- #1
ilvreth
- 33
- 0
Hi to all.
Say that you have an eigenvalue problem of a Hermitian matrix ##A## and want (for many reasons) to calculate the eigenvalues and eigenstates for many cases where only the diagonal elements are changed in each case.
Say the common eigenvalue problem is ##Ax=λx##. The ##A## matrix is a sum of two matrices ##A=B+C## and the ##C## matrix contains only the diagonal elements non-zero. For example
\begin{equation}
\begin{pmatrix}
E_{1}& a & b \\
c & E_{2}& d \\
e & f & E_{3}
\end{pmatrix}
=
\begin{pmatrix}
0& a & b \\
c& 0 & d \\
e& f & 0
\end{pmatrix}
+
\begin{pmatrix}
E_{1}& 0 & 0 \\
0& E_{2} & 0 \\
0& 0 & E_{3}
\end{pmatrix}
\end{equation}Say you want to calculate the eigenstates of the ##A## matrix but in a different way.
I was thinking is there is a method which is used to split the problem in two other sub-problems. The first step to be something like to calculate something for the ##B## matrix which remains unchanged in each case so the calculation is performed only one time, in the second step you only perform calculations for the ##C## matrix which in any case onlyn the diagonal elements are changed so you have to work only with the ##C## matrix problem and finally you combine the data of these two matrices in order to obtain the final result for the ##A## matrix.
Whats your opinion?
Say that you have an eigenvalue problem of a Hermitian matrix ##A## and want (for many reasons) to calculate the eigenvalues and eigenstates for many cases where only the diagonal elements are changed in each case.
Say the common eigenvalue problem is ##Ax=λx##. The ##A## matrix is a sum of two matrices ##A=B+C## and the ##C## matrix contains only the diagonal elements non-zero. For example
\begin{equation}
\begin{pmatrix}
E_{1}& a & b \\
c & E_{2}& d \\
e & f & E_{3}
\end{pmatrix}
=
\begin{pmatrix}
0& a & b \\
c& 0 & d \\
e& f & 0
\end{pmatrix}
+
\begin{pmatrix}
E_{1}& 0 & 0 \\
0& E_{2} & 0 \\
0& 0 & E_{3}
\end{pmatrix}
\end{equation}Say you want to calculate the eigenstates of the ##A## matrix but in a different way.
I was thinking is there is a method which is used to split the problem in two other sub-problems. The first step to be something like to calculate something for the ##B## matrix which remains unchanged in each case so the calculation is performed only one time, in the second step you only perform calculations for the ##C## matrix which in any case onlyn the diagonal elements are changed so you have to work only with the ##C## matrix problem and finally you combine the data of these two matrices in order to obtain the final result for the ##A## matrix.
Whats your opinion?