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Abstract
\baselineskip=13pt We consider two types of majorization relationships between sequences of vectors y=(yk)k=1m and x=(xk)k=1ℓ in Rn with ℓ≤m. It is said that x is majorized by y, x≺y, if the sum of any k vectors from x is in the convex hull of all possible sums of k vectors from y. It is said that x is doubly stochastically majorized by y, x≺dsy, if xk=∑j=1mmkjyj, k=1,...,ℓ, for some doubly stochastic matrix M=(mkj)k,j=1m,m. \par In a recent article ["Inverse spectral problem for normal matrices and the Gauss-Lucas Theorem", Trans. Amer. Math. Soc. 357(10) (2004) 4043--4064] S. M. Malamud formulated the problem of finding a geometric condition guaranteeing that x≺y⇔x≺dsy. We answer this question in the case when the vectors in y are distinct and are extreme points of their convex hull. In particular, we derive a geometric characterization of the extreme points of the level set L≺2(y)={x:x≺y}. Finally, we derive a set of algebraic conditions that characterize the extreme points of L≺ℓ(y)={x:x≺y} for any ℓ≤m and y.
Author information
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PF
Pal Fischer
Dept. of Mathematics and Statistics, University of Guelph, Guelph, Ontario N1G 2W1, Canada