Timeline for Efficiently computing a few localized eigenvectors
Current License: CC BY-SA 3.0
3 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Feb 13, 2012 at 18:02 | comment | added | dranxo | As for the size, I'd like to work with larger matrices in the future. The Lanczos idea is interesting. I don't have a good intuition for how the eigenvectors converge so I'm hesitant to throw out candidates that are not localizing early on. | |
| Feb 11, 2012 at 19:36 | comment | added | Suvrit | Actually, a friend of mine who does eigenvectors for a living insisted, that if we are willing to settle for 10% of the spectrum, we might as well compute the whole spectrum for $n$ even as large as 50,000. So I guess, unless absolutely short on storage, for a tiny $1000 \times 1000$ matrix, I would go ahead and compute the entire spectrum. It takes only 3 seconds on my 5 year old laptop to compute the full spectrum of a 1000 x 1000 matrix! | |
| Feb 11, 2012 at 9:15 | history | answered | Federico Poloni | CC BY-SA 3.0 |