Let $x_n$ be a sequence of reals. Show that $$\delta_{x_n}\xrightarrow{w}\delta_{x} \iff x_n \to x$$
Since the weak convergence is equivalent to pointwise convergence of characteristic functions and since $$\varphi_{\delta_x}(t)=\int e^{its} \ d\delta_x(s) = e^{itx}$$ the "$\Leftarrow$" direction follows with continuity of $e^{it(\cdot)}$.
I am somewhat confused about the "$\Rightarrow$" direction. At first, I was going to do pretty much the same but with $\log$ yet I recalled that the complex log isn't continuous.
What is the proper way to do it?
Let $F,F_n$ denote the CDF's of probability measures $\delta_{x}$ and $\delta_{x_n}$. These are the characteristic functions of the sets $[x,\infty)$ and $[x_n,\infty)$.
Then: $$\delta_{x_{n}}\stackrel{w}{\rightarrow}\delta_{x}\iff\forall y\neq x\; F_{n}\left(y\right)\rightarrow F\left(y\right)$$
This because $F$ is continuous at $y$ if and only if $y\neq x$.
Assume that $x_{n}$ does not converge to $x$.
Then some $\epsilon>0$ can be found such that $\left|x-x_{n}\right|>\epsilon$ for $n$ large enough and a subsequence $\left(x_{n_{k}}\right)$ must exist with $x_{n_{k}}>x+\epsilon$ for each $k$ or $x_{n_{k}}<x-\epsilon$ for each $k$.
In the first case for $y\in\left(x,x+\epsilon\right)$ we have $F\left(y\right)=1$ and $F_{n_k}\left(y\right)=0$ for each $k$.
In the second case for $y\in\left(x-\epsilon,x\right)$ we have $F\left(y\right)=0$ and $F_{n_k}\left(y\right)=1$ for each $k$.
So in both cases we find that $\delta_{x_{n}}\stackrel{w}{\rightarrow}\delta_{x}$ is not true.
Proved is now $\neg x_{n}\rightarrow x\Rightarrow\neg\delta_{x_{n}}\stackrel{w}{\rightarrow}\delta_{x}$ or equivalently $\delta_{x_{n}}\stackrel{w}{\rightarrow}\delta_{x}\Rightarrow x_{n}\rightarrow x$.