Matrix aggregating methods¶
SpAbs¶
\[{\rm SpAbs} = \sum_{i = 1}^N \left| \lambda_i \right|\]
where \(\lambda_i\) is \(i\)-th eigenvalue.
SpMax¶
\[{\rm SpMax} = \max_{i = 1}^N \lambda_i\]
SpDiam¶
\[{\rm SpDiam} = {\rm SpMax} - {\rm SpMin}\]
SpAD¶
\[{\rm SpAD} = \sum_{i = 1}^N \left| \lambda_i - \bar{\lambda} \right|\]
LogEE¶
\[{\rm LogEE} = \log(\sum_{i = 1}^N \exp(\lambda_i))\]
SM1¶
\[{\rm SM1} = \sum_{i = 1}^N \lambda_i\]
VE1¶
\[{\rm VE1} = \sum_{i = 1}^N \left| \ell_i \right|\]
where \(\ell_i\) is eigenvector elements corresponding to leading eigenvalue.
VE2¶
\[{\rm VE2} = \frac{\rm VE1}{A}\]
VR1¶
\[{\rm VR1} = \sum_{(i, j) \in {\rm bonds}} \left( \ell_i \cdot \ell_j \right)^{-1/2}\]
VR2¶
\[{\rm VR2} = \frac{\rm VR1}{A}\]