Publications and Preprints
positive linear maps and spreads of matrices
by
Rajendra Bhatia and Rajesh Sharma
The farther a normal matrix is from being a scalar, the more dispersed its eigenvalues
should be. There are several inequalities in matrix analysis that render this principle more
precise. Here it is shown how positive unital linear maps can be used to derive many of these
inequalities.
isid/ms/2014/14 [fulltext]
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