We consider $A \in \mathcal{S}_n(\mathbb{R})$ symmetric with eigenvalues $\lambda_1 \leqslant \cdots \leqslant \lambda_n$ and corresponding orthonormal basis of eigenvectors $\left(\mathbf{w}_1, \ldots, \mathbf{w}_n\right)$. We set $B = A + \mathbf{u u}^T$ with $\|\mathbf{u}\| = 1$. Suppose in this question that $\lambda_1 < \lambda_2 < \cdots < \lambda_n$, and that $J = \{1,2,\ldots,n\}$. For $x \in \mathbb{R} \backslash \left\{\lambda_1, \ldots, \lambda_n\right\}$ we set $$f(x) = \sum_{k=1}^n \frac{\left\langle \mathbf{w}_k, \mathbf{u} \right\rangle^2}{x - \lambda_k}.$$
(a) Show that $f$ is of class $C^\infty$ on $\mathbb{R} \backslash \left\{\lambda_1, \ldots, \lambda_n\right\}$, and calculate its derivative $f'(x)$.
(b) Show that the equation $f(x) = 1$ has a unique solution in each interval $]\lambda_\ell, \lambda_{\ell+1}[$ for all $\ell \in \{1,2,\ldots,n-1\}$, and in $]\lambda_n, +\infty[$.
(c) We denote by $\mu_1 \leqslant \mu_2 \leqslant \cdots \leqslant \mu_n$ the eigenvalues of $B$. Show that $$\lambda_1 < \mu_1 < \lambda_2 < \mu_2 < \cdots < \lambda_n < \mu_n.$$

In this fourth part, $A \in \mathcal{S}_n(\mathbb{R})$ is a symmetric matrix whose eigenvalues are denoted $\lambda_1 \leqslant \lambda_2 \leqslant \cdots \leqslant \lambda_n$. We consider an arbitrary orthonormal basis $\left(\mathbf{u}_1, \ldots, \mathbf{u}_n\right)$. Let $\mathbf{U}$ be a random variable taking values in the finite set $\left\{\mathbf{u}_1, \ldots, \mathbf{u}_n\right\}$, following the uniform distribution on this set. We consider the random variable $B = A + \mathbf{U}\mathbf{U}^T$. Prove that there exists $x \in \mathbb{R}$ such that $\mathbb{E}\left[\chi_B(x)\right] \neq 0$.

We fix an integer $d \in \mathbb{N}^*$, and we equip $\mathbb{R}^d$ with the usual inner product denoted $\langle \cdot, \cdot \rangle$ and the associated Euclidean norm $\|\cdot\|$. We denote $C := \{x \in \mathbb{R}^d \mid \|x\| \leq 1\}$ the closed unit ball of $\mathbb{R}^d$. Let $M$ be a nonzero real symmetric matrix of size $d \times d$ such that $\forall x \in \mathbb{R}^d,\, \langle x, Mx \rangle \geq 0$. We define $f(x) := -\frac{1}{2}\langle x, Mx \rangle$. Describe the set of minimizers of $f$ on $C$.

Let $n$ be the index of $u$, that is, the integer such that $u^{n-1} \neq 0$ and $u^n = 0$. Prove that there exists a vector $v$ such that $v$ is an eigenvector of $h$ and $u^{n-1}(v) \neq 0$.

Prove that if a complex number $\lambda$ is an eigenvalue of $M$, then $-\lambda$ is also an eigenvalue of $M$ with the same multiplicity.

Let $x \in \mathbb{R}$ and let $$P = \left[\begin{array}{lll}1 & 1 & 1 \\ 0 & 2 & 2 \\ 0 & 0 & 3\end{array}\right], \quad Q = \left[\begin{array}{ccc}2 & x & x \\ 0 & 4 & 0 \\ x & x & 6\end{array}\right] \text{ and } R = PQP^{-1}$$
Then which of the following options is/are correct?
(A) There exists a real number $x$ such that $PQ = QP$
(B) $\det R = \det\left[\begin{array}{lll}2 & x & x \\ 0 & 4 & 0 \\ x & x & 5\end{array}\right] + 8$, for all $x \in \mathbb{R}$
(C) For $x = 0$, if $R\left[\begin{array}{l}1 \\ a \\ b\end{array}\right] = 6\left[\begin{array}{l}1 \\ a \\ b\end{array}\right]$, then $a + b = 5$
(D) For $x = 1$, there exists a unit vector $\alpha\hat{i} + \beta\hat{j} + \gamma\hat{k}$ for which $R\left[\begin{array}{l}\alpha \\ \beta \\ \gamma\end{array}\right] = \left[\begin{array}{l}0 \\ 0 \\ 0\end{array}\right]$

Let $A = \left[ \begin{array} { l l } a & b \\ c & d \end{array} \right]$ and $B = \left[ \begin{array} { l } \alpha \\ \beta \end{array} \right] \neq \left[ \begin{array} { l } 0 \\ 0 \end{array} \right]$ such that $A B = B$ and $a + d = 2021$, then the value of $a d - b c$ is equal to $\_\_\_\_$.

Let $A$ be a $2 \times 2$ real matrix and $I$ be the identity matrix of order 2 . If the roots of the equation $| A - x I | = 0$ be - 1 and 3 , then the sum of the diagonal elements of the matrix $A ^ { 2 }$ is $\_\_\_\_$ .

Let $A$ be a $2 \times 2$ symmetric matrix such that $A \left[ \begin{array} { l } 1 \\ 1 \end{array} \right] = \left[ \begin{array} { l } 3 \\ 7 \end{array} \right]$ and the determinant of $A$ be 1 . If $A ^ { - 1 } = \alpha A + \beta I$, where $I$ is an identity matrix of order $2 \times 2$, then $\alpha + \beta$ equals $\_\_\_\_$

Let $B = \left[ \begin{array} { l l } 1 & 3 \\ 1 & 5 \end{array} \right]$ and $A$ be a $2 \times 2$ matrix such that $A B ^ { - 1 } = A ^ { - 1 }$. If $B C B ^ { - 1 } = A$ and $C ^ { 4 } + \alpha C ^ { 2 } + \beta I = O$, then $2 \beta - \alpha$ is equal to
(1) 16
(2) 2
(3) 8
(4) 10

Consider a discrete-time system where stochastic transitions between the two states (A and B) occur as shown in Figure 2.1. The transition probability in unit time from the state A to B is $\alpha$ and from the state B to A is $\beta$. Note that $0 < \alpha < 1$ and $0 < \beta < 1$. Variables $n$ and $k$ represent discrete time and are integers greater than or equal to 0.
Answer the following questions.

1. Let $P_{\mathrm{A}}(n)$ be the probability that the state is A at time $n$ and $P_{\mathrm{B}}(n)$ be the probability that the state is B at time $n$. Let $\boldsymbol{P}(n) = \binom{P_{\mathrm{A}}(n)}{P_{\mathrm{B}}(n)}$. Express matrix $\boldsymbol{M}$ using $\alpha$ and $\beta$, assuming $\boldsymbol{P}(n+1) = \boldsymbol{M}\boldsymbol{P}(n)$.
2. Obtain all eigenvalues and the corresponding eigenvectors of matrix $\boldsymbol{M}$.
3. As time tends towards infinity, the probability that the state is A and the probability that the state is B converge towards constant values. Obtain each value.
4. Assume $R_{\mathrm{A}}(n) = P_{\mathrm{A}}(n) - \lim_{k \rightarrow \infty} P_{\mathrm{A}}(k)$. Express $R_{\mathrm{A}}(n+1)$ by using $R_{\mathrm{A}}(n)$.