If $X,Y \subset \mathbb{R}$ are measure zero sets, how can I show that $X \times Y \subset \mathbb{R^2}$ is a measure zero set too?
My outline is the following:
Since $X,Y$ is a measure zero set, we can find open intervals $U_i$ and $V_j$ for $X$ and $Y$, respectively. Then, the union of the open intervals is a cover for $X$ and $Y$. That part I have been able to do. However, I need to show now that the sum of the measures of $(U_i \times V_j)$ can be written less than any arbitrary $\epsilon >0$. That is:
$$ \sum_{i,j}|(U_i \times V_j)| < \epsilon $$
Since by definition of $X,Y$ being a measure zero set, we have
$$ \sum_{i}|U_i| < \sqrt{\epsilon} \\ \text{and} \sum_{j}|V_j| < \sqrt{\epsilon} $$
It then makes logical sense that we want
$$ \sum_{i,j}|(U_i \times V_j)| < \sum_{i}|U_i| \cdot \sum_{j}|V_j| < \sqrt{\epsilon} \cdot \sqrt{\epsilon} < \epsilon $$
Does anyone know how I can get the relation:
$$ \sum_{i,j}|(U_i \times V_j)| < \sum_{i}|U_i| \cdot \sum_{j}|V_j| $$
by something simple like the triangle inequality without having to resort to heavy measure theory? Thanks!
$U_i \times V_i$ is an open rectangle. Use the formula for the measure of a rectangle, and apply the distributive law:
$$\sum_{i=1}^m\sum_{j=1}^na_ib_j = \left(\sum_{i=1}^ma_i\right)\left(\sum_{j=1}^jb_j\right)$$
to the resulting sum of products.