at 12:44 | review | First questions | |||
| Aug 1, 2022 at 13:16 | |||||
| S Aug 1, 2022 at 12:44 | history | asked | Ritteraxt | CC BY-SA 4.0 |