Birkhoff's theorem #
Main statements #
doublyStochastic_eq_sum_perm
: IfM
is a doubly stochastic matrix, then it is a convex combination of permutation matrices.doublyStochastic_eq_convexHull_perm
: The set of doubly stochastic matrices is the convex hull of the permutation matrices.extremePoints_doublyStochastic
: The set of extreme points of the doubly stochastic matrices is the set of permutation matrices.
TODO #
- Show that for
x y : n → R
,x
is majorized byy
if and only if there is a doubly stochastic matrixM
such thatM *ᵥ y = x
.
Tags #
Doubly stochastic, Birkhoff's theorem, Birkhoff-von Neumann theorem
If M is a doubly stochastic matrix, then it is an convex combination of permutation matrices. Note
doublyStochastic_eq_convexHull_permMatrix
shows doublyStochastic n
is exactly the convex hull of
the permutation matrices, and this lemma is instead most useful for accessing the coefficients of
each permutation matrices directly.
Birkhoff's theorem
The set of doubly stochastic matrices is the convex hull of the permutation matrices. Note
exists_eq_sum_perm_of_mem_doublyStochastic
gives a convex weighting of each permutation matrix
directly. To show doublyStochastic n
is convex, use convex_doublyStochastic
.
The set of extreme points of the doubly stochastic matrices is the set of permutation matrices.