In (Brunner et al. 2013), the authors mention (end of pag. 6) that a set of correlations p(ab|xy) can be nonlocal only if Δ≥2 and m≥2, where Δ is the number of measurement outcomes for the two parties (that is, the number of different values that a and b can assume), and m the number of measurement settings that one can choose from (that is, the number of values of x and y).
A probability distribution p(ab|xy) is here said to be nonlocal if it can be written as p(ab|xy)=∑λq(λ)p(a|x,λ)p(b|y,λ).
The Δ=1 (only one measurement outcome) case is trivial: if this is the case, denoting with 1 the only possible measurement outcome, we have p(11|xy)=1 for all x,y. Without even needing the hidden variable, we can thus just take p(1|x)=p(1|y)=1 and we get the desired decomposition (1).
The m=1 case, however, is less trivial. In this case the question seems equivalent to asking whether an arbitrary probability distribution p(a,b) can be written as p(a,b)=∑λq(λ)p(a|λ)p(b|λ).
Answer
Make a λa,b for every pair (a,b).
Then make q(λa,b)=p(a,b), and
p(a|λa,b)=p(b|λa,b)=1.
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