stevendaryl said:
... So that model predicts the red graph.
You are right that the graph is for spin-1/2, I actually didn't even look at the scale.
The issue is that the graph is a readout of a DIFFERENCE between 2 measurement settings. So first you must say whether your model is intended to be rotationally invariant. The graph is for such models. Yours is if the original spin vector S is randomly oriented across some series of trials. So Alice and Bob obviously won't know that orientation.
Let's assume Alice and Bob are both set at 0 degrees and there is no classical interaction related to their settings. The red graph predicts anti-correlation. But that doesn't occur in those cases in which S is oriented at 90 degrees. Alice's overlap produces a 50-50 outcome for +1 and -1, and Bob's overlap produces a 50-50 outcome for -1 and +1. So in those cases, there is NO correlation at all. At other angles, there is varying anti-correlation. When you integrate across all possible S, you get correlation varying from -.5 to +.5 - which is NOT the red line. (And perhaps I am not following your model correctly at this point, not entirely sure.)
The only way to get the red line is if ALL possible outcomes (for each angle setting) are pre-determined and fixed prior to measurement. There can be no probability relating to an interaction with Alice or Bob. So it might look something like the following:
S oriented at 17 degrees (changes from pair to pair):
A@17 degrees, B@17 degrees: + -
A@18 degrees, B@18 degrees: + -
A@19 degrees, B@19 degrees: - +
A@20 degrees, B@20 degrees: + -
A@21 degrees, B@21 degrees: + -
...
A@105 degrees, B@105 degrees: - +
A@106 degrees, B@106 degrees: + -
A@107 degrees, B@107 degrees: - +
A@108 degrees, B@108 degrees: + -
A@109 degrees, B@109 degrees: - +
...
A@194 degrees, B@194 degrees: - +
A@195 degrees, B@195 degrees: + -
A@196 degrees, B@196 degrees: - +
A@197 degrees, B@197 degrees: - +
This allows Alice and Bob to always get the same results at the same settings. Of course, what is above is a full blown local hidden variables model and if that is the effect of the Bloch sphere model, then I would agree with you.