minkwe wrote:Heinera wrote:minkwe wrote:Heinera,
Both you and Richard claim QM/non-locality/non-realism/statistical error can violate the above theorem but LHV can not. The challenge quite simply is to produce the non-local/non-real/statistical dataset which demonstrates the violation. Richard claims to have written the simulation, we will see if it holds up. We will calculate delta from his dataset, and obtain the appropriate upper bound using his theorem. Hopefully for Richard, his claim will hold up because all his papers and claims are at stake.
Ok, so let us try this again: I can produce a non-local hidden variable model that beats the CHSH inequality by a safe margin; in fact it gives the same value for the inequality as QM does. It uses no data rejection, no loopholes.
And furthermore, all the four correlations can be computed on the same set of hidden variables. No disjoint sets.
Would that be of interest?
Please proceed. We will use Richard's LG theorem to calculate the appropriate bound and we will see if your non-local model holds up. If it is calculated on the same set then delta will be zero and the upper bound will be 2. But no need to explain just provide the dataset and we'll see.
Here is the model:
http://rpubs.com/heinera/16727
It is a simple non-local HV model without data rejection of any kind; no loopholes. It beats the CHSH inequality with a safe margin, even when all four correlations are computed on the same set of hidden variables.
Hopefully this example will make you realise that the CHSH inequality only applies to LHV models.

