Infinitely often and almost always

From Machinelearning

Let A1,A2,A3,… be a sequence of events in some sample space Ω. Let ω∈Ω be an outcome.

In the following table, all statements in the "infinitely often" column are logically equivalent. Similarly, all statements in the "almost always" column are logically equivalent.

perspective infinitely often almost always
unions and intersections ω∈⋂N=1∞⋃n=N∞An ω∈⋃N=1∞⋂n=N∞An
first-order quantifiers ∀N≥1∃n≥N:ω∈An ∃N≥1∀n≥N:ω∈An
verbal expression ω∈An for infinitely many n≥1 ω∈An for almost all n≥1, i.e. ω∈An for all but finitely many n≥1, i.e. ω∉An for finitely many n≥1
lim sup/lim inf ω∈lim supn→∞An ω∈lim infn→∞An
limit of sup/inf ω∈limN→∞⋃n=N∞An ω∈limN→∞⋂n=N∞An

Analogy with sequences of real numbers

Let (an)n=1∞ be a sequence of real numbers, let ϵ>0 be a real number, and let x be a real number.

We say (an)n=1∞ is eventually ϵ-close to x iff there exists some N≥1 such that for all n≥N we have |an−x|≤ϵ.

We say that (an)n=1∞ is continually ϵ-adherent iff for every N≥1 there exists some n≥N such that |an−x|≤ϵ.

I think we can even define An:={x∈R:|an−x|≤ϵ}.