How to prove Wielandt minimax formula?
The statements are as follows:
Let $1leqslant i_1<i_2<cdots<i_kleqslant n$ be integers. Define a partial flag to be a nested collection $V_1subset V_2cdotssubset V_k$ of subspaces of $mathbb{C}^n$ s.t. $dim(V_j)=i_j$ for all j between 1 and k. Define the Schubert variety $X(V_1,...,V_k)$ to be the collection of all k-dimensional subspaces W s.t. $dim(Wcap V_j)geqslant j$. Show that for any Hermitian matrix A,
$$lambda_{i_1}+...+lambda_{i_k}=sup_{V_1,...,V_k} inf_{Win X(V_1,...,V_k)}tr(A|_{W})$$.
Where $lambda_{i_j}$ means the $i_j$ th eigenvalue of A, from large to small. The trace in the right formula stands for the partial trace of A on W.
I have proofed that the LHS is no bigger than the RHS using induction on k, but I do not know how to prove the other side.
linear-algebra eigenvalues-eigenvectors random-matrices schubert-calculus
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The statements are as follows:
Let $1leqslant i_1<i_2<cdots<i_kleqslant n$ be integers. Define a partial flag to be a nested collection $V_1subset V_2cdotssubset V_k$ of subspaces of $mathbb{C}^n$ s.t. $dim(V_j)=i_j$ for all j between 1 and k. Define the Schubert variety $X(V_1,...,V_k)$ to be the collection of all k-dimensional subspaces W s.t. $dim(Wcap V_j)geqslant j$. Show that for any Hermitian matrix A,
$$lambda_{i_1}+...+lambda_{i_k}=sup_{V_1,...,V_k} inf_{Win X(V_1,...,V_k)}tr(A|_{W})$$.
Where $lambda_{i_j}$ means the $i_j$ th eigenvalue of A, from large to small. The trace in the right formula stands for the partial trace of A on W.
I have proofed that the LHS is no bigger than the RHS using induction on k, but I do not know how to prove the other side.
linear-algebra eigenvalues-eigenvectors random-matrices schubert-calculus
add a comment |
The statements are as follows:
Let $1leqslant i_1<i_2<cdots<i_kleqslant n$ be integers. Define a partial flag to be a nested collection $V_1subset V_2cdotssubset V_k$ of subspaces of $mathbb{C}^n$ s.t. $dim(V_j)=i_j$ for all j between 1 and k. Define the Schubert variety $X(V_1,...,V_k)$ to be the collection of all k-dimensional subspaces W s.t. $dim(Wcap V_j)geqslant j$. Show that for any Hermitian matrix A,
$$lambda_{i_1}+...+lambda_{i_k}=sup_{V_1,...,V_k} inf_{Win X(V_1,...,V_k)}tr(A|_{W})$$.
Where $lambda_{i_j}$ means the $i_j$ th eigenvalue of A, from large to small. The trace in the right formula stands for the partial trace of A on W.
I have proofed that the LHS is no bigger than the RHS using induction on k, but I do not know how to prove the other side.
linear-algebra eigenvalues-eigenvectors random-matrices schubert-calculus
The statements are as follows:
Let $1leqslant i_1<i_2<cdots<i_kleqslant n$ be integers. Define a partial flag to be a nested collection $V_1subset V_2cdotssubset V_k$ of subspaces of $mathbb{C}^n$ s.t. $dim(V_j)=i_j$ for all j between 1 and k. Define the Schubert variety $X(V_1,...,V_k)$ to be the collection of all k-dimensional subspaces W s.t. $dim(Wcap V_j)geqslant j$. Show that for any Hermitian matrix A,
$$lambda_{i_1}+...+lambda_{i_k}=sup_{V_1,...,V_k} inf_{Win X(V_1,...,V_k)}tr(A|_{W})$$.
Where $lambda_{i_j}$ means the $i_j$ th eigenvalue of A, from large to small. The trace in the right formula stands for the partial trace of A on W.
I have proofed that the LHS is no bigger than the RHS using induction on k, but I do not know how to prove the other side.
linear-algebra eigenvalues-eigenvectors random-matrices schubert-calculus
linear-algebra eigenvalues-eigenvectors random-matrices schubert-calculus
edited 2 days ago
Matt Samuel
37.5k63565
37.5k63565
asked Jul 26 '18 at 16:25
user579758user579758
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