grandes-ecoles 2023 Q13

grandes-ecoles · France · mines-ponts-maths2__pc Matrices Linear Transformation and Endomorphism Properties
We consider the Euclidean space $E = \mathscr{M}_{N,1}(\mathbf{R})$ equipped with the inner product $\langle X, Y \rangle = \sum_{i=1}^{N} X[i] Y[i] \pi[i]$, where $\pi$ is a $\pi$-reversible probability for the Markov kernel $K$. We consider the endomorphism of $E$ defined by $u : X \mapsto (I_N - K)X$. Show that $\ker(u) = \operatorname{Vect}(U)$ and that $u$ is a self-adjoint endomorphism of $E$.
We consider the Euclidean space $E = \mathscr{M}_{N,1}(\mathbf{R})$ equipped with the inner product $\langle X, Y \rangle = \sum_{i=1}^{N} X[i] Y[i] \pi[i]$, where $\pi$ is a $\pi$-reversible probability for the Markov kernel $K$.\\
We consider the endomorphism of $E$ defined by $u : X \mapsto (I_N - K)X$. Show that $\ker(u) = \operatorname{Vect}(U)$ and that $u$ is a self-adjoint endomorphism of $E$.