Eigenvectors from EigenvaluesPar Eric Antoine Scuccimarra
This paper was released over the summer which describes a newly discovered method for obtaining eigenvectors from eigenvalues. While this method only works for Hermitian matrices, previous methods for computing eigenvectors were far more complicated and costly. While relatively, easy, it can be quite costly to determine the dominant eigenvector of a matrix, and this process had to be repeated after removing the dominant eigenvector of the matrix in order to compute additional eigenvectors.
This new method shows that there is a straightforward relationship between the normed squared eigenvalues of a matrix, the eigenvalues of submatrices, and the eigenvectors. I can't stress enough how amazing this is. This will require that all linear algebra textbooks be revised.
I have a numpy implementation of this new method available here.
CommentsPlease login to comment
Nov 28, 2019 at 11:32 pm
Hello friends, recently I got into the hands of a unique site where You need to predict how the value will change, up, or down, You have only two buttons to answer, so if you even randomly press the buttons, Your chances are 50% to 50%, and thanks to special techniques that you will find after registration, Your balance will increase every 60 seconds. In one minute you can earn from one dollar to infinity! This is a unique way to earn money on the Internet today, the service has been working since 2014, and always pays the money earned on time. After registration, you will receive a BONUS +10 000b to the account, and will be able to fully test this wonderful service. <a href=http://bit.ly/ol-en2/>Free registration in this service + 10 000b to the account!</a> Try it for FREE. http://bit.ly/ol-en2