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> [!definition]
> Let $(\Omega_\alpha, \FFF_\alpha)_{\alpha\in I}$ be a collection of measure spaces. The ==**product $\sigma$-field**== $\FFF = \bigotimes_{\alpha\in I} \FFF_\alpha$ is the minimal $\sigma$-field over $\Omega = \bigotimes_{\alpha \in I} \Omega_\alpha$ such that each projection map $\pi_\alpha: \Omega\to \Omega_{\alpha}$ is measurable; equivalently, it is the $\sigma$-algebra generated by
> $ E_\alpha \times \prod_{\gamma \in I\setminus \{a\}} \Omega_\gamma$
> for all $\alpha$.
>[!idea]
>If this isn't reminiscent of the [[product topology]], you're actually blind.
The main intuition is that a product space should be independent in each of its projections.
We're sometimes interested in the sets
$ \Omega_J = \prod_{\alpha \in J} \Omega_\alpha,\qquad \FFF_J = \bigotimes_{\alpha\in J} \FFF_\alpha$ which are the partial products over subsets $J\subset I$; this will be standard notation.
>[!example]
>It's useful to note that
>$ \AAA_0 = \{(\pi_J)^{-1}(E_J) = E_J\times \Omega_{I\setminus J}: \abs{J} < \infty, E_J\subset F_J\}$
>is an algebra generating our product $\sigma$-algebra.
# How we want the Product Measure to behave
The main intuition is that a product space should be independent in each of its projections.
> [!definition] Marginals
> Let $J\subset I$ be finite, and let $\PP$ be a measure on $\Omega$. Then, the ==**finite-dimensional marginal**== (or ==**distribution**==) of $\PP$ on $J$ is the pushforward measure $\PP_J = (\pi_J)_\sharp (\PP)$ on $(\Omega_J, \FFF_J)$. Explicitly,
> $ \PP_J(E) = \PP(E\times \Omega_{I\setminus J})$
> for all $E\subset F_J$.
We want these finite-dimensional marginals to all be self-consistent; if $J'\subset J\subset I$ are finite subsets, then the marginal $\PP_{J'}$ should be the same whether we project from $I$ to $J'$ or through $J$.