I'm working through some practice problems for my final exam and I would like to get some ideas on tackling this problem:
Let $(\Omega,\mathcal{F})=(\mathbb{R}_+,\mathcal{B}(\mathbb{R}_+))$ and $\text{P}(d\omega)=\exp(-\omega)d\omega$ or equivalently,
$P[(a,b]]=\exp(-a)-\exp(-b)$ for $0\leq a\leq b < \infty$.
Let $X_n(\omega)=1_{[n,\infty)}(\omega)$ for $n\in\mathbb{N}$.
Does $S_n=\sum_{j=1}^n X_j$ converge almost surely to some limit S and does the partial sum $S_n$ converge to S in $L_1$?
My idea for the first part is to use Markov's inequality and Borel-Cantelli and show that $\sum P(|X_n|>\epsilon)<\infty$. I was able to find the probability distribution of $\mu_n(B)$ of $X_n$, for $\forall B\in\mathcal{B}$ to be:
$$ P(X\in B)=\mu_n(B)=\left\{ \begin{aligned} P(\emptyset) = 0 && 0,1\not\in B\\ P\circ X^{-1}[0,n)=1-\exp(-n) && 0\in B, 1\not\in B\\ P\circ X^{-1}[n,\infty)=\exp(-n) && 0\not\in B, 1\in B\\ P\circ X^{-1}[0,\infty)=1 && 0,1\in B \end{aligned} \right. $$
For the second, I don't really have a clue except that i know that $\{X_n\}$ is uniformly integrable since it's uniformly bounded by by an $L_1$ random variable.
Edit: for later viewing